Prame off-target peptides and uses thereof

Abstract

The present disclosure relates to compositions that involve isolated peptides, e.g., PRAME425-433 off-target peptides, and the use of such compositions in methods for assessing off-target effects of antigen-recognition molecules that target a PRAME425-433 peptide, as well as for selecting antigen-recognition molecules and enriching samples for antigen-recognition molecules that specifically bind the PRAME425-433 peptide.

Description

PRAME OFF-TARGET PEPTIDES AND USES THEREOFCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 63 / 665,393, filed June 28, 2024, U.S. Provisional Application No. 63 / 682,544, filed August 13, 2024, and U.S. Provisional Application No. 63 / 805,030, filed May 13, 2025, the disclosure of each of which is incorporated by reference herein in its entirety.SEQUENCE LISTING

[0002] The instant application contains a Sequence Listing which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. Said XML copy, created on June 25, 2025, is named 250298_000953_SL.xml and is 459,983 bytes in size.FIELD

[0001] The present disclosure relates to compositions that involve isolated peptides, e.g., PRAME425 33 off-target peptides, and the use of such compositions in methods for assessing off- target effects of antigen-recognition molecules that target a PRAME425-433 peptide, as well as for selecting antigen-recognition molecules and enriching samples for antigen-recognition molecules that specifically bind the PRAME425-433 peptide.BACKGROUND

[0002] Antigen-recognition molecules, such as T-cell receptors (TCRs) and antibodies, are capable of identifying antigens, which include agents recognized by the immune system of a host as defined herein. Antigen-recognition molecules can help the immune system neutralize an antigen and / or initiate an antigen- specific immune response by binding to an antigenic peptide presented in a complex with a major histocompatibility complex (MHC) molecule (MHC-peptide complex) on the surface of an antigen-presenting cell.

[0003] The MHC-peptide complex is presented on the surface of the antigen-presenting cell as a result of a cellular process in which an MHC gene in the antigen-presenting cell encodes an MHC molecule; the MHC molecule subsequently binds to the antigenic peptide thereby creating the MHC-peptide complex; and the resulting MHC-peptide complex is positioned on the cell surfaceso that a portion of the peptide is presented for binding with an antigen-recognition molecule. Each peptide is made up of a short chain of amino acids, and some of the amino acids of a peptide in an MHC-peptide complex are bound to the MHC molecule while at least some of the remaining amino acids are presented as available for binding with an antigen-recognition molecule. Antigenrecognition molecules are able to bind to a peptide of an MHC-peptide complex on the surface an antigen-presenting cell to help the immune system neutralize the antigen and / or initiate an antigenspecific immune response. This process is an important component of the immune system’s ability to recognize and mount a response against foreign agents.

[0004] This cellular process is also carried out on peptides native to the body. Generally, however, antigen-recognition molecules are able to distinguish between native peptides and nonnative peptides presented on antigen-presenting cells so that normal cells are not attacked by the immune system.

[0005] Research is underway with a goal of isolating (e.g., screening / selecting) and / or engineering antigen-recognition molecules to target cells that would otherwise not be targeted through the above-described mechanism. For instance, cancer cells are native cells that are typically not effectively suppressed by the immune system, and research has shown that it can be possible to use TCRs, antibodies, and other antigen-recognition molecules to target the cancerspecific MHC-peptide complexes on cancer cells. While targeted treatments with antigenrecognition molecules may be effective to neutralize intended target cells, side effects of the treatment may be severe if antigen-recognition molecules bind off-target native cells in addition to the intended target cells. Side effects are often identified during clinical trials, which can result in patient death, other adverse effects on patients, and expenditure of time and resources in research and development. Accordingly, there is a need in the art for methods and systems that allow for accurate and efficient prediction of off-targets to the target peptide of interest which helps evaluate the risk associated with the target peptide at the target selection step as well as help in screening the most specific antigen-recognition molecules.SUMMARY

[0006] In one aspect, provided herein is an isolated peptide comprising an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0007] In some embodiments, the isolated peptide comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181.

[0008] In some embodiments, the isolated peptide consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181.

[0009] In some embodiments, the isolated peptide comprises an amino acid sequence of any one of SEQ ID NOs: 150-153.

[0010] In some embodiments, the isolated peptide consists of an amino acid sequence of any one of SEQ ID NOs: 150-153.

[0011] In some embodiments, the isolated peptide comprises an amino acid sequence of SEQ ID NO: 151.

[0012] In some embodiments, the isolated peptide consists of an amino acid sequence of SEQ ID NO: 151.

[0013] In some embodiments, the isolated peptide comprises one or more non-proteogenic amino acids, one or more non-naturally occurring amino acids, one or more non-native peptide bonds, or any combination thereof, optionally wherein the isolated peptide comprises one or more reverse peptide bonds, one or more D-isomers of amino acids, one or more chemical modifications, or any combination thereof.

[0014] In some embodiments, the isolated peptide is produced by expression in a heterologous host cell.

[0015] In some embodiments, the isolated peptide is produced synthetically.

[0016] In some embodiments, the isolated peptide, or fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-23 amino acids in length, or 8-17 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

[0017] In another aspect, provided herein is a fusion protein comprising one or more peptides described herein, or fragments or derivatives thereof, fused to one or more heterologous molecules.

[0018] In some embodiments, the one or more heterologous molecules comprise an MHC molecule, or a fragment or derivative thereof.

[0019] In some embodiments, the MHC molecule is a class I MHC molecule.

[0020] In some embodiments, the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

[0021] In some embodiments, the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

[0022] In some embodiments, the HLA-A molecule is an HLA-A*02:01 molecule.

[0023] In another aspect, provided herein is a conjugate comprising one or more peptides described herein, or fragments or derivatives thereof, conjugated to one or more heterologous molecules.

[0024] In some embodiments, the one or more heterologous molecules comprise an MHC molecule, or a fragment or derivative thereof.

[0025] In some embodiments, the MHC molecule is a class I MHC molecule.

[0026] In some embodiments, the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

[0027] In some embodiments, the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

[0028] In some embodiments, the HLA-A molecule is an HLA-A*02:01 molecule.

[0029] In some embodiments, the one or more peptides, or fragments or derivatives thereof, are conjugated to a particle or a solid support.

[0030] In another aspect, provided herein is an oligomeric complex comprising two or more isolated peptides described herein or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0031] In another aspect, provided herein is a non-covalent complex comprising (i) an isolated peptide described herein or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and (ii) an MHC molecule, or a fragment or derivative thereof.

[0032] In some embodiments, the MHC molecule is a class I MHC molecule.

[0033] In some embodiments, the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

[0034] In some embodiments, the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

[0035] In some embodiments, the HLA-A molecule is an HLA-A*02:01 molecule.

[0036] In another aspect, provided herein is a composition comprising (i) one or more isolated peptides described herein, one or more fusion proteins described herein, one or more conjugates described herein, one or more oligomeric complexes described herein, or one or more non-covalent complexes described herein, or any combination thereof; and (ii) a carrier or excipient.

[0037] In another aspect, provided herein is an isolated cell comprising one or more fusion proteins described herein, one or more conjugates described herein, one or more oligomeric complexes described herein, or one or more non-covalent complexes described herein, or any combination thereof.

[0038] In some embodiments, the isolated cell is an immune cell.

[0039] In some embodiments, the isolated cell is an antigen-presenting cell (APC).

[0040] In another aspect, provided herein is an isolated polynucleotide comprising a nucleotide sequence encoding one or more isolated peptides described herein or one or more fusion proteins described herein.

[0041] In some embodiments, the nucleotide sequence is operably linked to a promoter.

[0042] In some embodiments, the isolated polynucleotide comprises DNA.

[0043] In some embodiments, the isolated polynucleotide comprises RNA.

[0044] In some embodiments, the RNA is mRNA.

[0045] In some embodiments, the RNA is self-replicating RNA.

[0046] In another aspect, provided herein is a vector comprising an isolated polynucleotide described herein.

[0047] In some embodiments, the vector is an expression vector.

[0048] In some embodiments, the vector is a viral vector.

[0049] In another aspect, provided herein is a host cell comprising an isolated polynucleotide described herein or a vector described herein.

[0050] In some embodiments, the host cell is a prokaryotic cell.

[0051] In some embodiments, the host cell is a eukaryotic cell.

[0052] In some embodiments, the host cell is an immune cell.

[0053] In some embodiments, the host cell is an antigen-presenting cell (APC).

[0054] In another aspect, provided herein is a composition comprising (i) an isolated polynucleotide described herein or a vector described herein; and (ii) a carrier or excipient.

[0055] In some embodiments, the carrier is a lipid nanoparticle carrier. In another aspect, provided herein is a composition comprising (i) one or more isolated peptides described herein, one or more fusion proteins described herein, one or more conjugates described herein, one or more oligomeric complexes described herein, one or more non-covalent complexes described herein, or one or more cells described herein, or any combination thereof, conjugated to a solid support.

[0056] In some embodiments, the solid support is a multi-well plate.

[0057] In another aspect, provided herein is a kit comprising:(i) a) one or more isolated peptides described herein; b) one or more fusion proteins described herein; c) one or more conjugates described herein; d) one or more oligomeric complexes described herein; e) one or more non-covalent complexes described herein; f) one or more compositions described herein; g) one or more cells described herein; h) one or more polynucleotides described herein; and / or i) one or more vectors described herein;(ii) optionally, an antigen-recognition molecule that targets PRAME425-433 peptide; and / or(iii) optionally, packaging and / or instructions for use for the same.

[0058] In some embodiments, the antigen-recognition molecule(s) comprises an antibody, a T cell receptor (TCR), or a chimeric antigen receptor (CAR).

[0059] In another aspect, provided herein is an in vitro method of assessing off-target effects of an antigen-recognition molecule that targets PRAME425-433 peptide, comprising: a) contacting the antigen-recognition molecule with PRAME425-433 peptide presented in a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-PRAME425-433 peptide complex); b) contacting the antigen-recognition molecule with one or more off-target peptides, wherein each of said off-target peptides (i) comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, , and (ii) is presented in a complex with the same kind of MHC molecule, or the fragment or derivative thereof, as in (a) (MHC- off-target peptide complex); and c) determining the level of binding of the antigen-recognition molecule to the MHC- PRAME425-433 peptide complex and each of the MHC-off-target peptide complexes.

[0060] In another aspect, provided herein is an in vitro method of assessing off-target effects of an antigen-recognition molecule that targets PRAME425-433 peptide, comprising: a) contacting the antigen-recognition molecule with one or more off-target peptides, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and wherein each of said off-target peptides is presented in one of the following forms: (1) as a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-off-target peptide complex), (2) as a peptide, or (3) as a protein or fragment thereof comprising said peptide; and b) determining the level of binding of the antigen-recognition molecule to said one or more MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides.

[0061] In some embodiments, each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0062] In some embodiments, each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0063] In some embodiments, each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0064] In some embodiments, each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0065] In some embodiments, the off-target peptide comprises an amino acid sequence of SEQ ID NOs: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0066] In some embodiments, the off-target peptide consists of an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0067] In some embodiments of the above-described in vitro methods, the method further comprises determining that the antigen-recognition molecule is likely to have off-target effects ifit detectably binds to at least one MHC-off-target peptide complex, off-target peptide or protein or fragment thereof comprising said off-target peptide.

[0068] In another aspect, provided herein is method for selecting an antigen-recognition molecule that targets PRAME425-433 peptide, comprising: a) contacting a plurality of antigen-recognition molecules with PRAME425-433 peptide presented in a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-PRAME425-433 peptide complex); b) contacting the same plurality of antigen-recognition molecules with one or more off-target peptides, (i) wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and (ii) wherein each of said off-target peptides is presented in one of the following forms: (1) as a complex with the same kind of MHC molecule, or the fragment or derivative thereof as in (a) (MHC-off-target peptide complex), (2) as a peptide, or (3) as a protein or fragment thereof comprising said off-target peptide; c) selecting one or more antigen-recognition molecules based on their level of binding to MHC-PRAME425 -433 peptide complex and based at least in part on the number of different MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides detectably bound by each of the antigenrecognition molecules; and d) optionally, repeating steps (a)-(c) using the one or more selected antigenrecognition molecules.

[0069] In some embodiments, each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0070] In some embodiments, each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0071] In some embodiments, each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0072] In some embodiments, each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0073] In some embodiments, the off-target peptide comprises an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0074] In some embodiments, the off-target peptide consists of an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0075] In some embodiments, the one or more selected antigen-recognition molecules delectably bind no more than five MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides.

[0076] In some embodiments, the one or more selected antigen-recognition molecules do not detectably bind to any of the tested MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides.

[0077] In some embodiments, the plurality of antigen-recognition molecules is in a library.

[0078] In some embodiments, the library is a phage display library or a yeast library.

[0079] In some embodiments, one or more of the MHC-PRAME425-433 peptide complexes, MHC- off-target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides, are immobilized on a solid support.

[0080] In some embodiments, one or more of the MHC-PRAME425-433 peptide complexes, MHC- off-target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides, are present on a surface of a cell.

[0081] In some embodiments, the antigen-recognition molecule is likely to have off-target effects if it detectably binds to at least one MHC-off-target peptide complex, or off-target peptide or protein or fragment thereof comprising said off-target peptide, when the off-target peptide is present on a surface of a cell at a copy number of at least about 1,000 copies / cell.

[0082] In some embodiments, the one or more selected antigen-recognition molecules do not detectably bind to any of the tested MHC-off-target peptide complexes, or off-target peptides or proteins or fragments thereof comprising said off-target peptides, when the off-target peptide is present on a surface of a cell at a copy number of at least about 1,000 copies / cell.

[0083] In some embodiments, each of said one or more off-target peptides is presented as an MHC-off-targct peptide complex, or a fragment or derivative thereof, on a surface of a cell at a copy number of at least about 1,000 copies / cell.

[0084] In some embodiments, one or more of the MHC-PRAME425-m peptide complexes, MHC- off-target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides are present in a soluble form.

[0085] In some embodiments, the level of binding is determined by detecting the amount of antigen-recognition molecules bound to the MHC-PRAME425-433 peptide complexes, MHC-off- target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off- target peptides.

[0086] In some embodiments, the method is performed in a high-throughput format.

[0087] In some embodiments, the method is performed in a multi-well plate.

[0088] In another aspect, provided herein is a method of enriching a sample for antigenrecognition molecules that target PRAME425-433 peptide, comprising: a) contacting a sample comprising a plurality of antigen-recognition molecules with PRAME425-433 peptide presented in a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-PRAME425-433 peptide complex) in the presence of one or more off-target peptides, wherein each of said off-target peptides (i) comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, wherein each of said one or more off-target peptides is presented in one of the following forms: (1) as a complex with an MHC molecule, or a fragment or derivative thereof (MHC -off-target peptide complex), (2) as a peptide, or (3) as a protein or fragment thereof comprising said off-target peptide; b) enriching the sample by isolating the antigen-recognition molecules that are detectably bound to said MHC-PRAME425-433 peptide complex; and c) optionally, repeating steps (a)-(b) using the enriched sample.

[0089] In some embodiments, each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0090] In some embodiments, each of said off-target peptides consists of amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0091] In some embodiments, each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0092] In some embodiments, each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0093] In some embodiments, the off-target peptide comprises an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0094] In some embodiments, the off-target peptide consists of an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0095] In some embodiments, said MHC-PRAME425-433 peptide complex is present on a cell or solid support and said off-target peptides or proteins or fragments thereof comprising said off- target peptides or MHC-off-target peptide complexes are present in solution.

[0096] In some embodiments, said MHC-PRAME425-433 peptide complex is labeled and said off- target peptides or proteins or fragments thereof comprising said off-target peptides or MHC-off- target peptide complexes are not labeled or are labeled differently.

[0097] In some embodiments, the PRAME425-433 peptide comprises the amino acid sequence of SLLQHLIGL (SEQ ID NO: 75).

[0098] In some embodiments, the PRAME425-433 peptide consists of the amino acid sequence SLLQHLIGL (SEQ ID NOs: 75).

[0099] In some embodiments, the off-target peptide comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181.

[0100] In some embodiments, the off-target peptide consists of an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181.

[0101] In some embodiments, each of said off-target peptides is presented as an MHC-off-target peptide complex.

[0102] In some embodiments, the MHC molecule is a class I MHC molecule.

[0103] In some embodiments, the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

[0104] In some embodiments, the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

[0105] In some embodiments, the HLA-A molecule is an HLA-A*02:01 molecule.

[0106] In some embodiments, the peptide within the MHC-PRAME425-433 peptide complex and / or MHC-off-target peptide complex is covalently bound to the MHC.

[0107] In some embodiments, the peptide within the MHC-PRAME425-433 peptide complex and / or MHC-off-target peptide complex is non-covalently bound to the MHC.

[0108] In some embodiments, the antigen-recognition molecule(s) comprises an antibody, a T cell receptor (TCR), or a chimeric antigen receptor (CAR).

[0109] In some embodiments, each of said off-target peptides, or a fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8- 23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

[0110] In another aspect, provided herein is a library of off-target peptides, said library comprising two or more peptides each selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0111] In some embodiments, said library comprises two or more off-target peptides each selected from the amino acid sequences of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0112] In some embodiments, said library comprises two or more off-target peptides each selected from the amino acid sequences of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

[0113] In some embodiments, the at least two off-target peptides are each present in a complex with a major histocompatibility complex (MHC) molecule.

[0114] In some embodiments, the MHC molecule is a class I MHC molecule.

[0115] In some embodiments, the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

[0116] In some embodiments, the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

[0117] In some embodiments, the HLA-A molecule is an HLA-A*02:01 molecule.

[0118] In some embodiments, the peptide within the MHC-off-target peptide complex is covalently bound to the MHC.

[0119] In some embodiments, the peptide within the MHC-off-target peptide complex is non- covalently bound to the MHC.

[0120] In another aspect, provided herein is a library comprising two or more proteins or fragments thereof each comprising one or more off-target peptides, wherein each of said off-targets peptide is selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or fragments or derivatives thereof.

[0121] In some embodiments, each of said off-target peptides is selected from the amino acid sequences of SEQ ID NOs: 151-152 and 154-181, or fragments or derivatives thereof.

[0122] In some embodiments, each of said off-target peptides is selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, and 150, or fragments or derivatives thereof.

[0123] In some embodiments, each of said off-target peptides, or a fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8- 23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

[0124] In another aspect, provided herein is a library comprising: a) two or more isolated peptides described herein; b) two or more fusion proteins described herein; c) two or more conjugatesdescribed herein; d) two or more oligomeric complexes described herein; e) two or more non- covalcnt complexes described herein; f) two or more compositions described herein; g) two or more cells described herein; h) two or more polynucleotides described herein; and / or i) two or more vectors described herein, optionally wherein each element of the library exists in a separate container.

[0125] In some embodiments, each of said isolated peptides, or a fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8- 23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.BRIEF DESCRIPTION OF THE DRAWINGS

[0126] The above and further aspects of this invention should be read with reference to the drawings, in which like elements in different drawings are identically numbered. The drawings, which are not necessarily to scale, depict selected embodiments and are not intended to limit the scope of the invention. The detailed description illustrates by way of example, not by way of limitation, the principles of the invention. This description will clearly enable one skilled in the art to make and use the invention, and describes several embodiments, adaptations, variations, alternatives and uses of the invention, including what is presently believed to be the best mode of carrying out the invention.

[0127] FIG. 1 is a flow diagram illustrating an exemplary method for ranking a plurality of potential off-target peptides of a target peptide.

[0128] FIG. 2 is a flow diagram illustrating an exemplary method for providing one or more comparison MHC-off-target models for comparison to an MHC-target model.

[0129] FIG. 3 is a flow diagram illustrating an exemplary method for quantifying structural similarity between a potential off-target peptide in a groove of an MHC molecule and a targetpeptide in complex with the MHC molecule for the purposes of antigen-recognition molecule binding.

[0130] FIG. 4 is a flow diagram illustrating an exemplary method for identifying potential off- target peptide(s) based on sequence similarity and structural similarity for an antigen-recognition molecule that recognizes a target peptide presented in complex with an MHC molecule (MHC- target peptide complex).

[0131] FIG. 5 is a flow diagram illustrating an exemplary method for ranking potential target peptides to mitigate off-target toxicity.

[0132] FIG. 6 is a block diagram of an exemplary system for development of an antigen recognition molecule.

[0133] FIG. 7 is a block diagram of an exemplary structure -based off-target prediction engine.

[0134] FIG. 8 is a block diagram of an embodiment of the structure-based off-target prediction engine.

[0135] FIG. 9 is a block diagram of another embodiment of the structure-based off-target prediction engine.

[0136] FIG. 10 illustrates a block diagram of an exemplary embodiment of a target toxicity database.

[0137] FIG. 11 illustrates a block diagram of an embodiment of a computing device.

[0138] FIG. 12 illustrates a block diagram of an embodiment of a computing network.

[0139] FIG. 13 illustrates cellular functions related to the example embodiments presented herein.

[0140] FIG. 14 is a block diagram of an embodiment of the structure-based off-target prediction engine applied as a proof of concept to a A G’E43 / 6, - / 76 (EVDPIGHLY (SEQ ID NO: 29)) - HLA- A*01:01 complex.

[0141] FIG. 15 is a block diagram of another embodiment of the structure-based off-target prediction engine applied as a proof of concept to a MAGEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) - HLA-A*01:01 complex.

[0142] FIGs. 16A through 16E include a chart in which 231 potential off-target peptides of the MA GEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) - HLA-A*01:01 complex are ranked according to root mean square deviation (RMSD) of conformation of the respective off-target peptide to the target peptide. FIG. 16A includes the top 50 off-target peptides, i.e., highest priority, highestranked off-target peptides. FIG. 16A discloses SEQ ID NOS 202-207, 47, 208-214, 216-219, 215, 220-230, 45, 261-266, 232, and 267-278, respectively, in order of appearance. FIG. 16B includes the 51stthrough 100thranked off-target peptides. FIG. 16B discloses SEQ ID NOS 279-324, 39, and 325-327, respectively, in order of appearance. FIG. 16C includes the 101stthrough 150thranked off-target peptides. FIG. 16C discloses SEQ ID NOS 328-339, 44, 340-352, 231, 353-368, 32, 369, 41, and 370-373, respectively, in order of appearance. FIG. 16D includes the 151stthrough 200thranked off-target peptides. FIG. 16D discloses SEQ ID NOS 374-392, 43, 393-418, 30, and 419-421, respectively, in order of appearance. FIG. 16E includes the 201stthrough 231stranked off-target peptides. FIG. 16E discloses SEQ ID NOS 422-437, 31, and 438-451, respectively, in order of appearance.

[0143] FIGs. 17A through 17E include a chart in which 231 potential off-target peptides of the MA GEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) - HLA-A*01:01 complex are ranked according to root mean square deviation (RMSD) of conformation of the respective off-target peptide and HLA groove to the target HLA-peptide complex. FIG. 17A includes the top 50 off-target peptides, i.e., highest priority, highest ranked off-target peptides. FIG. 17A discloses SEQ ID NOS 47, 45, 209, 231-232, 321, 39, 218, 215, 217, 368, 313, 281, 263, 431, 269, 443, 452, 294, 314, 207, 361,346, 283, 223, 227, 279, 204, 332, 406, 342, 213, 261, 367, 325, 324, 229, 203, 326, 339, 369, 208, 374, 340, 320, 216, 211, 319, 268, and 225, respectively, in order of appearance. FIG. 17B includes the 51stthrough 100thranked off-target peptides. FIG. 17B discloses SEQ ID NOS 262, 205, 311, 376, 286, 214, 438, 206, 301, 389, 344, 222, 296, 380, 219, 32, 271, 212, 440, 336, 333, 322, 210, 221, 273, 266, 354, 416, 226, 338, 270, 295, 299, 364, 435, 427, 419, 312, 334, 350, 335, 317, 331, 228, 377, 407, 297, 359, 292, and 449, respectively, in order of appearance. FIG. 17C includes the 101stthrough 150thranked off-target peptides. FIG. 17C discloses SEQ ID NOS 363, 293, 396, 316, 291, 351, 373, 399, 43, 309, 308, 372, 337, 304, 274, 362, 387, 224, 403, 415, 202, 392, 288, 352, 30, 451, 328, 421, 285, 381, 408, 298, 425, 353, 386, 409, 400, 275, 341, 422, 414, 277, 300, 411, 441, 429, 410, 357, 358, and 437, respectively, in order of appearance. FIG. 17D includes the 151stthrough 200thranked off-target peptides. FIG. 17D discloses SEQ ID NOS 404, 379, 278, 315, 306, 398, 397, 302, 402, 264, 453, 375, 318, 230, 284, 282, 307, 329, 370,347, 428, 348, 417, 310, 265, 436, 276, 378, 395, 267, 433, 442, 401, 323, 413, 280, 394, 366, 220, 371, 305, 349, 287, 360, 384, 289, 450, 44, 365, and 343, respectively, in order of appearance. FIG. 17E includes the 201stthrough 231stranked off-target peptides. FIG. 17E discloses SEQ IDNOS 430, 303, 426, 423, 41 , 424, 432, 393, 439, 418, 444, 355, 446, 390, 290, 356, 383, 412, 385, 388, 272, 330, 420, 345, 31, 405, 448, 327, 391, 445, and 447, respectively, in order of appearance.

[0144] FIGs. 18A through 18F include a chart in which 231 potential off-target peptides of the MAGEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) - HLA-A*01:01 complex are ranked according to similarity of molecular surface interaction fingerprints (MSIFs) of the respective off-target peptide and HLA groove to the target HLA-peptide complex. FIG. 18A includes the top 50 off- target peptides, i.e., highest priority, highest ranked off-target peptides. FIG. 18A discloses SEQ ID NOS 311, 419, 292, 452, 359, 318, 229, 209, 47, 269, 43, 223, 232, 357, 44, 393, 399, 447, 309, 387, 317, 203, 424, 306, 453, 215, 383, 261, 320, 421, 380, 427, 301, 308, 414, 362, 406, 281, 325, 369, 270, 213, 290, 342, 454, 202, 341, 287, 265, and 207, respectively, in order of appearance. FIG. 18B includes the 51stthrough 100thranked off-target peptides. FIG. 18B discloses SEQ ID NOS 206, 347, 397, 413, 355, 30, 435, 405, 450, 381, 319, 339, 312, 299, 219, 214, 221, 327, 295, 375, 263, 332, 222, 402, 288, 417, 390, 204, 225, 230, 389, 358, 321, 386, 337, 374, 330, 437, 368, 348, 227, 446, 45, 267, 403, 316, 216, 336, 277, and 338, respectively, in order of appearance. FIG. 18C includes the 101stthrough 150thranked off-target peptides. FIG. 18C discloses SEQ ID NOS 326, 291, 212, 268, 224, 226, 443, 367, 39, 377, 329, 324, 379, 353, 401, 363, 211, 378, 400, 231, 266, 384, 278, 433, 279, 310, 360, 280, 349, 286, 428, 333, 31, 404, 334, 425, 407, 373, 442, 217, 305, 345, 307, 432, 303, 208, 285, 429, 356, and 282, respectively, in order of appearance. FIG. 18D includes the 151stthrough 200thranked off-target peptides. FIG. 18D discloses SEQ ID NOS 436, 409, 351, 331, 340, 364, 323, 431, 395, 366, 408, 272, 296, 275, 274, 293, 361, 398, 262, 376, 372, 346, 300, 273, 370, 297, 411, 322, 220, 394, 276, 392, 371, 304, 388, 422, 210, 426, 445, 412, 448, 264, 396, 41, 328, 314, 441, 423, 410, and 343, respectively, in order of appearance. FIG. 18E includes the 201stthrough 231stranked off-target peptides. FIG. 18E discloses SEQ ID NOS 294, 271, 335, 420, 350, 391, 438, 283, 354, 315, 289, 218, 344, 32, 416, 298, 444, 451, 418, 415, 313, 430, 449, 385, 228, 302, 205, 284, 352, 440, and 439, respectively, in order of appearance. FIG. 18F discloses SEQ ID NOS 311, 419, 292, 452, 359, 318, 229, 209, 47, 269, respectively, in order of appearance.

[0145] FIG. 19A illustrates a superposition of a 3D computational model of the MAGEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) in a complex with the HLA-A*01:01 MHC molecule and a 3D computational model of the TTN off-target peptide ESDPIVAQY (SEQ ID NO: 47) in the groove of the HLA-A*01:01 molecule.

[0146] FTG. 19B illustrates a superposition of a 3D computational model of the TTN off-target peptide ESDPIVAQY (SEQ ID NO: 47) in the groove of the HLA-A*01:01 molecule and an experimentally determined 3D computational model of the TTN off-target peptide ESDPIVAQY (SEQ ID NO: 47) in the groove of the HLA-A*01:01 molecule for the sake of verifying the exemplary methods illustrated in FIGs. 14 and 15.

[0147] FIG. 20A illustrates a superposition of a 3D computational model of the MAGEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) in a complex with the HLA-A*01:01 MHC molecule and a 3D computational model of the MRPL43 potential off-target peptide TVDPISSSL (SEQ ID NO: 202) in the groove of the HLA-A*01:01 molecule.

[0148] FIG. 20B illustrates a superposition of a 3D computational model of the MAGEA3168-176 (EVDPIGHLY (SEQ ID NO: 29)) in a complex with the HLA-A*01:01 MHC molecule and a 3D computational model of the IGHM off-target peptide ESATITCLV (SEQ ID NO: 204) in the groove of the HLA-A*01:01 molecule.

[0149] FIG. 21 is a block diagram of an embodiment of the structure-based off-target prediction engine applied as a proof of concept to a WT1126- 134 RMFPNAPYL (SEQ ID NO: 241)- HLA- A*02:01 complex.

[0150] FIGs. 22 A through 22D include a chart in which 142 potential off-target peptides of the WT1126- 134 RMFPNAPYL (SEQ ID NO: 241)- HLA-A*02:01 complex are ranked according to root mean square deviation (RMSD) of conformation of the respective off-target peptide to the target. FIG. 22A includes the top 40 off-target peptides, i.e., highest priority, highest ranked off- target peptides. FIG. 22A discloses SEQ ID NOS 455-457, 235, 238, 458-463, 237, 464, 240, 465-467, 233, and 468-489, respectively, in order of appearance. FIG. 22B includes the 41stthrough 80thranked off-target peptides. FIG. 22B discloses SEQ ID NOS 490-503, 239, and 504- 528, respectively, in order of appearance. FIG. 22C includes the 81stthrough 120thranked off- target peptides. FIG. 22C discloses SEQ ID NOS 529-549, 236, and 550-567, respectively, in order of appearance. FIG. 22D includes the 121stthrough 142ndranked off-target peptides. FIG. 22D discloses SEQ ID NOS 568-586 and 249-251, respectively, in order of appearance.

[0151] FIGs. 23A through 23D include a chart in which 142 potential off-target peptides of the WT1126- 134 RMFPNAPYL(SEQ ID NO: 241) - HLA-A*02:01 complex are ranked according to root mean square deviation (RMSD) of conformation of the respective off-target peptide to the target at residue positions 1, 2, 3, and 4 only. FIG. 23 A includes the top 40 off-target peptides,i.e., highest priority, highest ranked off-target peptides. FTG. 23A discloses SEQ ID NOS 488, 505, 457, 237, 552, 504, 578, 570, 528, 482, 463, 553, 235, 238, 455, 495, 456, 236, 240, 233, 467, 479, 500, 459, 501, 466, 525, 522, 511, 506, 516, 518, 503, 567, 475, 458, 476, 531, 513, and 470, respectively, in order of appearance. FIG. 23B includes the 41stthrough 80thranked off-target peptides. FIG. 23B discloses SEQ ID NOS 535, 494, 461, 468, 559, 496, 558, 557, 460, 524, 462, 478, 473, 489, 465, 464, 491, 477, 481, 517, 472, 469, 498, 471, 573, 530, 583, 521, 250, 249,586, 561, 581, 541, 508, 572, 585, 502, 251, and 564, respectively, in order of appearance. FIG.23C includes the 81stthrough 120thranked off-target peptides. FIG. 23C discloses SEQ ID NOS 239, 580, 515, 538, 512, 520, 497, 551, 532, 523, 534, 487, 545, 499, 529, 484, 582, 542, 574,483, 568, 480, 509, 533, 550, 526, 566, 560, 555, 577, 543, 527, 576, 569, 507, 565, 474, 563,575, and 584, respectively, in order of appearance. FIG. 23D includes the 121stthrough 142ndranked off-target peptides. FIG. 23D discloses SEQ ID NOS 490, 493, 519, 547, 485, 546, 549, 514, 571, 537, 486, 562, 492, 510, 536, 556, 544, 554, 579, 548, and 539-540, respectively, in order of appearance.

[0152] FIG. 24A illustrates a superposition of a 3D computational model of the WT1126-134 RMFPNAPYE (SEQ ID NO: 241) target peptide in a complex with the HLA-A*02:01 MHC molecule and a 3D computational model of the SF3B4 off-target peptide KEYGKPIRV (SEQ ID NO: 235) in the groove of the HLA-A*02:01 molecule.

[0153] FIG. 24B illustrates a superposition of a 3D computational model of the WT1126-134 RMFPNAPYE (SEQ ID NO: 241) target peptide in a complex with the HEA-A*02:01 MHC molecule and a 3D computational model of the IEF2 off-target peptide KIEPTEEAV (SEQ ID NO: 233) in the groove of the HEA-A*02:01 molecule.

[0154] FIG. 24C illustrates a superposition of a 3D computational model of the WT1126-134 RMFPNAPYE (SEQ ID NO: 241) target peptide in a complex with the HLA-A*02:01 MHC molecule and a 3D computational model of the USP9Y off-target peptide RLWGEPVNL (SEQ ID NO: 240) in the groove of the HLA-A*02:01 molecule.

[0155] FIG. 24D illustrates a superposition of a 3D computational model of the WT1126-134 RMFPNAPYE (SEQ ID NO: 241) target peptide in a complex with the HLA-A*02:01 MHC molecule and a 3D computational model of the SHC1 off-target peptide RVPPPPQSV (SEQ ID NO: 236) in the groove of the HLA-A*02:01 molecule.

[0156] FIG. 25A illustrates an X-Ray structure of ESK in complex with HLA-A*02:01 / W77.z2<5- 134. FIG. 25A discloses SEQ ID NO: 241

[0157] FIG. 25B illustrates the X-Ray structure of ESK in complex with HLA-A*02:0 \ / WTl 126- 134 of FIG. 25 A with a 3D computational model of off-target peptide KLYGKPIRV (SEQ ID NO: 235) in the groove of the HLA-A*02:01 molecule. FIG. 25B discloses SEQ ID NOS 241 and 235, respectively, in order of appearance.

[0158] FIGs. 26 A through 26C show off-target predictions for the PRAME TCR-transduced T cells. FIG. 26A is an illustration of aspects of the X-scan method being applied to the PRAME425- 433 target peptide, SLLQHLIGL (SEQ ID NO: 75). FIG. 26A discloses SEQ ID NOS 252-260, respectively, in order of appearance. FIG. 26B shows the results of pulsing 171 mutated peptides onto T2 cells that were co-cultured with PRAME TCR. IFNy levels were measured and the magnitude of IFNy secretion from PRAME TCR-transduced T cells was normalized to that induced by the reference peptide (i.e., the PRAME target peptide, which is recognized by Candidate PRAME TCR). Any mutation that ablated IFNy secretion to < 10% relative to that of the reference peptide was considered “non-permitted” because it did not permit TCR recognition. An array of “permitted” and “non-permitted” mutations is depicted and enabled the identification of the candidate PRAME TCR recognition motif. FIG. 26C shows confirmation screen results of the top 20 results of 119 potential cross-reactive peptides that were predicted by applying the recognition motif to a universe of peptides that were bioinformatically selected based on predicted affinity to HLA-A*02:01 (netMHCpan.v4), corresponding gene expression in healthy tissues (GTEx), and evidence of peptide presentation in healthy tissues and / or tumor samples (IEDB). The potential cross-reactive peptides were synthesized and pulsed at lOnM onto T2s that were subsequently co-cultured with candidate PRAME TCR-T cells.

[0159] FIGs. 27A through 27C depict the ranking of identified potential off-target peptides of PRAME425433 by a structural similarity metric according to the methods described herein. FIG. 27 A is an illustration of the pipeline used for ranking potential off-target peptides of the PRAME425-433 target peptide based on similarity in conformation to the PRAME425-433 target peptide. FIG. 27A discloses SEQ ID NOS 150-153 and 75, respectively, in order of appearance. FIG. 27B depicts a plot of the 323 potential off-target peptides as ranked by RMDS calculated between the peptide backbone of residues experimentally determined to be important for TCR interaction (positions 4, 5, 6, and 8). FIG. 27C is an inset of the plot in FIG. 27B for the top 30-ranked potential off-target peptides. FTG. 27C discloses SEQ ID NOS 154-163, 151 , 164-179, 152, and 180-181, respectively, in order of appearance.

[0160] FIGs. 28A through 28D illustrate cross -reactivity using a T2 functional avidity titration assay of the PRAME TCR with four potential off-target peptides (LLLPHLHGL (SEQ ID NO: 150) (TMEM205 gene); ILIEHLYGL (SEQ ID NO: 151) (LRP1 gene); HTLDHLHGV (SEQ ID NO: 152) (TTC17 gene); and SLQPHLLGL (SEQ ID NO: 153) (INAVA gene)) identified by a bioinformatic screen and X-scan analysis. Depicted are representative data showing interferon (IFN)-gamma (IFN-y) (also called IFNy, IFNg, and the like, herein) secretion from PRAME TCR- transduced human T cells following a 24-hour co-incubation with the HLA-A*02:01+ target T2 cell line treated with varying concentrations of the four off-target peptides derived from the proteins INAVA, TMEM205, TTC17, and LRP1 from 10’5to 1014M. The on-target PRAME425- 433 target SLLQHLIGL (SEQ ID NO: 75) (SLL) peptide served as a positive control. Following the co-incubation, culture supernatants were analyzed for IFN-y concentration according to the manufacturer’s instructions (Meso Scale Discovery).

[0161] FIG. 29 shows gene expression levels (in transcripts per million (TPM) of mRNA) from the Genotype-Tissue Expression (GTEx) database for a variety of normal tissue types.

[0162] FIG. 30 shows data quantifying LRP1 off-target peptide presentation in the context of HLA-A*02:01 in various tumor cell lines. The frequency of detection and corresponding ranges of copy numbers of the PRAME target peptide and the four experimentally detected off-target peptides (TMEM205, LRP1, TTC17, and INAVA) as detected by mass spectrometry across the various endogenous tumor cell lines, including cell lines with and without interferon (IFN) treatment, are shown. Treated cell lines, when 75-80% confluent, were stimulated for 48 hours with human recombinant interferon IFN-y (Peprotech #300-02-500UL) before harvesting. The cell lines were evaluated for LRP1 off-target peptide / HLA-A*02:01 content by lysing the harvested cells and performing an affinity pulldown of HLA-A*02:01 molecules prior to peptide copy number analysis via quantitative mass spectrometry. The number total number of HLA-bound 9mers detected by mass spectrometry in each treatment group is also provided for reference. FIG. 30 discloses SEQ ID NOS 75 and 150-153, respectively, in order of appearance.

[0163] FIGs. 31A through 31C characterize LRP1 expression in various cell lines and PRAME TCR reactivity to some of those cell lines. FIGs. 31A-31B show quantification of LRP1 protein expression in HLA-A*02:01+ tumor cell lines U-87MG, T98G, NCI-H2023.PRAME-KO, Hep-G2, and U-251MG. LRP1 protein expression was measured using a capillary-based protein detection system according to the manufacturer’s instructions (Protein Simple) and was normalized to expression of the housekeeper protein GAPDH (Glyceraldehyde 3-Phosphate Dehydrogenase) in each cell line. FIG. 31C shows the level of IFN-y secretion by PRAME TCR when incubated with various endogenous tumor cells lines, including cell lines known to express the PRAME target peptide (OVCAR-3 and NCI-H2023) that served as a positive control. IFN-y secretion was measured from PRAME TCR-transduced T cells following a 24-hour co-incubation with HLA-A*02:01+ target tumor cell lines U-87MG, T98G, NCI-H2023. PRAME- KO, Hep-G2, U-251MG, and NCI-H1915.HLA-A*02:01. The bars correspond to the average magnitude (mean ± SEM) of IFN-y secretion from PRAME TCR-transduced T cells derived from three healthy donors. Following the co-incubation, culture supernatants were analyzed for IFN-y concentration according to the manufacturer’s instructions (Meso Scale Discovery). PRAME TCR-transduced T cells cultured in the absence of target cells (T Cells Alone) served as a negative control, and the PRAME+ / HLA-A*02:01+ cell line OVCAR-3 served as a positive control.

[0164] FIGs. 32A through 32C show LRP1 protein expression levels in various human primary normal cell lines as measured by Wes™ (FIGs. 32A-32B) and the level of IFN-y secretion by PRAME TCR when incubated either alone (negative control) or with select human primary normal cells. The cell lines on the left (orange) were included in an initial off-target agnostic safety screen and the cell lines on the right (green) were included based on qualitative detection of the LRP1 peptide in corresponding tissues by mass spectrometry (MS). SK-MEL-5 and OVCAR-3 (gray) were included as positive controls known to express PRAME target peptide. FIG. 32A shows data quantifying LRP1 protein expression in HLA-A*02:01+ human primary normal cells: human aortic smooth muscle cells (HAoSMC-1), human astrocytes (HA-1), human brain microvascular endothelial cells (HBMEC-3), human brain vascular pericytes (HBVP-1), and human coronary artery smooth muscle cells (HCASMC-I). LRP1 protein expression was measured using a capillary-based protein detection system according to the manufacturer’s instructions (Protein Simple) and was normalized to expression of the housekeeper protein GAPDH in each cell line. The cell lines U-87MG (a glioblastoma cell line) and MCF-7 (a breast adenocarcinoma cell line) were used as positive and negative controls, respectively. FIG. 32B shows data quantifying IFN-y secretion from PRAME TCR-transduced human T cells following a 24-hour co-incubation with HLA-A*02:01+ human primary normal cells: human aortic smooth muscle cells (HAoSMC-1),human astrocytes (HA-1), human brain microvascular endothelial cells (HBMEC-3), human brain vascular pericytes (HBVP-1), and human coronary artery smooth muscle cells (HCASMC-1). The bars correspond to the average magnitude (mean± SEM) of IFN-y secretion from PRAME TCR- transduced T cells derived from three healthy donors. Following the co-incubation, culture supernatants were analyzed for IFN-y concentration according to the manufacturer’s instructions (Meso Scale Discovery). PRAME TCR-transduced T cells cultured in the absence of target cells (T cells alone) served as a negative control. FIG. 32C shows the LRP1 mass spectrum copy number analysis, in which a known amount of heavy synthetic LRP1 was spiked into the sample. The data shown quantify LRP1 off-target peptide presentation in the context of HLA-A*02:01 in primary normal human astrocytes (HA-1). The cells were evaluated for LRP1 off-target peptide / HLA- A*02:01 content by lysing the cells and performing an affinity pulldown of HLA-A*02:01 molecules prior to peptide copy number analysis via quantitative mass spectrometry. LRP1 off- target peptide / HLA-A*02:01 levels were quantified at approximately 212 copies / cell. The number of primary cell donors tested was 1-2 donors.

[0165] FIG. 33 depicts a summary of the in vitro de-risking efforts aimed at understanding the reactivity threshold of PRAME TCR to the LRP1 off-target peptide.

[0166] FIG. 34 illustrates the LRP1 off-target peptide mass spectra copy number analysis, in which a known amount of heavy synthetic LRP1 was spiked into the samples of T2 cells pulsed with 2 nM, 400 pM, or 80 pM of the LRP1 peptide.

[0167] FIGs. 35A through 35B illustrate PRAME TCR reacts to T2s that present ERP1 peptide at > 1000 copies / cell. FIG. 35A shows the level of IFN-y secretion from cells across various experimental conditions, including cells treated with the PRAME TCR or untransduced T cells (untreated (“UTD”)), and with no T2 cells (“T cells alone”), unpulsed T2 cells, or T2 cells pulsed with various concentrations of the ERP1 off-target peptide, including a concentration above the Upper Eimit Of Quantification (UEOQ) and a concentration below the Eower Eimit of Quantification (LLOQ). Following a 24-hour co-incubation, culture supernatants were analyzed for IFN-y concentration according to the manufacturer’s instructions (Meso Scale Discovery). The bars correspond to the average magnitude (mean ± SD) of IFN-y secretion from PRAME TCR- transduced T cells derived from three healthy donors. FIG. 35B shows the results of an EDHGlo™ cytotoxicity assay that measured the release of lactate dehydrogenase (LDH) from damaged or lysed cells under the same experimental conditions. The data show quantification of the releaseLDH from T2 cells presenting varying levels of the LRP1 off-target peptide following a 24-hour co-incubation with PRAME TCR-transduccd T cells. LDH release was used as a readout for T cell-mediated cytotoxicity of the T2 cells. T2 cells were treated with the LRP1 off-target peptide and then co-cultured with either PRAME TCR-transduced or untransduced T cells. T2 cells that were not pulsed with the peptide (unpulsed) and PRAME TCR-transduced T cells incubated in the absence of target cells (T cells alone) both served as negative controls for the co-incubation assay. Following the co-incubation, culture supernatants were analyzed for LDH concentration according to the manufacturer’s instructions (LDH-Glo, Promega). The bars correspond to the average magnitude (mean ± SD) of LDH release induced by PRAME TCR-transduced T cells derived from three healthy donors. Dotted lines indicate the average magnitude of background IFNy secreted by nontransduced T cells.

[0168] FIGs. 36A through 36B illustrates that several essential tissues present high levels (> 1 ,000 copies / cell) of LRP1 peptide, particularly cardiovascular tissues (e.g., coronary artery with plaques and aorta). FIG. 36A summarizes the frequency of samples positive for the off-target peptide within the HLA-A02 positive samples and the approximate copy number ranges for those LRP1 off-target peptide positive samples. 13 / 30 cardiac tissue samples had high copy number of LRP1 (>1,000 copies / cell) including 8 coronary artery samples with plaques and 4 aorta samples from patients with a history of MI. Red letters indicate the residue to which a heavy label was conjugated for the synthetic spike-in. FIG. 36A discloses SEQ ID NO: 151. FIG. 36B shows the estimated copy number of the LRP1 off-target peptide as detected by mass spectrometry in various normal tissue samples, including one from a patient with a myocardial infarction (MI) comorbidity. CA = coronary artery.

[0169] FIG. 37 shows a summary of the patient data and copy number analysis for specific normal / diseased tissue samples presenting high ERP1 off-target peptide copy numbers. Both coronary artery tissue samples where LRP1 off-target peptide IEIEHEYGE (SEQ ID NO: 151) was detected were diseased (with plaques). 8 / 11 coronary samples with plaques were LRP1+. LRP1 off-target peptide ILIEHEYGL (SEQ ID NO: 151) was not detected in the non-diseased coronary artery HLA-A02:01 samples (6 samples). One aorta sample with a comorbidity of myocardial infarction (MI) was found to be very high at (> 6000 copies / cell).

[0170] FIGs. 38A through 38B show specificity analysis with IFNy and cytotoxicity readouts from co-culture of candidate PRAME TCR-T cells tested with HLA-A*02:01 -positive / PRAME-negative tumor cell lines. FIG. 38A shows co-culture supernatants harvested at t = 24 hours and subsequently analyzed for IFNy content via Meso Scale Discovery assay (MSD). FIG. 38B shows a subset of the tumor cell lines that were transduced to express a fluorescent reporter. PRAME TCR-T cells were co-cultured with reporter-transduced tumor cells for 5 days, and total fluorescent object counts were recorded using an IncuCyte cell imager. A decrease influorescent object counts indicates tumor cell death. Shaded areas indicate SEM.

[0171] FIGs. 39A through 39C show peptide copy number analysis and functional assays using off-target overexpression models. FIG. 39A shows co-culture supernatants harvested at t = 24 hours and subsequently analyzed for IFNy content via MSD. FIG. 39B shows tumor cell lines transduced to express a fluorescent reporter. Candidate PRAME TCR-T cells were co-cultured with reporter-transduced tumor cells for 5 days, and total fluorescent area was recorded using an IncuCyte cell imager. FIG. 39C shows mass spectrometry analysis that confirmed the presence of HLA-A*02:01 / LRPl(ILIEHLYGL) (SEQ ID NO: 151) peptide in its respective Midigene- transduced cell lines. Relative copy numbers were estimated using a synthetic heavy labelled spike-in approach.

[0172] FIG. 40 shows an overview' of the approach described herein, wherein mass spectrometry (MS)-enabled quantitative immunopeptidomics was combined with cell-based functional assays to identify a development-limiting risk of OT-directed cardiotoxicity for the candidate PRAME TCR.DEFINITIONS

[0173] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the pertinent art.

[0174] Singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Thus, for example, a reference to “a method” includes one or more methods, and / or steps of the type described herein and / or which will become apparent to those persons skilled in the art upon reading this disclosure.

[0175] The term “about” or “approximately” includes being within a meaningful range of a value. The allowable variation encompassed by the term “about” or “approximately” depends on the particular' system under study, and can be readily appreciated by one skilled in the pertinent art.

[0176] The terms “major histocompatibility complex,” and “MHC” encompass the terms “human leukocyte antigen” or “HLA” (the latter two of which arc generally reserved for human MHC molecules), naturally occurring MHC molecules (e.g., MHC class I molecule comprising MHC class I a (heavy) chain and p2 microglobulin; MHC class II molecule comprising MHC class II a chain and MHC class II P chain), individual chains of MHC molecules (e.g., MHC class I a (heavy) chain, MHC class II a chain, and MHC class II P chain), individual subunits of such chains of MHC molecules (e.g., al, a2, and / or a3 subunits of MHC class I a chain, al and / or a2 subunits of MHC class II a chain, piand / or p2 subunits of MHC class II P chain) as well as portions (e.g., the peptide-binding portions, e.g., the peptide-binding grooves), mutants and various derivatives thereof (including fusions proteins), wherein such portion, mutants and derivatives retain the ability to display an antigenic peptide for recognition by a T-cell receptor (TCR), e.g., an antigenspecific TCR. An MHC class I molecule comprises a peptide binding groove formed by the al and a2 domains of the heavy a chain that can stow a peptide of around 8-14 amino acids. In certain embodiments, an MHC class I molecule can stow a peptide of about 8 amino acids in length. In certain embodiments, an MHC class I molecule can stow a peptide of about 9 amino acids in length. In certain embodiments, an MHC class I molecule can stow a peptide of about 10 amino acids in length. In certain embodiments, an MHC class I molecule can stow a peptide of about 11 amino acids in length. In certain embodiments, an MHC class I molecule can stow a peptide of about 12 amino acids in length. In certain embodiments, an MHC class I molecule can stow a peptide of about 13 amino acids in length. In certain embodiments, an MHC class I molecule can stow a peptide of about 14 amino acids in length. Despite the fact that both classes of MHC bind a core of about 9 amino acids (e.g., 5 to 17 amino acids) within peptides, the open-ended nature of MHC class II peptide binding groove (the al domain of a class II MHC a polypeptide in association with the pi domain of a class II MHC P polypeptide) allows for a wider range of peptide lengths. Peptides binding MHC class II usually vary between 12 and 20 amino acids in length, though shorter or longer lengths (e.g., 23 amino acids in length) are not uncommon. As a result, peptides may shift within the MHC class II peptide binding groove, changing which 9-mer sits directly within the groove at any given time. In certain embodiments, an MHC class II molecule can stow a peptide of about 12 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 13 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 14 amino acids in length. In certainembodiments, an MHC class IT molecule can stow a peptide of about 15 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 16 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 17 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 18 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 19 amino acids in length. In certain embodiments, an MHC class II molecule can stow a peptide of about 20 amino acids in length. In some embodiments, the MHC -peptide complex described herein may be an MHC-peptide complex from a non-human animal. In other embodiments, the MHC-peptide complex described herein may include an HLA-peptide complex, i.e., an MHC-peptide complex from a human.

[0177] The term “non-human animal” and the like refers to any vertebrate organism that is not a human. In some embodiments, a non-human animal is a cyclostome, a bony fish, a cartilaginous fish (e.g., a shark or a ray), an amphibian, a reptile, a mammal, and a bird. In some embodiments, a non-human animal is a mammal. In some embodiments, a non-human mammal is a primate, a goat, a sheep, a pig, a dog, a cow, or a rodent. In some embodiments, a non-human animal is a rodent such as a rat or a mouse.

[0178] The term “antigen” refers to any agent (e.g., protein, peptide, polysaccharide, glycoprotein, glycolipid, nucleotide, portions thereof, or combinations thereof) that, when introduced into an immunocompetent host can be recognized by the immune system of the host and elicit an immune response by the host. A T-cell receptor (TCR) can recognize a peptide presented in the context of a major histocompatibility complex (MHC) as part of an immunological synapse. The peptide-MHC (pMHC) complex is recognized by the TCR, with the peptide (antigenic determinant) and the TCR idiotype providing the specificity of the interaction. Accordingly, the term “antigen” encompasses peptides presented in the context of MHCs, e.g., peptide-MHC complexes. The peptide displayed on MHC may also be referred to as an “epitope” or an “antigenic determinant”. The terms “peptide,” “antigenic determinant,” “epitopes,” etc., encompass not only those presented naturally by antigen-presenting cells (APCs), but may be any desired peptide so long as it is recognized by an immune cell of an animal, e.g., when presented appropriately to the cells of an immune system. For example, a peptide having an artificially prepared amino acid sequence may also be used as the epitope.

[0179] The term “antigen-recognition molecule” refers to any molecule that is capable of recognizing an antigen as defined above. Antigen-recognition molecules can include, but arc not limited to, T cell receptors (TCR), antibodies, or chimeric antigen receptors (CARs).

[0180] The term “antigen presenting cell” or “APC” refers to any cell that presents on the surface of the cell an antigen in association with a major histocompatibility complex molecule, e.g., either MHC class I or MHC class II molecule, or both.

[0181] ‘ ‘MHC-peptide complex,” “peptide-MHC complex,” “pMHC complex,” “peptide-in- groove,” and the like includes: (i) an MHC molecule, e.g., a human and / or non-human animal MHC molecule, or portion thereof (e.g., the peptide-binding groove thereof, or e.g., the extracellular portion thereof); and (ii) an peptide (e.g., an antigenic peptide), where the MHC molecule and the peptide are complexed in such a manner that the pMHC complex can specifically bind a T-cell receptor. pMHC complexes encompass cell surface expressed pMHC complexes and soluble pMHC complexes.

[0182] “ HLA-peptide complex,” “peptide-HLA complex,” “pHLA complex,” and the like refers to an MHC-peptide complex wherein the MHC molecule is a Human Leukocyte Antigen (HLA) molecule.

[0183] The terms “protein” and “polypeptide”, used interchangeably herein, encompass all kinds of naturally occurring and synthetic proteins, including protein fragments of all lengths, fusion proteins and modified proteins (e.g., proteins resulting from phosphorylation, acetylation, myristoylation, palmitoylation, glycosylation, oxidation, formylation, amidation, polyglutamylation, ADP-ribosylation, PEGylation, biotinylation, etc.). Small polypeptides of less than 100 amino acids, preferably less than 50 amino acids, may be referred to as “peptides”.

[0184] The terms “polynucleotide” and “nucleic acid”, used interchangeably herein, include polymeric forms of nucleotides of any length, including ribonucleotides (RNA), deoxyribonucleotides (DNA), or analogs or modified versions thereof. They include single-, double-, and multi- stranded DNA or RNA, genomic DNA, complementary DNA (cDNA), DNA- RNA hybrids, and polymers comprising purine bases, pyrimidine bases, or other natural, chemically modified, biochemically modified, non-natural, or derivatized nucleotide bases.

[0185] In general, a "promoter" or "promoter sequence" is a DNA regulatory region capable of binding an RNA polymerase in a cell (e.g., directly or through other promoter-bound proteins or substances) and initiating transcription of a coding sequence. A promoter may be operably linkedto other expression control sequences, including enhancer and repressor sequences and / or with a polynucleotide described herein.

[0186] The term “operably linked” or the like refers to a juxtaposition wherein the components described are in a relationship permitting them to function in their intended manner. For example, a control sequence “operably linked” to a coding sequence is ligated in such a way that expression of the coding sequence is achieved under conditions compatible with the control sequences. “Operably linked” sequences include both expression control sequences that are contiguous with a gene of interest and expression control sequences that act in trans or at a distance to control a gene of interest (or sequence of interest). The term “expression control sequence” includes polynucleotide sequences, which are necessary to affect the expression and processing of coding sequences to which they are ligated. “Expression control sequences” include: appropriate transcription initiation, termination, promoter and enhancer sequences; efficient RNA processing signals such as splicing and polyadenylation signals; sequences that stabilize cytoplasmic mRNA; sequences that enhance translation efficiency (i.e., Kozak consensus sequence); sequences that enhance polypeptide stability; and when desired, sequences that enhance polypeptide secretion. The nature of such control sequences differs depending upon the host organism. For example, in prokaryotes, such control sequences generally include promoters, ribosomal binding sites and transcription termination sequences, while in eukaryotes typically such control sequences include promoters and transcription termination sequences. The term “control sequences” is intended to include components whose presence is essential for expression and processing, and can also include additional components whose presence is advantageous, for example, leader sequences and fusion partner sequences.

[0187] The term “isolated” refers to a homogenous population of molecules (such as polynucleotides or polypeptides) which have been substantially separated and / or purified away from other components of the system the molecules are produced in, such as a recombinant cell, as well as a protein that has been subjected to at least one purification or isolation step. In certain aspects, “isolated” refers to a molecule that is substantially free of other cellular material and / or chemicals and encompasses molecules that are isolated to a higher purity, such as to 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100% purity. The term “isolated” as used herein may also refer to a cell, or homogenous population of cells, that has been removed from its natural environment and substantially separatedfrom other cellular components with which it is naturally associated. This includes cells that have been cultured in vitro or otherwise manipulated outside of their native biological context. The term encompasses cells that are part of a purified population, free from significant contamination by other cell types, and may include, e.g., genetically modified cells, stem cells, or cells derived from tissues or organs. In some embodiments, an isolated cell of the present disclosure is an immune cell, e.g., an antigen-presenting cell (APC)..

[0188] The term “derivative” as used herein refers to a peptide, polypeptide, or polynucleotide, or a variant or analog thereof, comprising one or more mutations and / or chemical modifications as compared to a reference peptide, polypeptide or polynucleotide. Mutations and / or chemical modifications are further detailed below and can include, for example, insertions, substitutions, deletions, transversions, and / or inversions at one or more locations in the amino acid or nucleotide sequence.

[0189] The terms “antibody,” “immunoglobulin,” “binding protein” and the like refer to monoclonal antibodies, multispecific antibodies, human antibodies, humanized antibodies, chimeric antibodies, single-chain Fvs (scFv), single chain antibodies, Fab fragments, F(ab') fragments, disulfide-linked Fvs (sdFv), intrabodies, minibodies, diabodies and anti-idiotypic (anti- id) antibodies (including, e.g., anti-Id antibodies to antigen- specific TCR), and epitope-binding fragments of any of the above. The terms “antibody” and “antibodies” also refer to covalent diabodies such as those disclosed in U.S. Pat. Appl. Pub. 20070004909, incorporated herein by reference in its entirety, and Ig-DARTS such as those disclosed in U.S. Pat. Appl. Pub. 20090060910, incorporated herein by reference in its entirety. In some instances, an immunoglobulin or antibody may be a membrane-bound immunoglobulin or antibody, such as a B Cell Receptor (BCR).

[0190] A “pMHC-binding protein” refers to an antigen-binding protein (e.g., an immunoglobulin, antibody, TCR, CAR, or the like) that specifically binds a pMHC complex.

[0191] An “individual” or “subject” or “animal” refers to humans, veterinary animals (e.g., cats, dogs, cows, horses, sheep, pigs, etc.) and experimental animal models of diseases (e.g., mice, rats). In one embodiment, the subject is a human.

[0192] The term “library” refers to an isolated collection of at least two elements that differ from one another in at least one aspect. For example, a “peptide library” is a collection of at least two peptides that may differ from one another by at least one amino acid. As another example, a“pMHC complex library” is a collection of pMHC complexes that may differ from one another by at least one amino acid in the peptide or at least one MHC polypeptide. The elements of the library are isolated from like type of elements that are not part of the library (e.g., peptides of a peptide library are isolated from peptides that are not part of the library). The library may exist in vitro or ex vivo. One or more elements (e.g., each element) of the library may be isolated from one or more other elements (e.g., each other element) of the library. A library may be “sorted” such that each of the one or more isolated elements exists in an identifiable and accessible physical space, such as a cell or a container, so that each set of the one or more isolated elements may be selectively accessed or pulled from the library for use according to the disclosure elsewhere herein. Each container may be separable (e.g., a vial) or part of an integral solid support (e.g., an individual well of a multi- well plate). One or more elements of a library (including partial portions or the entirety of the library) may be used according to the disclosure herein. Various elements of a library may be used contemporaneously or consecutively, such as for screening antigen-recognition molecules for off-target cross-reactivity.

[0193] The term “administration” and the like refers to and includes the administration of a composition (e.g., antigen-recognition molecule) to a subject or system (e.g., to a cell, organ, tissue, organism, or relevant component or set of components thereof). The skilled artisan will appreciate that route of administration may vary depending, for example, on the subject or system to which the composition is being administered, the nature of the composition, the purpose of the administration, etc. For example, in certain embodiments, administration to an animal subject (e.g., to a human or a rodent) may be bronchial (including by bronchial instillation), buccal, enteral, interdermal, intra-arterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, mucosal, nasal, oral, rectal, subcutaneous, sublingual, topical, tracheal (including by intratracheal instillation), transdermal, vaginal and / or vitreal. In some embodiments, administration may involve intermittent dosing. In some embodiments, administration may involve continuous dosing (e.g., perfusion) for at least a selected period of time.

[0194] The term “essential, normal tissues” refers to tissues of a patient where side-effects of a given antigen-recognition molecule administered for treating a disease may be deemed unacceptable. The list of tissues considered essential, normal would vary depending on the disease being treated and on the risks associated with the disease itself (e.g., the list would be smaller forlife-threatening diseases than for non-life-threatening diseases). For example but not by way of limitation, when treating life-threatening cancers, tissue types that may be considered non-essential may include breast, ovary and testes. The list of tissues considered essential and normal would also vary depending on the likelihood for a given antigen-recognition molecule to reach such tissues. For example, brain may not be included in the list of essential, normal tissues in cases of antigen-recognition molecules which do not permeate blood-brain-barrier of patients with the disease being treated.

[0195] The terms “component,” “engine,” “module,” “system,” “server,” “processor,” “memory,” and the like are intended to include one or more computer-related units, such as but not limited to hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, an object, an executable, a thread of execution, a program, and / or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and / or thread of execution and a component may be localized on one computer and / or distributed between two or more computers. In addition, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and / or remote processes such as in accordance with a signal having one or more data packets, such as data from one component interacting with another component in a local system, distributed system, and / or across a network such as the Internet with other systems by way of the signal.

[0196] The term “3D computational model” refers to a computer-readable representation of a 3D (three-dimensional) structure that includes information about portions of the 3D structure in relation to each other. In examples presented herein in which the 3D structure includes one or more molecules, the 3D computational model of that 3D structure includes positions of atoms, or collections of atoms, in relation to each other. In some examples, the 3D computational model represents a conformation of molecule(s) such that arrangement in space of constituent atoms of the molecule(s) are represented in the 3D computational model. In examples presented herein in which the 3D structure includes a peptide, the 3D computational model includes positions of at least a portion of the amino acids of the peptide in relation to each other. For instance, a 3D computational model of a peptide may represent a conformation of the peptide, or a folded 3Dstructure of the peptide. For instance, a 3D computational model of a peptide, MHC molecule, and / or other molecule may be a file in Protein Data Bank (PDB) format, Macromolecular Crystallographic Information File (mmCIF or PDBx / mmCIF) format, Polygon File Format or Stanford Triangle Format (PLY), or other suitable file or data structure format as understood by a person skilled in the pertinent art. A 3D computational model of a peptide, a peptide in a groove of an MHC molecule, or a peptide in complex with an MHC molecule can be computationally generated, computationally refined, and / or based on experimentally determined structures.

[0197] The terms “MHC-target model” and “MHC-off-target model” refer to 3D computational models of peptides positioned in the grooves of, or in complex with, MHC molecules, respectively, a target peptide positioned in a groove of, or in complex with, an MHC molecule and an off-target peptide positioned in a groove of, or in complex with, an MHC molecule. For purposes of 3D computational models, a peptide may be considered to be positioned in the groove of an MHC molecule or in complex with an MHC molecule when positioned or docked in a conformation and orientation relative to the binding groove of the MHC molecule that optimizes, based on at least one measure, the probability of peptide binding or loading on to the MHC molecule, regardless of whether stable peptide binding / loading has been experimentally validated or does in fact occur. A given target peptide may be represented by one or more MHC- target models, and likewise a given off-target peptide may be represented by one or more MHC- target models. MHC-target models and MHC-off-target models can be generated computationally and / or based on experimentally determined structures. For instance, MHC-target models and MHC-off-target models can be experimentally determined using methods such as X-ray crystallography, cryogenic electron microscopy (cryo-EM), Nuclear Magnetic Resonance (NMR), other suitable experimental method as understood by a person skilled in the pertinent art, or combinations thereof. MHC-target models and MHC-off-target models can be generated computationally by de novolab initio approaches or by using one or more templates. For instance, such models can be generated computationally by fragment assembly (e.g., using Rosetta or other such tools), by template-based modeling / homology-based modeling / threading (e.g., using Rosetta or other such tools), by sequence-based machine learning (e.g., using AlphaFold or other such tools), or by other suitable computational tool as understood by a person skilled in the pertinent art, or combinations thereof. MHC-target models and MHC-off-target models can be generated using both experimental data and computational prediction tools. For instance, an initial 3Dcomputational model or a portion of a 3D computational model may be determined by experimentation and the cxpcrimcntal-bascd 3D computational model (or model portion) may be refined or supplemented using computational tools.

[0198] The terms “coarse-grained” and “refined”, when referring to a 3D computational model such as an MHC-target model and an MHC-off-target model, indicate a level of computational refinement performed on the 3D computational model to improve the accuracy and / or increase the resolution of the 3D computational model as compared to the physical structure that the 3D computational model represents. Generally, a “refined” 3D computational model is more accurate, higher resolution, and / or has been refined by more computational processing than a “coarsegrained” computational model. For instance, a coarse-grained model may be refined by minimizing some energy function or finding a minimum in an energy landscape (e.g., using Rosetta FlexPepDock, GROMOS force field, CHARMM force field, or other such tools).

[0199] The term “connected” means that one function, feature, structure, or characteristic is directly joined to or in communication with another function, feature, structure, or characteristic.

[0200] The term “coupled” means that one function, feature, structure, or characteristic is directly or indirectly joined to or in communication with another function, feature, structure, or characteristic.

[0201] The terms “comprising” or “containing” or “including” are meant that at least the named element, or method step is present in article or method, but does not exclude the presence of other elements or method steps, even if the other such elements or method steps have the same function as what is named.

[0202] As used herein, unless otherwise specified, the use of the ordinal adjectives “first,” “second,” “third,” etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

[0203] In this description, numerous specific details are set forth. It is to be understood, however, that implementations of the disclosed technology may be practiced without these specific details. In other instances, well-known methods, structures, and techniques have not been shown in detail in order not to obscure an understanding of this description. References to “one embodiment,” “an embodiment,” “some embodiments,” “example embodiment,” “various embodiments,” “one implementation,” “an implementation,” “example implementation,” “various implementations,”“some implementations,” etc., indicate that the implementation(s) of the disclosed technology so described may include a particular feature, structure, or characteristic, but not every implementation necessarily includes the particular feature, structure, or characteristic. Further, repeated use of the phrase “in one implementation” does not necessarily refer to the same implementation, although it may.

[0204] In accordance with the disclosure herein, there may be employed conventional molecular biology, microbiology, and recombinant DNA techniques within the skill of the art. Such techniques are explained fully in the literature. See, e.g., Sambrook, Fritsch & Maniatis, Molecular Cloning: A Laboratory Manual, Second Edition. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press, 1989 (herein “Sambrook et al., 1989”); DNA Cloning: A Practical Approach, Volumes I and II (D.N. Glover ed. 1985); Oligonucleotide Synthesis (M.J. Gait ed. 1984); Nucleic Acid Hybridization [B.D. Hames & S.I. Higgins eds. (1985)]; Transcription And Translation [B.D. Hames & S.J. Higgins, eds. (1984)]; Animal Cell Culture [R.I. Freshney, ed. (1986)]; Immobilized Cells And Enzymes [IRL Press, (1986)]; B. Perbal, A Practical Guide To Molecular Cloning (1984); Ausubel, F.M. et al. (eds.). Current Protocols in Molecular Biology. John Wiley & Sons, Inc., 1994. These techniques include site directed mutagenesis as described in Kunkel, Proc. Natl. Acad. Sci. USA 82: 488- 492 (1985), U. S. Patent No. 5,071, 743, Fukuoka et al., Biochem. Biophys. Res. Commun. 263: 357-360 (1999); Kim and Maas, BioTech. 28: 196-198 (2000); Parikh and Guengerich, BioTech. 24: 428-431 (1998); Ray and Nickoloff, BioTech. 13: 342-346 (1992); Wang et al., BioTech. 19: 556-559 (1995); Wang and Malcolm, BioTech. 26: 680-682 (1999); Xu and Gong, BioTech. 26: 639-641 (1999), U.S. Patents Nos. 5,789, 166 and 5,932, 419, Hogrefe, Strategies 14. 3: 74-75 (2001), U. S. Patents Nos. 5,702,931, 5,780,270, and 6,242,222, Angag and Schutz, Biotech. 30: 486-488 (2001), Wang and Wilkinson, Biotech. 29: 976-978 (2000), Kang et al., Biotech. 20: 44-46 (1996), Ogel and McPherson, Protein Engineer. 5: 467-468 (1992), Kirsch and Joly, Nucl. Acids. Res. 26: 1848-1850 (1998), Rhem and Hancock, J. Bacteriol. 178: 3346-3349 (1996), Boles and Miogsa, Curr. Genet. 28: 197-198 (1995), Barrenttino et al., Nuc. Acids. Res. 22: 541-542 (1993), Tessier and Thomas, Meths. Molec. Biol. 57: 229-237, and Pons et al., Meth. Molec. Biol. 67: 209-218.DETAILED DESCRIPTION

[0205] Some embodiments presented herein relate to identification of off-target peptide(s) that are similar to an intended target peptide of an MHC-target peptide complex, such that an antigenrecognition molecule that is engineered for the intended target MHC-target peptide complex is likely to also recognize the off-target peptide(s) (e.g., peptide-MHC (pMHC) complexes comprising an off-target peptide). As will be understood herein, an antigen-recognition molecule which is said to “target” a specific peptide (i.e., a “target peptide”) is intended or purposed for (i.e., designed, engineered, and / or screened / selected for) preferentially recognizing and binding a peptide-MHC (pMHC) complex comprising the target peptide. Embodiments presented herein provide methods for generating 3D models of off-targets and targets, comparing off-target models to target models, ranking off-targets for a given target based on structural similarity so that higher ranked off-targets may be used for further in vivo studies, and ranking potential targets based on similarity of potential off-targets so that higher ranked targets and their associated off-targets may be used for further in vivo studies. In some embodiments, ranking and identification of the off- targets and / or targets can be agnostic of the antigen-recognition molecule so that the identified off- target peptides, predicted in vivo toxicity, and / or ranking of potential target peptides can be used to guide development of an antigen-recognition molecule for targeting a target peptide having a low number of identified off-target peptides, a low predicted probability of in vivo toxicity, and / or a preferred ranking. Some embodiments disclosed herein include computational systems, engines, modules, devices, and / or networks configured to carry out a majority of steps associated with the above embodiments. The output of such computational systems, etc. can be used to inform antigenrecognition molecule development, screening of patients for clinical trials, individual patient treatment, and other such applications as understood by a person skilled in the pertinent art according to the teachings herein. One aim of some embodiments presented herein is to avoid side effects that would otherwise be identified during clinical trials, thereby reducing patient death, reducing other adverse effects on patients, and reducing expenditure of time and resources in research and development.

[0206] MHC molecules are generally classified into two categories: class I and class II MHC molecules. An MHC class I molecule is an integral membrane protein comprising a glycoprotein heavy chain, also referred to herein as the a chain, which has three extracellular domains (i.e., al, a2 and a3) and two intracellular domains (i.e., a transmembrane domain (TM) and a cytoplasmicdomain (CYT)). The heavy chain is noncovalently associated with a soluble subunit called p2 microglobulin (02m or 02M). An MHC class II molecule or MHC class II protein is a heterodimeric integral membrane protein comprising one a chain and one P chain in noncovalent association. The a chain has two extracellular domains (al and a2), and two intracellular domains (a TM domain and a CYT domain). The P chain contains two extracellular domains (pi and p2), and two intracellular domains (a TM domain and CYT domain).

[0207] The domain organization of class I and class II MHC molecules forms the antigenic determinant binding site, e.g., the peptide-binding portion or peptide binding groove, of the MHC molecule. A peptide binding groove refers to a portion of an MHC protein that forms a cavity in which a peptide, e.g., antigenic determinant, can bind. The conformation of a peptide binding groove is capable of being altered upon binding of a peptide to enable proper alignment of amino acid residues important for TCR binding to the peptide-MHC (pMHC) complex.

[0208] In some embodiments, MHC molecules include fragments of MHC chains that are sufficient to form a peptide binding groove. For example, a peptide binding groove of a class I protein can comprise portions of the al and a2 domains of the heavy chain capable of forming two P-pleated sheets and two a helices. Inclusion of a portion of the p2 microglobulin chain stabilizes the MHC class I molecule. While for most versions of MHC Class II molecules, interaction of the a and P chains can occur in the absence of a peptide, the two-chain molecule of MHC Class II is unstable until the binding groove is filled with a peptide. A peptide binding groove of a class II protein can comprise portions of the al and pi domains capable of forming two P-pleated sheets and two a helices. A first portion of the al domain forms a first P-pleated sheet and a second portion of the al domain forms a first a helix. A first portion of the pi domain forms a second P- pleated sheet and a second portion of the pi domain forms a second a helix. The X-ray crystallographic structure of class II protein with a peptide engaged in the binding groove of the protein shows that one or both ends of the engaged peptide can project beyond the MHC protein (Brown et al., pp. 33-39, 1993, Nature, Vol. 364; incorporated herein in its entirety by reference). Thus, the ends of the al and pi a helices of class II form an open cavity such that the ends of the peptide bound to the binding groove are not buried in the cavity. Moreover, the X-ray crystallographic structure of class II proteins shows that the N-terminal end of the MHC P chain apparently projects from the side of the MHC protein in an unstructured manner since the first 4amino acid residues of the 0 chain could not be assigned by X-ray crystallography. Many human and other mammalian MHCs arc well known in the art.

[0209] In some embodiments, the MHC molecule may be a human HLA molecule selected from the group consisting of HLA- A, HLA-B, HLA-C, HLA-E, HLA-F, and HLA-G. A list of commonly used HLA alleles is described in Shankarkumar et al. ((2004) The Human Leukocyte Antigen (HLA) System, Int. J. Hum. Genet. 4(2):91-103), incorporated herein in its entirety by reference. Shankarkumar et al. also present a brief explanation of HLA nomenclature used in the art. Additional information regarding HLA nomenclature and various HLA alleles can be found in Holdsworth et al. (2009) The HLA dictionary 2008: a summary of HLA-A, -B, -C, -DRB1 / 3 / 4 / 5, and DQB1 alleles and their association with serologically defined HLA-A, -B, -C, -DR, and -DQ antigens, Tissue Antigens 73:95-170, and a recent update by Marsh et al. (2010) Nomenclature for factors of the HLA system, 2010, Tissue Antigens 75:291-455, each of which publications is incorporated herein in its entirety by reference. In some embodiments, the MHC I or MHC II polypeptides may be derived from any functional human HLA-A, B, C, DR, or DQ molecules. In one embodiment, the HLA molecule is encoded by HLA-A2, such as an HLA-A*02:01 allele. In another embodiment, the HLA molecule is encoded by HLA-A1, such as an HLA-A*01:01 allele.

[0210] Targeting peptide-MHC (pMHC) complexes specifically expressed on cells such as cancer cells via, e.g., antibody-based or cell-based therapeutics approaches, can be an effective way of destroying such cells. However, the potential off-targets associated with these pMHC complexes can often lead to off-target toxicity. The present disclosure provides, among other things, a method useful in the prediction of such off-targets.

[0211] Methods useful in prediction of such off-targets are presented, for example, in WO2023122621 , which is incorporated by reference herein in its entirety. In certain embodiments, WO2023122621 presents a method, referred to herein as the “PIGSPRED method” in which, for a target peptide, amino acid positions are distinguished as either being bound in an MHC-target peptide complex or available to bind to an antigen recognition molecule. In certain embodiments, the PIGSPRED method identifies potential off-target peptides based on binding affinity to the MHC molecule and the similarity of the amino acid sequence of a potential off-target peptide to the available positions of the target peptide. WO2023122621 at paragraphs

[0272] -

[0274] and Table IB presents one example in which the PIGSPRED method is applied to a MAGEA4 target peptide GVYDGREHTV (SEQ ID NO: 242). In this example, positions 4 and 6-9 of said targetpeptide are identified as available positions, and potential off-target GLADGRTHTV (SEQ ID NO: 243) is determined a higher degree of similarity to said target peptide than other potential off- target peptides GVPDCRIFTV (SEQ ID NO: 244), SVYDAREFSV (SEQ ID NO: 245), GLSDGQWHTV (SEQ ID NO: 246), GVFDNCSHTV (SEQ ID NO: 247), and KVSDGHFHTV (SEQ ID NO: 248).

[0212] In some embodiments, the PIGSPRED method calculates a DoS score, optionally wherein only positions of the target peptide identified as not involved in interacting with the MHC molecule are considered in calculating the DoS score, and the PIGSPRED method calculates a probability of in vivo toxicity of each potential target peptide based at least in part on the number of potential off-target peptide(s), which may be determined at least in part by DoS. Once cancer-specific pHLAs are identified, PIGSPRED can be used to calculate the number of potential off-targets having sequence similarity associated with each cancer-specific pHLA. In certain embodiments of the PIGSPRED method, the number of potential off-targets is representative of the likelihood of off-target toxicity associated with a target and is used to rank the list of pHLA targets and to prioritize the targets for therapeutic development. In certain embodiments of the PIGSPRED method, the off-targets predicted by PIGSPRED can be used in experimental screening of therapeutic molecules to confirm that the therapeutic molecules do not bind the off-targets. The most specific therapeutic molecules can thus be selected for further development.

[0213] Another method, referred to herein as “X-scan” determines antigen-recognition molecule (e.g., TCR) binding motifs. In some embodiments, the X-scan method can be used to determine positions of a target peptide which are important for binding to a respective antigen recognition molecule by: (i) generating a plurality of mutant peptides which have exactly one amino acid substitution at exactly one position of the target peptide; and (ii) determining which mutated peptides lead to increased or decreased signaling (e.g., TCR signaling) when brought into contact with the antigen-recognition molecule. Details of the X-scan method are described in greater detail in Border, Ellen C., et al. "Affinity -enhanced T-cell receptors for adoptive T-cell therapy targeting MAGE-A10: strategy for selection of an optimal candidate." Oncoimmunology 8.2 (2019), incorporated by reference herein in its entirety.

[0214] In certain embodiments, the present disclosure provides computational methods based on 3D models of target and off-target peptides for ranking and / or selecting off-target peptides for use in in vitro methods for assessing off-target effects of an antigen-recognition molecule. In certainaspects, both the PIGSPRED method and the present disclosure describe methods which can be used to estimate off-target toxicity associated with a target peptide and identify potential off-target peptides for use in experimental screening of therapeutic molecules. In certain embodiments, systems and methods of the present disclosure can be utilized as an alternative to the PIGSPRED method; in certain embodiments, systems and methods of the present disclosure can incorporate or utilize the PIGSPRED method to pre-screen targets and / or off targets; in certain embodiments, systems and methods of the present disclosure can incorporate or utilize additional and / or alternative pre-screening methods to the PIGSPRED method; and in certain embodiments, a combination of similarity metrics determined by the PIGSPRED method (e.g., a probability of in vivo toxicity, risk metric, DoS, ranking) and / or alternative method can be used in combination with structural similarity metrics disclosed herein to prioritize target and / or off-target peptides for antigen-recognition molecule development.

[0215] Aspects of the embodiments of the structure-based off-target peptide analysis are described in relation to the Figures.

[0216] FIG. 1 is a flow diagram illustrating an exemplary method 100 for ranking a plurality of potential off-target peptides of a target peptide.

[0217] At block 110, an MHC-target model is obtained. The MHC-target model can be obtained from a database, generated, and / or refined at block 110. In some embodiments, block 110 includes performing experimental methods and / or computationally generating the MHC-target model. In some embodiments, block 110 includes obtaining the MHC-target model, or an initial model from a database. In such embodiments, the database can include experimentally determined and / or computationally generated 3D computational models of peptides, MHC molecules, and / or MHC- peptide complexes. In some embodiments, the MHC-target model can be based at least in part on an experimentally developed 3D computational model. Obtaining the MHC-target model at block 110 can include extracting the experimental model from a database or performing experimental methods to obtain the MHC-target model.

[0218] In some embodiments, the MHC-target model is derived from a predicted structure. In one embodiment, a template based modeling process can determine the predicted structure by performing the steps of (a) searching a database of known protein structures comprising a 3D computational model of a template peptide bound to the MHC molecule to identify a plurality of template structures based, at least in part, on amino acid sequence similarity of the template peptidewith the peptide sequence of the target peptide; (b) aligning the peptide sequence to each of the 3D computational models of the template structures based on a comparison of the sequences; (c) calculating an energy score for each of the aligned peptide sequences; (d) selecting a template structure based on the calculated energy scores; and (e) assigning a predicted structure based on the selected template structure. In addition to, or as an alternative to the template based modeling process, the predicted structure can be determined using a sequence-based machine learning algorithm, which may optionally use a neural network-based model. In some embodiments, the predicted structure can be pre-packed (“prepacked predicted structure”), wherein prepacking the predicted structure is optimized based at least in part on the selection of rotamer combinations for the peptide and MHC molecule to eliminate steric clashes. Optionally, the predicted structure can be based at least in part on a templated-based modeling or experimental measurements followed by prepacking.

[0219] In some embodiments, the MHC-target model can be generated by refining the predicted structure. In such embodiments, the predicted structure can include a coarse-grained MHC-target peptide model. The coarse-grained MHC-target model can be refined by using a computational peptide docking algorithm. Optionally, the computational peptide docking algorithm comprises a Monte Carlo search with minimization algorithm.

[0220] The computational peptide docking algorithm can include some or all of the following steps performed in various orders, including alternative steps, and / or including intermediate steps as understood by a person skilled in the pertinent art. The computational peptide docking algorithm can include the step of: (a) modifying an energy function used to evaluate an MHC- peptide model by reducing the weight of van der Waals repulsive forces and / or increasing the weight of van der Waals attractive forces, optionally both, to an extent that will permit sampling of alternative conformations of the MHC-peptide model while preventing a peptide of the MHC- peptide model from separating from a binding pocket within the groove of the MHC molecule during a subsequent energy minimization reconfiguration of the MHC-peptide model. The computational peptide docking algorithm can include the step of: (b) optimizing a rigid body orientation of the peptide of the MHC-peptide model by applying a random rigid body perturbation, optionally a Gaussian rigid body perturbation, comprising a rotation and / or translation to affect the orientation of the peptide within the MHC-peptide model with respect to the groove, repacking the side chains of rotamers within a peptide-MHC interface of the MHC-peptide model following the random rigid body perturbation, and applying an energy minimization step following the repacking to arrive at a reconfigured rigid body orientation, wherein the repacking comprises optimizing the selection of rotamer combinations for the peptide-MHC interface to eliminate steric clashes, wherein the energy minimization step comprises using a deterministic algorithm to find a local energy minimum, wherein the reconfigured rigid body orientation is accepted only if an energy function criterion, optionally the Metropolis criterion, is met, and wherein the applying of the random rigid body perturbation, the repacking, and the energy minimization step are sequentially repeated for a plurality of cycles, optionally a predefined number of cycles and / or until an energy criterion is satisfied. The computational peptide docking algorithm can include the step of: (c) optimizing the peptide backbone conformation, following optimization of the rigid body orientation, by applying a random torsion angle perturbation to the peptide backbone, optionally comprising a Rosetta small move or a Rosetta shear move, repacking the side chains of retainers within the peptide-MHC interface following the random torsion angle perturbation, and applying an energy minimization step following the repacking to arrive at a reconfigured peptide backbone conformation, wherein the repacking comprises optimizing the selection of rotamer combinations for the peptide-MHC interface to eliminate steric clashes, wherein the energy minimization step comprises using a deterministic algorithm to find a local energy minimum, wherein the reconfigured peptide backbone conformation is accepted only if an energy function criterion, optionally the Metropolis criterion, is met, and wherein the applying of the random torsion angle perturbation, the repacking, and the energy minimization step are sequentially repeated for a plurality of cycles, optionally a predefined number of cycles and / or until an energy criterion is satisfied, optionally wherein the random torsion angle perturbation alternates between Rosetta small moves and Rosetta shear moves each cycle. The Metropolis criterion includes an acceptance criterion from the metropolis algorithm. Specifically, in the context of simulated protein folding, the Metropolis criterion accepts all moves (perturbations) that lower an energy score of the protein and accepts moves (perturbations) that increase the energy score with a predetermined acceptance probability, which may decrease as the energy increase grows larger and / or as the temperature decreases. Alternative random walk algorithms and criterion can be utilized as understood by a person skilled in the pertinent art. The computational peptide docking algorithm can include the step of: (d) repeating steps (b) and (c) for a plurality of cycles wherein the van der Waals forces are gradually ramped back towards normal values suchthat the last cycle is performed with the normal values to arrive at one or more refined MHC- targcts.

[0221] In some embodiments, multiple refined MHC-target can be generated using the computational peptide docking algorithm, alternative computational peptide docking algorithm, or other suitable algorithm as understood by a person skilled in the pertinent art. In such embodiments, the MHC-target peptide model obtained at block 110 may be selected from the multiple refined MHC-target peptides based on lowest energy score and / or highest stability of the refined MHC-targets.

[0222] At block 120, a plurality of comparison MHC-off-target models are obtained such that a potential off-target peptide is respectively represented in one or more of the plurality of comparison MHC-off-target models. Each of the comparison MHC-off-target models can be obtained from a database, generated, and / or refined at block 120. In some embodiments, the off-target peptides represented by the plurality of comparison MHC-off-target models can be a large pool, theoretically all peptides represented in essential normal tissues, or tissues otherwise of concern regarding off-target toxicity. However, in practicality, the availability of 3D computational structures of peptides and MHC-peptide complexes is limited, and therefore database mining is not presently an option. Experimental determination of each of these structures is highly impractical, and even present computational methods for 3D computational modeling of this large of a data set are impractical. Authors contemplate future advancements in database offerings, experimental techniques, and computational methods which may allow for the potential off-target peptides to include a large pool of peptides. In specific examples of implementations of method 100 presented herein, however, the potential off-target peptides represented in one or more of the plurality of comparison MHC-off-target models constitute peptides pre-filtered from the larger pool of peptides so that the number of potential off- target peptides obtained at block 120 is computationally practical for 3D model comparison. In some embodiments, at block 120, the plurality of comparison MHC-off-target models are based on peptide sequences of the potential off-target peptides identified in a pre-filter step. One example of a suitable pre-filter step is the PIGSPRED method described elsewhere herein.

[0223] With a pre-filter step, some or all of the plurality of comparison MHC-off-target models may be obtained experimentally. However, in practice, presently, databases of experimentally determined peptide conformations and MHC-peptide complexes are still inadequate for thepurposes of determining off-target toxicity. Further, even with a pre-filter step to limit the number of off- target peptides, experimental determination for every potential off-target peptide may be impractically resource intensive if not impossible in many applications. For at least these reasons, in silica development of at least a portion of the comparison MHC-off-target models may be necessary in some applications of the method 100. Because method 100 is for the purpose of ranking a plurality of potential off-target peptides of a target peptide, it is preferred that the comparison MHC-off-target models are obtained via the same methodology so that the comparison MHC-off-target models are comparable to each other. Therefore, preferably, each of the comparison MHC-off-target models are, at least in part, computationally generated. Presently, there is no comprehensive database of computationally generated peptides; however, Authors contemplate that such a database can be constructed according to methods disclosed herein. See, for instance, database 600 illustrated in FIG. 10. With the existence of such database, the plurality of comparison MHC-off-target models can be obtained, at block 120, from such database.

[0224] In some embodiments, some or all of the MHC-off-target models for a given off-target peptide is derived from a predicted structure specific to the given off-target peptide (e.g., based at least in pail on an amino acid sequence of the off-target peptide).

[0225] In some embodiments, the plurality of comparison MHC-off-target models are obtained via a method 120 for providing one or more comparison MHC-off-target models for comparison to an MHC-target model as illustrated in FIG. 2. As described in greater detail in relation to FIG. 2, in method 120, the MHC-target peptide model is used as a template, and the peptide sequence of the template structure is substituted by the off-target sequence (a.k.a. threading technique). A coarse-grained MHC-off-target model is generated by packing of the sidechains of off-target peptide and MHC monomers to remove internal clashing.

[0226] Additionally, or alternatively, a template based modeling process can determine the predicted structure for a given off-target peptide by performing steps (a)-(e) of the template based modeling process described in relation to block 110. In addition to, or as an alternative to a template based modeling process, the predicted structure can be determined using a sequencebased machine learning algorithm, which may optionally use a neural network-based model. In some embodiments, the predicted structure can be pre-packed (“prepacked predicted structure”), wherein prepacking the predicted structure is optimized based at least in part on the selection of rotamer combinations for the peptide and MHC molecule to eliminate steric clashes. Optionally,the predicted structure can be based at least in part on a templated-based modeling or experimental measurements followed by prepacking.

[0227] In some embodiments, one or more MHC-off-target models can be generated by refining the predicted structure for a respective off-target peptide. In such embodiments, the predicted structure can include a coarse-grained MHC-off-target peptide model. The coarse-grained MHC- off-target model can be refined by using a computational peptide docking algorithm. Optionally, the computational peptide docking algorithm comprises a Monte Carlo search with minimization algorithm. The computational peptide docking algorithm can include some or all of steps (a)-(c) as described in relation to block 110. The computational peptide docking algorithm can include the step of: (d) repeating steps (b) and (c) for a plurality of cycles wherein the van der Waals forces are gradually ramped back towards normal values such that the last cycle is performed with the normal values to arrive at one or more refined MHC-off-target models for a given off-target peptide.

[0228] In some embodiments, multiple refined MHC-off-target models for a given off-target peptide can be generated using the computational peptide docking algorithm, alternative computational peptide docking algorithm, or other suitable algorithm as understood by a person skilled in the pertinent art. In such embodiments, the MHC-off-target peptide models obtained at block 120 may be selected from the multiple refined MHC-target peptides based on lowest energy score and / or highest stability of the refined MHC-off-target models.

[0229] In some embodiments, the MHC-target model obtained at block 110 and the MHC-off- target models obtained at block 120 are generated using identical or similar methodologies. For instance, a predictive structure (e.g., coarse-grained model) can be obtained via the same methodology for each target peptide and off-target peptide, and the predictive structure can be refined by the same refinement methodology each target peptide and off-target peptide.

[0230] At block 130, a structural similarly metric for each of the potential off-target peptides is computed. The structural similarity metric indicates a degree of similarity between the MHC- target model and some or all of the comparison MHC-off-target models associated with a respective potential off-target peptide. In some embodiments, the structural similarity metric can be calculated according to method 130 illustrated in FIG. 3.

[0231] At block 140, the potential off-target peptides can be ranked based at least in part on the structural similarity metric. In some embodiments, off-target peptides can be ranked according to method 140 illustrated in FIG. 4.

[0232] FIG. 2 is a flow diagram illustrating an exemplary method for providing one or more comparison MHC-off-target models for comparison to an MHC-target model. The one or more comparison MHC-off-target models represent a single off-target peptide in groove with an MHC molecule. The MHC-off-target models can be used to rank potential off-target peptides, such as described in relation to the method 100 of FIG. 1. Additionally, or alternatively, the one or more comparison MHC-off-target models may be useful for other in silico analysis and testing, particularly if models of other structures, such as antigen-recognition molecules, are available for comparison and / or interaction studies.

[0233] At block 121, a coarse-grained MHC-off-target model is generated by a substituting, in the MHC-target model, a sequence of the potential off-target peptide in place of a sequence of the target peptide. Amino acids of the target peptide are replaced by amino acids of the off-target peptide in corresponding positions. The MHC-target model is preferably experimentally generated; however, the MHC-target model may be obtained by other means, for instance as described in greater detail in relation to block 110 of FIG. 1. Unlike other protein structure prediction methods based on protein threading, the target peptide may not be the best fit and / or may not have the highest sequence identity to the off-target peptide as compared to other available templates. However, using the target peptide as a template for threading may prioritize the docking conformation of the target peptide-MHC complex within a noisy solution space of conformations and help ensure that off-target peptide-MHC complex conformations which more closely resemble that of the peptide-MHC complex conformation are analyzed, as these conformations may be more likely to induce off-target effects (via binding of antigen-recognition molecules targeting the target peptide MHC complex) according to the molecular mimicry theory. As a consequence of block 121, the coarse-grained MHC-off-target model is dependent upon the associated target peptide, meaning that for a theoretical off-target peptide which is modeled separately for two different targets, there will be two distinct coarse-grained MHC off-target models, one for each of the two targets. In some embodiments, after substitution of the sequence of the potential off-target peptide in place of a sequence of the target peptide, sidechains of the off-target peptide and MHC monomers can be packed to remove internal clashing. Additionally, or alternatively selection ofrotamer combinations for the off-target peptide and MHC molecule can be optimized to eliminate stcric clashes.

[0234] At block 122, a plurality of refined MHC-off-target models can be generated by computationally optimizing the coarse-grained MHC-off-target model multiple times such that each optimization of the coarse-grained MHC-off-target model results in a respective refined MHC-off-target model of the plurality of refined MHC-off-target models. Therefore block 122 generates a plurality of refined MHC-off-target models which represent a single potential off- target peptide in a groove of an MHC molecule.

[0235] In some embodiments, each coarse-grained MHC-off-target model can be refined using a computational peptide docking algorithm to optimize peptide-MHC backbone and side chains. The peptide docking algorithm may use random conformation sampling and / or deterministic methods to refine the model. Optionally, the computational peptide docking algorithm performs Monte-Carlo sampling with minimization approach of the backbone and on-the-fly side-chain optimization thereby generating multiple models of an off-target peptide-MHC complex from a single coarse-grained MHC-off target model. The computational peptide docking algorithm can include some or all of steps (a)-(c) as described in relation to block 110. The computational peptide docking algorithm can include the step of: (d) repeating steps (b) and (c) for a plurality of cycles wherein the van der Waals forces are gradually ramped back towards normal values such that the last cycle is performed with the normal values to arrive at the plurality of refined MHC-off-target models for a given coarse-grained MHC off-target model.

[0236] In some embodiments, multiple refined MHC-off-target models for a given off-target peptide can be generated using an alternative computational peptide docking algorithm or other suitable refinement algorithm as understood by a person skilled in the pertinent art.

[0237] In some embodiments, the computational peptide docking algorithm (or other suitable algorithm) is repeated multiple times, optionally at least 100, 200, 500, 1,000, 2,000, 5,000, or 10,000 times, to produce the refined MHC-off-target models. In some embodiments, at least 100, 200, 500, 1,000, 2,000, 5,000, or 10,000 refined MHC-off-target models can be generated based at least in part on the coarse-grained MHC-off-target model.

[0238] At block 123, one or more comparison MHC-off-target models may be selected from the plurality of refined MHC-off-target models for further analysis (e.g., comparison to the MHC- target model). The one or more comparison MHC-off-target models may be only a portion of theplurality of refined MHC-off-target models selected, for example, such that the one or more comparison MHC-off-target models have lower energy than a majority of the plurality of the refined MHC-off-target models. As such, the one or more comparison MHC-off-target models provided by method 120 include lower energy and / or more stable refined MHC-off-target models. In some embodiments, the one or more comparison MHC-off-target models may include only models from the top 1%, 5%, or 10% lowest-energy and / or most stable refined MHC-off-target models. In some embodiments, the one or more comparison MHC-off-target models may include only model from the top 5, 10, or 100 lowest-energy and / or most stable refined MHC-off-target models.

[0239] In some embodiments, for each of the refined MHC-off-target models, a series of metrics is computed that helps to identify the lowest energy models. For instance, FlexPepDock protocol is an example computational peptide docking algorithm that provides a reweighted score metric that can be used to select lowest energy stable models among the plurality of refined MHC-off- target models. Reweighted score is defined by the FlexPepDock protocol as a linear sum of a total score of the complex, interface score (energy of the pair-wise interactions across the peptide-MHC interface), and peptide score (sum of an energy function over the peptide residues). The lower the reweighted score the more stable is the predicted peptide-MHC model.

[0240] In some embodiments, five lowest re-weighted score models of the plurality of refined MHC-off-target models are selected such that method 120 provides five comparison MHC-off- target models.

[0241] FIG. 3 is a flow diagram illustrating an exemplary method for quantifying structural similarity between a potential off-target peptide in a groove of an MHC molecule and a target peptide in complex with the MHC molecule for the purposes of antigen-recognition molecule binding.

[0242] At block 131, a plurality of comparison MHC-off-target models is obtained. The plurality of comparison MHC-off-target models can be obtained by methods described in relation to block 120 of FIG. 1, by method 120 in FIG. 2, other method for obtaining MHC-off-target models disclosed herein, variations thereof, alternatives thereto, or other suitable method as understood by a person skilled in the pertinent ail. The plurality of comparison MHC-off target models represent a single potential off-target peptide in a groove of an MHC molecule.

[0243] At block 132, for each of the plurality of comparison MHC-off-target models, one or more structural similarity metrics arc calculated. Each structural similarity metric has a corresponding value for each of the plurality of comparison MHC-off-target models and represents structural similarity between each of the plurality of comparison MHC-off-target models and an MHC-target model. The one or more structural similarity metrics can include metrics associated with protein structure comparison methods such as distance-based measures of protein structure similarity, contact-based measures of protein structure similarity, geometric deep learning methods, and other suitable methods as understood by a person skilled in the pertinent aid.

[0244] Distance-based measures provide a difference value which quantifies distances between atoms, or groups of atoms (e.g., a residue), of the MHC-target model and corresponding atoms, or groups of atoms, of a respective comparison MHC-off-target model of the plurality of comparison MHC-off-target models when aligned or superimposed, including by methods or tools well known in the art (e.g., in a manner that minimizes one or more structural similarity metrics, such as a distance-based measure). Where distances are quantified between groups of atoms, a geometric or weighted center may be used for calculating distances. The difference value itself can be used as a structural similarity metric or a structural similarity metric can be calculated based on the difference value. For distance-based measures, the methodology and the atoms, or groups of atoms, considered can affect the difference value.

[0245] Root mean square deviation (RMSD) is a distance-based comparison methodology that can be used to generate quantitative metrics to measure the average distance between atoms, or groups of atoms, of superimposed protein structures. Generally, a lower RMSD value indicates high similarity in the 3D conformations between two structures. RMSD, other suitable distancebased comparison methodology as understood by a person skilled in the pertinent art, or combination thereof can be utilized at block 132 to generate structural similarity metric(s).

[0246] In one embodiment, values of four similarity metrics are calculated for each MHC-off- target model as described below.

[0247] A first example similarity metric is an RMSD metric which quantifies similarity of the overall peptide-MHC complex structure that includes the peptide and the binding groove region in the al and a2 domain of MHC molecule. The first example similarity metric for a given MHC- off-target model is the RMSD between the MHC-off-target model and MHC-target model considering the aforementioned structures of each model.

[0248] A second example similarity metric is an RMSD metric which quantifies similarity of the peptide conformation in the MHC groove. The second example similarity metric for a given MHC- off-target model is the RMSD between the MHC-off target model and the MHC-target model considering the peptide conformation of each model.

[0249] A third example similarity metric is an RMSD metric to quantify similarity of the conformation of the peptide residue positions important for TCR / Ab interaction. The value of the third example similarity metric for a given MHC-off-target model is the RMSD between the MHC- off target model and the MHC-target model considering conformation of the peptide residue positions important for TCR / Ab interaction of each model. The third example similarity metric quantifies distances between atoms of the MHC-target model at each position that has been determined to be available for binding by an antigen-recognizing molecule to a peptide-MHC (pMHC) complex comprising the target peptide bound to the MHC molecule and all corresponding atoms of the potential off-target peptide backbones of the plurality of comparison MHC-off-target models at each of the corresponding positions.

[0250] RMSD metrics may be quantified by computationally aligning / superimposing in three- dimensional space a given MHC-target model with a particular' MHC-off-target model (e.g., using Pymol or another suitable molecular' visualization tool). The models may be aligned based on sequence similarity (e.g., using the Pymol “align” function”) and / or structural similarity (e.g., using the Pymol “super” function). In some instances, whichever alignment / superimpo sition function minimizes the RMSD may be used. Preferably, the models may be aligned / superimposed without any further refinement of the molecular structures, such as removal of atoms (e.g., with “cycles” set equal to 0 within Pymol). Upon alignment / superimposition, the RMSD may be calculated between selected atoms.

[0251] The first three example metrics demonstrate how selection of atoms for calculation of a structural symmetry metric can affect the value of the structural symmetry metric. Other considerations for atom selection can include consideration of heavy atoms only and / or atoms in the peptide backbone only. For each of the first, second, and third metric, optionally, the first / second / third example similarity metric quantifies distances between heavy atoms only. For each of the first, second, and third metric, optionally, the first / second / third example similarity metric quantifies distances between heavy atoms of the target peptide backbone of the MHC-targetmodel and all corresponding heavy atoms of each of the potential off-target peptide backbones of the plurality of comparison MHC-off-targct models.

[0252] A fourth example similarity metric is determined based on a quantification of a correlation between a molecular surface interaction fingerprint of the MHC-target model and each of the plurality of comparison MHC-off-target models. The molecular' surface interaction fingerprint includes at least one vector that characterizes an interaction probability of a respective model with an antigen-binding molecule based on geometric features and / or chemical features of the molecular' surface. Optionally, the correlation quantification includes a correlation coefficient such as a Pearson correlation coefficient. Optionally, the geometric features comprise shape index or distance-dependent curvature and / or the chemical features comprise hydropathy, continuum electrostatics, or location of free electrons and proton donors.

[0253] In some embodiments, a molecular surface interaction fingerprinting (MaSIF) tool, which is based on a geometric deep learning method, is used to capture fingerprints that are important for specific biomolecular interactions that can be used to produce structural similarity metrics. MaSIF is described in greater detail in Gainza, Pablo, et al. "Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning." Nature Methods 17.2 (2020): 184-192 incorporated by reference herein in its entirety. In some embodiments, to calculate the fourth example similarity metric, first, a geometric deep learning tool such as the MaSIF tool is used to compute a plurality of interaction fingerprints for the MHC-target model as well as for each of the plurality of comparison MHC-off-target models (see, e.g., the “MaSIF-site” application described in Gainza et al, supra). The interaction fingerprints are computed for the peptide-MHC molecular surface that includes the peptide and at least a portion of the MHC molecule, including the binding groove region in the al and a2 domain of MHC molecule (optionally, including only the binding groove region). Each interaction fingerprint is represented as a vector characterizing an interaction probability for a particular portion of the peptide-MHC molecular surface (a “patch”). The patches are then optimally aligned in three-dimensional space and corresponding patches are identified based on the spatial alignment (the number of corresponding patches being less than or equal to the total number of patches for whichever model has the smaller number of total patches). The alignment can be performed, for example, using Pyoints, a python package to process and analyze point cloud data, voxels, and raster images, or other suitable data fusing / processing package as understood by a person skilled in the pertinent art. An aggregate molecular surface interactionfingerprint (MSIF), represented as a vector, that characterizes the spatially distributed interaction probabilities across corresponding patches is then computed for each of the models being compared. Next, a correlation value (e.g., a correlation coefficient such as a Pearson correlation coefficient) of the interaction probabilities of the patches is computed. The correlation can be performed, for instance using Pyoints. The value of the fourth example similarity metric for a given MHC-off-target model is based on the correlation value. A high correlation value indicates that the off-target-MHC complex surface has a similar molecular surface interaction fingerprint (MSIF) to that of the target-MHC complex surface.

[0254] In some embodiments, the molecular surface interaction fingerprint (MSIF) is determined by: (a) decomposing a surface of the respective model into a plurality of overlapping geodesic patches; (b) mapping surface features of the respective model to each of the geodesic patches using polar geodesic coordinates, wherein the surface features comprise one or more, optionally all, of the following features: shape index, distance-dependent curvature, hydropathy, continuum electrostatics, and location of free electrons and proton donors; (c) applying a convolutional neural network to each patch to produce an interaction fingerprint vector for each patch, wherein applying the convolutional neural network comprises rotating the geodesic patch to provide rotation invariance, and wherein the convolutional neural network has been trained on pairs of patches comprising a target patch with a known interacting patch of a binding partner and the target patch with a patch of a random non-binding partner to maximize interaction fingerprint vector differences between non-interacting patches and minimize interaction fingerprint vector differences between interacting patches; and d) determining the molecular surface interaction fingerprint based at least in part on the interaction fingerprint vectors of the plurality of overlapping geodesic patches, wherein determining the molecular surface interaction fingerprint comprises identifying spatially corresponding patches between the MHC-target model and each respective MHC off-target model and wherein the molecular surface interaction fingerprint characterizes the distribution of interaction probabilities across the corresponding patches. Determining the molecular surface interaction fingerprints (MSIFs) based on the interaction fingerprints for the plurality of patches for comparison may be performed as described elsewhere herein (e.g., using Pyoints or other suitable software to align patches and identify corresponding patches).

[0255] At block 133, for each of the one or more structural similarity metrics, a single composite structural similarity metric is calculated. The single composite structural similarity metric has avalue based at least in part on the corresponding structural similarity metric values for at least a portion of the plurality of comparison MHC-off-targct models.

[0256] In some embodiments, the plurality of comparison MHC-off-target models comprises a predetermined number of models, optionally, at least 5. In some embodiments, the number of comparison MHC-off-target models for the potential off-target peptide can be selected from a plurality of refined MHC-off-target models as described in greater detail in relation to block 123 of FIG. 2. In some embodiments, the one or more comparison MHC-off-target models may include 5, 10, or 100 MHC-off-target models.

[0257] In some embodiments, the composite structural similarity metric of each of the one or more structural similarity metrics is based at least in part on an aggregate measure of a respective structural similar- metric for each of the plurality of comparison MHC-off-target models. The aggregate measure can include an average, median, or minimum.

[0258] For instance, in an implementation of the method 130 having the five example structural similarity metrics, respective values for each of the first, second, third, fourth, and fifth example structural similarity metrics can be calculated for each of the comparison MHC-off-target models. Then, a composite structural similarity metric can be calculated for each of the five example structural similarity metrics. The same principle can be applied to any of the example structural similarity metrics and / or other structural similarity metrics as understood by a person skilled in the pertinent art.

[0259] FIG. 4 is a flow diagram illustrating an exemplary method 140 for identifying potential off-target peptide(s) based on sequence similarity and structural similarity for an antigenrecognition molecule that recognizes a target peptide presented in complex with an MHC molecule (MHC-target peptide complex).

[0260] At block 141, a pool of peptides of suitable length is obtained. Optionally, peptides of the pool of peptides are expressed in normal tissues, optionally, essential, normal tissues. In some embodiments the pool of peptides can be assembled based on canonical human protein sequences in a medical research database such as, as a non-limiting example, UniprotKB. In some embodiments, the peptide length is 9 mer, 10 mer, or 11 mer. In some embodiments, the peptide length is the same length as that of the target peptide.

[0261] At block 142, high sequence similarity peptides are identified from within the pool. The identified high sequence similarity peptides (i) have higher sequence similarity to the target peptidethan a majority of peptides within the pool and (ii) have a binding affinity to the MHC molecule greater than a threshold value.

[0262] High similarity peptides identified at block 142 can be based on one or more of the following: (a) a degree of similarity between a sequence of a peptide within the pool and a target peptide sequence of the target peptide, optionally wherein a threshold degree of similarity for selection requires one or more residue mismatches and / or requires one or more identical residues; (b) a number of identical residues, optionally at least three, at positions within the target peptide sequence that have been determined to be available for binding by an antigen-recognizing molecule to a peptide-MHC (pMHC) complex comprising the target peptide bound to the MHC molecule, optionally wherein the positions available for binding an antigen-recognizing molecule have been predicted by a mutagenesis screen to be those positions that, based on changes in binding affinity, are not involved in binding the MHC molecule, optionally wherein the mutagenesis screen is a computational mutagenesis screen and those positions that are not involved in binding the MHC molecule are determined by a machine learning model, such as an artificial neural network, trained on peptide-MHC binding data; (c) binding affinity to the MHC molecule, wherein peptides within the pool that are determined to have a binding affinity below a threshold binding affinity are not selected, optionally wherein binding affinity is determined by a machine learning model, such as an artificial neural network, trained on peptide-MHC binding data; and (d) tissue expression, wherein peptides within the pool that are not expressed in normal tissue, optionally not in essential normal tissue, are not selected. In some embodiments, the proteome is a human proteome and the normal tissue or essential tissue is human tissue.

[0263] The high sequence similarity peptides include at least two amino acids that (i) are located at positions corresponding to positions within the target peptide that are predicted to be available to interact with an antigen-recognition molecule and (ii) are identical to the corresponding amino acids of the target peptide. In some specific embodiments, high sequence similarities may include at least 3, 4, 5 or more amino acids that (i) are located at positions corresponding to positions within the target peptide that are predicted to be available to interact with an antigen-recognition molecule and (ii) are identical to the corresponding amino acids of the target peptide. Sequence similarity may be further evaluated by assessing Degree of Similarity (DoS) or overall peptide sequence similarity across all peptide positions, wherein peptides having more amino acids thatare identical to the amino acids at corresponding positions in the target peptide have a higher DoS and arc more similar’ in sequence.

[0264] In some embodiments the high sequence similarity peptides are identified using the PIGSPRED method.

[0265] At block 143, the potential off-target peptide(s) are identified by selecting, within the high sequence similarity peptides, peptide(s) that are more structurally similar, when positioned in a groove of the MHC molecule, to the MHC-target peptide complex than a majority of the higher sequence similarity peptides. In some embodiments, the selected structurally similar’ peptides are in the top 50th, 40th, 30th, 20th, 10th, 5th, 2nd, or 1stpercentiles of the high sequence similarity peptides. Preferably, the total number of the structurally similar peptides is a manageable number for further in vivo or in vitro testing. In examples presented herein, known off-target peptides were likely to be found by considering the top 20thpercentile. In some embodiments, the percentile considered is between the 20thand 1stpercentiles such that the selected structurally similar peptides are in the top 20dl, 19th, 18th, 17th16th, 15th, 14th, 13d1, 12th, 11th, 10th, 9th, 8th, 7th, 6th, 5th, 4th, 3rd, 2nd, or 1stpercentiles of the high sequence similarity peptides.

[0266] In some embodiments, the method 140 can include quantifying structural similarity between each of the high sequence similarity peptides in a groove of the MHC molecule and the target peptide in the groove of the MHC molecule for the purposes of antigen-recognition molecule binding according to method 130 illustrated in FIG. 3 and / or as described in relation to block 130 of FIG. 1. In some embodiments, the potential off-target peptides are ranked based on structural similarity and a portion of the highest ranking (i.e., most structurally similar’) potential off-target peptide(s) are selected.

[0267] FIG. 5 is a flow diagram illustrating an exemplary method for ranking potential target peptides to mitigate off-target toxicity.

[0268] At block 210, two or more potential target peptides, among disease-associated peptides, that are predicted to bind to an MHC molecule are obtained. Disease-specific MHC-target peptide complexes can be identified by ascertaining genes that are specifically expressed in diseased tissue. In some embodiments, the disease-specific MHC-target peptide complex can be identified based on a medical database such as The Cancer Genome Atlas (TCGA) and Genome Tissue Expression Database (GTEx), which include human gene sequences. In some embodiments, a gene that is expressed in a cancer type at 75-percentile TPM value > 2 and is negligibly expressed in allessential, normal tissues or essential cell types in the GTEx is considered a cancer- specific gene. The canonical protein sequence corresponding to the cancer- specific gene can be derived from a medical research database including canonical human protein sequences such as the UniProtKB database.

[0269] In some embodiments, the two or more potential target peptides are selected from a database such as database 600 illustrated in FIG. 10. In some embodiments, the two or more off- target peptides are selected based on having a low risk metric. In some embodiments, the risk metric is based on a predicted off-target toxicity as determined by the PIGSPRED method or other computational method.

[0270] At block 220, a respective list of potential off-target peptides is obtained for each of the potential target peptides. The respective list of potential off-target peptides can be obtained via the PIGSPRED method, from a database, such as database 600, as disclosed elsewhere herein, and / or by other suitable method as understood by a person skilled in the pertinent art.

[0271] At block 230, potential off-target peptides within the respective list of off-target peptides are ranked, for each of the potential target peptides, based at least in part on structural similarity of each potential off-target peptide to the potential target peptide. The potential off-target peptides can be ranked as disclosed elsewhere herein. For instance, one or more structural similarity metrics can be calculated for each potential off-target peptide, and the potential off-target peptides can be ranked from most structurally similar to least structurally similar based at least in part on the structural similarity metrics.

[0272] At block 240, the two or more potential target peptides can be ranked based at least in part on the ranking of potential off-target peptides within the respective list of potential off-target peptides. In some embodiments, the potential target peptides can be ranked according to the number of potential off-target peptides having at least one structural similarity metric above a predetermined threshold for that target peptide. For example, a first target peptide may be ranked higher than a second target peptide, where the first target peptide is predicted, based at least in part on the methods described herein, to have fewer potential off-target peptides satisfying a structural similarity criterion (e.g., an RMSD between potential off-target peptide backbones and the respective target peptide backbone lower than a threshold RMSD value) than the second target peptide and where the ranking predicts a likelihood of off-target toxicity or related consideration. A ranking of potential target peptides may be used to select one or more target peptides fortherapeutic development (e.g., development of antigen-recognition molecules against the target peptide).

[0273] FIG. 6 is a block diagram of an exemplary system 300 for development of an antigen recognition molecule.

[0274] An in silica (i.e., computational) system 310 ranks potential target peptides and potential off-target peptides for the purpose of providing recommended target and / or off-target peptides for further testing and development. In vivo system 330 synthesizes target and off-target peptides and / or MHC-peptide complexes for development and testing of antigen recognition molecules.

[0275] As illustrated, the in silica system 310 receives target peptide sequences 311 of potential target peptides as an input. A sequence-based target ranking engine 312 ranks the potential target peptides. In some embodiments, the sequence-based target ranking engine 312 utilizes aspects of the PIGSPRED method to rank the target peptides. In some embodiments the sequence-based target ranking engine 312 compares the received target peptide sequences 311 to a database, such as database 600, and selects potential target peptides based on having low risk metric. The sequence-based target ranking engine 312 outputs one or more low risk target sequence(s) 313 and associate high sequence similarity off-target sequences 314.

[0276] The in silica system 310 includes a structure-based off-target ranking engine 400 configured to rank the high sequence similarity off-target sequences 314 based on structural similarity to the target peptide. In some embodiments, the structure-based off-target ranking engine 400 is configured similar to the structure-based off-target ranking engine 400 is illustrated in FIG. 7. In some embodiments, the structure-based off-target ranking engine 400 is configured to computationally execute steps of method 100 illustrated in FIG. 100. In some embodiments, the structure-based off-target ranking engine 400 is configured to rank the low risk target sequence(s) 313 according to method 200 illustrated in FIG. 6. The structure-based off-target ranking engine 400 is configured to output recommended target sequence) s) 316, which may (or may not) be ranked, and may (or may not) include a filtered list of prioritized potential target sequences from the target sequence(s) 313 input to the structure -based off-target ranking engine 400. The structure-based off-target ranking engine 400 is configured to output recommended off- target sequences 317. Although not illustrated, the structure-based off-target ranking engine 400 may optionally output MHC-target models for each of the recommended target sequence(s) 316 and / or MHC-off-target models for each of the recommended off-target sequences 317.

[0277] The recommended target sequence(s) 316 the recommended off-target sequences 317 can be used to identify peptides for an in vivo synthesis process 331 which synthesizes antigen recognition molecules 332 and MHC-off-target peptide complexes 333, which in turn, can be fed into an in vivo testing process 334, which can provide one or more recommended antigen recognition molecule(s) 335 as an output.

[0278] FIG. 7 is a block diagram of an exemplary structure-based off-target ranking engine 400. The structure-based off-target ranking engine 400 receives as a first input 313, an MHC and target peptide sequence or an MHC-target model. The structure -based off-target ranking engine 400 receives, as a second input 314, potential off-target sequences associated with the target peptide of the first input 313. The structure-based off-target ranking engine 400 may be configured to receive an optional third input 401 including residue positions of the target peptide available for binding to an antigen recognition molecule when in an MHC-target peptide complex. The important positions may be determined by the PIGSPRED method, by identifying amino acid positions of the target peptide unbound to the MHC molecule in the MHC-target model, by experimental methods, and / or by other suitable method as understood by a person skilled in the pertinent ail.

[0279] The structure-based off-target ranking engine 400 can include an off-target model engine 410 configured to generate one or more comparison MHC-off-target models for each off-target peptide. In some embodiments, the off-target model engine 410 is configured to execute method 120 in FIG. 2 for each off-target peptide sequence in the second input 314. In some embodiments, the off-target model engine 410 can also generate an MHC-target model if such a model is not provided in the first input 313. Note that the outputs of the off-target model engine 410 may be useful for other purposes beyond the structure-based off-target ranking engine 400 as illustrated, such as in silica evaluation of potential antigen-recognition molecules, comparison to experimentally determined models, and other applications as understood to a person skilled in the pertinent art. Authors contemplate additional use cases are likely to become apparent as computational processing continues to become more available and the field of bioinformatics continues to advance.

[0280] The off-target model engine 410 can include a coarse-grain model builder 411 configured to generate a coarse-grained MHC-off-target model for each off-target peptide sequence provided in the second input 314. In some embodiments, the coarse-grain model builder 411 is further configured to generate a coarse-grained MHC-target model if an MHC-target model is notprovided in the first input 313. In some embodiments, the coarse-grain model builder 411 is configured to execute computational methods as described in relation to block 121 of FIG. 2.

[0281] The off-target model engine 410 can include a model refinement module 412. In some embodiments, the model refinement module is configured to generate one or more refined MHC- off-target models for each coarse-grained MHC-off-target model. The model refinement module 412 may also be configured to generate one or more refined MHC target model if a coarse-grained MHC-off-target model is provided by the coarse-grain model builder 411. In some embodiments, the model refinement module 412 is configured to computationally execute steps associated with block 122 of FIG. 2.

[0282] The off-target model engine 410 can include a model selection module 413. The model selection module 413 is configured to select at least one of the refined MHC-off-target models for each off-target peptide. The model selection module 413 may also select a refined MHC-target model if more than one refined MHC-target model is provided from the model refinement module 412. The selected refined MHC-off-target model(s) are provided as comparison MHC-off-target models for comparison to the MHC-target model. In some embodiments, the model selection module 413 is configured to computationally execute steps associated with block 123 of FIG. 2.

[0283] The structure-based off-target ranking engine 400 can include a similarity engine 420 configured to calculate one or more structural similarity metrics for each off-target peptide of the second input 314. In some embodiments, the similarity engine 420 is configured to calculate each of the structural similarity metric(s) based at least in part on a comparison of the 3D structure of the MHC-target model to each of the MHC-off-target models, or at least a portion of the MHC- off-target models per off-target peptide. In some embodiments, the similarity engine 420 is configured to computationally execute steps of method 130 illustrated in FIG. 3.

[0284] The similarity engine 420 can include a geometric similarity metric calculator 421 and / or an RMSD structural similarity metric calculator 422. The similarity engine 420 can include additional and / or alternative structural similarity metric calculator(s) that are able to calculate a structural similarity metric as understood by a person skilled in the pertinent art. In some embodiments, the geometric structural similarity metric calculator 421 and the RMSD structural similarity metric calculator 422 are configured to execute steps associated with block 132 of FIG. 3. The geometric similarity calculator can utilize geometric deep learning algorithms, such as MaSIF, to calculate a structural similarity metric (e.g., based on geometric and / or chemicalfeatures of the molecular surface, such as shape index, distance-dependent curvature, hydropathy, continuum electrostatics, location of free electrons and proton donors, etc.) as disclosed elsewhere herein, alternatives thereto, and variations thereof as understood by a person skilled in the pertinent art. In embodiments in which the third input 401 including important residue positions are provided as an input to the structure-based off-target ranking engine 400, the RMSD structural similarity metric calculator 422 can calculate a structural similarity metric based only on positions of the target peptide important and / or available for antigen recognition molecule binding (e.g., positions of the target peptide unbound to the MHC molecule in the MHC-target peptide complex).

[0285] The similarity engine 420 can include a similarity metric calculator 423. In some embodiments, the similarity metric calculator 423 is configured to calculate a single composite structural similarity metric having a value based at least in part on the corresponding structural similarity metric values for at least a portion of the plurality of comparison MHC-off-target models. In some embodiments, the similarity metric calculator 423 is configured to computationally execute steps associated with block 133 of FIG. 3.

[0286] The structure-based off-target ranking engine 400 can include a ranking engine 430. The ranking engine is configured to rank, and optionally filter, the off-target peptides based at least in part on the structural similarity metrics calculated by the similarity engine 420.

[0287] The ranking engine 430 includes a ranking module 431 configured to provide an off-target similarity ranking output 411. Examples 1 and 2 provided herein are illustrative examples of how potential peptides can be ranked according to various similarity metrics by the ranking module 431. In some embodiments, the ranking engine 430 is configured to computationally execute steps associated with block 140 of FIG. 1. In some embodiments, the off-target similarity ranking 441 can be stored in a database such as database 600 illustrated in FIG. 10.

[0288] Optionally, the ranking engine 430 can include a selection module 432 configured to select prioritized potential off-target sequences from the second input 314 for further analysis and / or testing. In some embodiments, the selection module 432 is configured to provide the selected potential off-target sequences as a reduced off-target peptide list 442. The reduced off- target peptide list can be used as recommended off-target sequences 317 and provided to an in vivo system 330 for further analysis and testing as described in relation to FIG. 6.

[0289] FIG. 8 is a block diagram of an embodiment of the structure-based off-target prediction engine 400. FIG. 8 may also be considered as an example method flow chart illustrating aspectsof computational methods disclosed herein. The first input (input- 1 ), corresponds to the first input 313 of FIG. 7. In the illustrated embodiment, the first input includes off-target peptides predicted by the PIGSPRED method. The second input (input-2) corresponds to the second input 314 of FIG. 7. In the illustrated embodiment, the second input can include an experimentally solved target-peptide-MHC complex or a computationally modeled target-peptide-MHC complex. The optional third input (input-3) corresponds to the optional third input 401 of FIG. 7. In the illustrated embodiment, the third input includes peptide residue positions important TCR / Ab interaction as determined by any experimental approach.

[0290] The structure-based off-target prediction engine includes two coarse-grained model creation approaches, which correspond to the coarse-grain model builder 411 of FIG. 7. In a first approach, a coarse-grained model is created using Rosetta in two steps. First, a threading approach is utilized in which a template peptide sequence is substituted with the target peptide sequence to build a coarse-grained model. In some examples, the MHC-target model can be used as the template for off-target peptides such that the amino acids of the MHC-target model are replaced by amino acids at corresponding positions of an off-target peptide. Second, packing of the sidechains is performed in each monomers to remove internal clashes that are not related to inter- molecular interactions. In the second approach, a coarse-grained model is created using AlphaFold. In the second approach, peptide-MHC model prediction using AlphaFold with default parameters is used to generate each MHC -off-target model.

[0291] The coarse MHC-off-target models (and optionally a coarse MHC-target model) are then refined using Rosetta. Peptide backbone and side chains are optimized for each model. In the illustrated embodiment, from 10,000 models generated per off-target peptide (and optionally target peptide), 5 lowest Rosetta energy models are selected. These steps correspond to the model refinement module 412 and the model selection module 413 of FIG. 7.

[0292] Finally, the selected 5 lowest Rosetta energy models are utilized as comparison MHC-off- target peptides and are compared for structural similarity to the MHC-target model. In the illustrated embodiment, the comparison includes computation of RMSD between the MHC-target model and MHC-off-target models; computation of median RMSD between; computation of median RMSD of the TCR / Ab interaction residues between the MHC-target model and MHC-off- target models; computation of correlation of the molecular- surface interaction fingerprints (MSIFs) between the MHC-target model and MHC-off-target models complex surfaces; and rank thepredicted off-target peptides by RMSD and MSIF metrics. The comparison block of the illustrated embodiment corresponds to the similarity engine 420 and the ranking module 431 of FIG. 7.

[0293] FIG. 9 is a block diagram of a workflow executable by a structure-based off-target ranking engine. Inputs to the computational workflow include two required inputs and one optional input. The first required input is a list of predicted off-target peptide sequences of equal length to the target peptide sequence. In some embodiments, the peptide length is 9 mer, 10 mer, or 11 mer. The source of these predicted off-targets can be the PIGSPRED or any other available methods which select a workable number of potential off-target peptides. The second required input is 3D- structure of the target-MHC complex in a suitable format (e.g., pdb format). The structure can be either experimentally determined using methods such as X-ray crystallography, Cryo-EM or computational predicted using tools including Rosetta, and AlphaFold. The optional input is a list of residue positions in the target peptide that are important for TCR / Ab interaction. These residues can be determined using structure analysis of target peptide-MHC-TCR / Ab complex or mutation scanning-based approaches such as X-scan.

[0294] The computational workflow can be divided into the following three components: (i) structural modeling of the off-target peptide -MHC complex and identifying lowest energy models,(ii) computing Root Mean Square Deviation (RMSD) and Molecular Surface Interaction Fingerprint (MSIF) metrices to compare 3D conformations of the off targets in MHC groove, and(iii) output metrics for ranking the potential off-target peptides.

[0295] For the first component, the modeling of an off-target peptide-MHC complex is executed in two steps: 1. Creating a coarse-grained model of the peptide-MHC complex, and 2. Refining the docking of peptide in the MHC groove of the coarse-grained model to generate multiple energy minimized stable models.

[0296] The coarse-grained model is generated using Rosetta if an experimental structure of the target peptide-MHC complex is available that can be used as a template. In this Rosetta approach, peptide sequence of the template structure is substituted by the off-target sequence (a.k.a. threading technique) followed by packing of the sidechains of off-target peptide and MHC monomers to remove internal clashing. Alternatively, without experimental target peptide-MHC template structure, AlphaFold2 (AF2) with default parameters generates the coarse-grained model.

[0297] The coarse-grained model is then refined using Rosetta-FlexPepDock protocol to optimize peptide-MHC backbone and side chains. In this protocol, Rosetta performs Monte-Carlosampling with minimization approach of the backbone and on-the-fly side-chain optimization there by generating multiple models of an off-target pcptidc-MHC complex. Currently, the protocol has been parameterized to generate 10000 models per off-target peptide-MHC. For each of these models, the protocol computes a series of metrics that helps to identify the lowest energy models. As recommended in the FlexPepDock protocol, the reweighted score metric is used in the workflow to select lowest energy stable models for downstream analyses. Reweighted score is defined as a linear sum of total score (rosetta energy score of the complex), interface score (energy of the pair-wise interactions across the peptide-MHC interface), and peptide score (sum of the rosetta energy function over the peptide residues). The lower the re weigh ted score the more stable is the predicted peptide-MHC model. We selected five lowest re-weighted score models per off- target peptide-MHC complex for the 3D-comformation comparison purpose (described below).

[0298] For the second component, RMSD and MSIF metrices are computed to compare 3D conformations of the off targets in MHC groove. RMSD is a quantitative metric to measure the average distance between atoms of superimposed protein structures. A lower RMSD value indicates high similarity in the 3D-conformations between two structures. In this workflow, RMSD metric is used to quantify three types of conformational similarities as described below:1. Similarity of the overall peptide-MHC complex structure that includes only the peptide and the binding groove region in the al and a2 domain of MHC molecule: For this computation, align and super functions from Pymol library, with cycles=0 parameter, is used to measure the RMSD between the target-MHC structure and off-target-MHC model.2. Similarity of the peptide conformation in the MHC groove: For this metric, the align and super functions from Pymol library, with cycles=0 parameter, is used to superimpose the target and off-target peptide in the model and measure RMSD.3. Similarity of the conformation of the peptide residue positions important for TCR / Ab interaction: To compute this metric, first, the target and off-target peptide in the model are superimpose using the align and super functions from Pymol library, with cyclcs-0 parameter, and then rms_cur function from Pymol library is used to measure the RMSD of the residue positions important for TCR / Ab interaction.

[0299] Additionally, the fourth metric for conformation comparison is MSIF. A recent publication described a method to compute fingerprint vectors that decipher patterns in protein surfaces important for biomolecular interaction. In this workflow, the method is used to computethe molecular surface interaction fingerprints (MSIFs) on the peptide-MHC molecular surface that includes only the peptide and the binding groove region in the al and a2 domain of MHC molecule. These fingerprints are represented as a vector of interaction probabilities of the patches on the peptide-MHC molecular surface. As an MSIF metric, a correlation of the interaction probabilities of the patches is computed by aligning the molecular surface of target peptide-MHC structure and off target peptide-MHC model using Pyoints package. A high correlation value would indicate the off-target-MHC complex surface to have a similar’ molecular surface interaction fingerprint (MSIF) to that of the target-MHC complex surface.

[0300] All the above described metrices are computed for the selected five lowest re-weighted score models per off-target peptide-MHC complex and finally the median value for the metrics is reported for an off- target peptide-MHC complex.

[0301] For the third component, output of the computational workflow, the method outputs four metrics per off-target peptide. These include median RMSD of the entire MHC and off-target peptide complex, median RMSD of the off-target peptide only, median RMSD of the residues positions important for TCR / Ab interaction, and median molecular surface interaction fingerprint (MSIF) correlation between the target and off-target peptide-MHC molecular’ surfaces.

[0302] The computation workflow is validated using publicly available data as described in greater detail in the Examples section herein. Two public data sources have been used to validate the accuracy of the computational workflow.

[0303] In the first Example, potential off-target peptides for a TCR that targets MA.GEA-3168-176 (EVDPIGHLY (SEQ ID NO: 29)) peptide - HLA-A01 complex are ranked. A set of 231 PIGSPRED predicted off targets were analyzed using the workflow. A computationally predicted model of EVDPDTILK (SEQ ID NO: 205) target peptide - HLA-A01 complex was used as the second input to the workflow. The optional input was not supplied in the first example. The aim here was to check if the workflow can prioritize the known Titan off-target peptide as a top ranked candidate.

[0304] In the second Example, potential off-targets for a bi-specific antibody that targets WT1126- 134 RMFPNAPYL (SEQ ID NO: 241) HLA-A02:01 complex. A set of 142 PIGSPRED and known off-targets were analyzed using the workflow. An experimental X-ray structure of targets WT1 126-134 RMFPNAPYL (SEQ ID NO: 241) HLA-A02:01 complex (PDBID: 3HPJ) was used as the second input. Two runs of the workflow were done, one without the optional input andother with the optional input of peptide residues position 1 ,2,3, and 4 that were known to be important for the antibody interaction.

[0305] FIG. 10 illustrates a block diagram of an exemplary embodiment of a target toxicity database 600 including MHC-target peptide complexes, a list of their respective associated off- target peptides, and an associated risk metric. In some embodiments, the MHC-target peptide complexes included in the database 600 are ranked according to method 200 in FIG. 5. In some embodiments, the off-target list can be determined according to method 140 illustrated in FIG. 4. In some embodiments, the risk metrics can include one or more structural similarity metrics for each off-target peptide calculated according to method 130 in FIG. 3. In some embodiments, a risk metric can be calculated for each off-target peptide based on a weighted sum or other suitable function of the structural similarity metrics for the given off-target peptide.

[0306] FIG. 11 illustrates a block diagram of an embodiment of a computing device 700. As shown, computing device 700 may include one or more processor(s) 710, an I / O device 720, a memory 730 containing an operating system (“OS”) 740, a database 750, and a program 760. In some embodiments, instructions are stored in the memory 730 that are executable by the processor 710 to perform steps of the computational methods disclosed herein. The computing device can include one or more modules or engines for carrying out computational methods disclosed herein. In some embodiments, the VO device 720 is configured to communicate with the respective ancillary features such as databased or software computational tools to carry out the functions and computational steps disclosed herein.

[0307] Computing device 700 may be a single server or may be configured as a distributed computer system including multiple servers or computers that interoperate to perform one or more of the processes and functionalities associated with the disclosed embodiments. In some embodiments, computing device 700 may further include a peripheral interface, a transceiver, a mobile network interface in communication with processor 710, a bus configured to facilitate communication between the various components of computing device 700, and a power source configured to power one or more components of computing device 700. A peripheral interface may include the hardware, firmware and / or software that enables communication with various peripheral devices, such as media drives (e.g., magnetic disk, solid state, or optical disk drives), other processing devices, or any other input source used in connection with the instant techniques. In some embodiments, a peripheral interface may include a serial port, a parallel port, a general-purpose input and output (GPTO) port, a game port, a universal serial bus (USB), a micro-USB port, a high definition multimedia (HDMI) port, a video port, an audio port, a Bluetooth™ port, an NFC port, another like communication interface, or any combination thereof.

[0308] In some embodiments, a transceiver may be configured to communicate with compatible devices and ID tags when they are within a predetermined range. A transceiver may be compatible with one or more of: RFID, NFC, Bluetooth™, low-energy Bluetooth™ (BLE), WiFi™, ZigBee™, ABC protocols or similar technologies.

[0309] A mobile network interface may provide access to a cellular network, the Internet, or another wide-area network. In some embodiments, a mobile network interface may include hardware, firmware, and / or software that allows processor 710 to communicate with other devices via wired or wireless networks, whether local or wide area, private or public, as known in the art. A power source may be configured to provide an appropriate alternating current (AC) or direct current (DC) to power components.

[0310] Processor 710 may include one or more of a microprocessor, microcontroller, digital signal processor, co-processor or the like or combinations thereof capable of executing stored instructions and operating upon stored data. Memory 730 may include, in some implementations, one or more suitable types of memory (e.g., volatile or non-volatile memory, random access memory (RAM), read only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, floppy disks, hard disks, removable cartridges, flash memory, a redundant array of independent disks (RAID), and the like) for storing files, including an operating system, application programs (including, e.g., a web browser application, a widget or gadget engine, or other applications, as necessary), executable instructions, and data. In one embodiment, the processing techniques described herein are implemented as a combination of executable instructions and data within memory 730.

[0311] Processor 710 may be one or more known processing devices, such as a microprocessor from the Pentium™ family manufactured by Intel™ or the Turion™ family manufactured by AMD™. Processor 710 may constitute a single core or multiple core processor that executes parallel processes simultaneously. For example, processor 710 may be a single core processor that is configured with virtual processing technologies. In certain embodiments, processor 710 may use logical processors to simultaneously execute and control multiple processes. Processor 710 mayimplement virtual machine technologies, or other similar known technologies to provide the ability to execute, control, run, manipulate, store, etc. multiple software processes, applications, programs, etc. Other types of processor arrangements could be implemented that provide for the capabilities disclosed herein as understood by a person skilled in the pertinent art.

[0312] Computing device 700 may include one or more storage devices configured to store information used by processor 710 (or other components) to perform certain functions related to the disclosed embodiments. In one example, computing device 700 may include memory 730 that includes instructions to enable processor 710 to execute one or more applications, such as server applications, network communication processes, and any other type of application or software known to be available on computer systems. Alternatively, the instructions, application programs, etc., may be stored in an external storage or available from a memory over a network. The one or more storage devices may be a volatile or non-volatile, magnetic, semiconductor, tape, optical, removable, non-removable, or other type of storage device or tangible computer-readable medium.

[0313] In one embodiment, computing device 700 may include memory 730 that includes instructions that, when executed by processor 710, perform one or more processes consistent with the functionalities disclosed herein. Methods, systems, and articles of manufacture consistent with disclosed embodiments are not limited to separate programs or computers configured to perform dedicated tasks. For example, computing device 700 may include memory 730 that may include one or more programs 760 to perform one or more functions of the disclosed embodiments. Moreover, processor 710 may execute one or more programs 760 located remotely from computing device 700. For example, computing device 700 may access one or more remote programs 760, that, when executed, perform functions related to disclosed embodiments.

[0314] Memory 730 may include one or more memory devices that store data and instructions used to perform one or more features of the disclosed embodiments. Memory 730 may also include any combination of one or more databases controlled by memory controller devices (e.g., server(s), etc.) or software, such as document management systems, Microsoft™ SQL databases, SharePoint™ databases, Oracle™ databases, Sybase™ databases, or other relational databases. Memory 730 may include software components that, when executed by processor 710, perform one or more processes consistent with the disclosed embodiments. In some embodiments, memory 730 may include database 750 for storing related data to enable computing device 700 to perform one or more of the processes and functionalities associated with the disclosed embodiments.

[0315] Computing device 700 may also be communicatively connected to one or more memory devices (c.g., databases (not shown)) locally or through a network. The remote memory devices may be configured to store information and may be accessed and / or managed by computing device 700. By way of example, the remote memory devices may be document management systems, Microsoft™ SQL database, SharePoint™ databases, Oracle™ databases, Sybase™ databases, or other relational databases. Systems and methods consistent with disclosed embodiments, however, are not limited to separate databases or even to the use of a database.

[0316] Computing device 700 may also include one or more I / O devices 720 that may include one or more interfaces for receiving signals or input from devices and providing signals or output to one or more devices that allow data to be received and / or transmitted by computing device 700. For example, computing device 700 may include interface components, which may provide interfaces to one or more input devices, such as one or more keyboards, mouse devices, touch screens, track pads, trackballs, scroll wheels, digital cameras, microphones, sensors, and the like, that enable computing device 700 to receive data from one or more users (such as via user device 130).

[0317] In example embodiments of the disclosed technology, computing device 700 may include any number of hardware and / or software applications that are executed to facilitate any of the operations. The one or more I / O interfaces may be utilized to receive or collect data and / or user instructions from a wide variety of input devices. Received data may be processed by one or more computer processors as desired in various implementations of the disclosed technology and / or stored in one or more memory devices.

[0318] While computing device 700 has been described as one form for implementing the techniques described herein, other, functionally equivalent techniques may be employed as understood by a person skilled in the pertinent art. For example, as known in the art, some or all of the functionality implemented via executable instructions may also be implemented using firmware and / or hardware devices such as application specific integrated circuits (ASICs), programmable logic arrays, state machines, etc. Furthermore, other implementations may include a greater or lesser number of components than those illustrated.

[0319] FIG. 12 illustrates a block diagram of an embodiment of a computing network 800 including computing device(s) 810, server(s) 820, memory store(s) 840, and a network 830 facilitating communication between each. In some embodiments, the network 800 is configuredto execute steps of computational methods as disclosed herein. In some embodiments, one or more computing dcvicc(s) 810 include various engines and / or modules as disclosed elsewhere herein, which may be distributed across the computing device(s). The computing device(s) are configured to communicate with ancillary databases and / or software services to carry out steps of computational methods disclosed herein.

[0320] Network 830 may be of any suitable type, including individual connections via the internet such as cellular or WiFi™ networks. In some embodiments, network 830 may connect terminals, services, and mobile devices using direct connections such as radio-frequency identification (RFID), near-field communication (NFC), Bluetooth™, low-energy Bluetooth™ (BLE), WiFi™, ZigBee™, ambient backscatter communications (ABC) protocols, USB, WAN, or LAN. Because the information transmitted may be personal or confidential, security concerns may dictate one or more of these types of connections be encrypted or otherwise secured. In some embodiments, however, the information being transmitted may be less personal, and therefore the network connections may be selected for convenience over security.

[0321] FIG. 13 illustrates cellular functions related to the example embodiments presented herein. A cell 910 includes MHC -peptide complexes 920, 930 presented on a surface 912 of the cell 910. The cell 910 includes a class I MHC-peptide complex 920 and a class II MHC-peptide complex 930. Each MHC-peptide complex 920, 930 includes a respective MHC molecule 922, 932 and a respective peptide 924, 934. Each peptide 924, 934 includes amino acids that are bound to the respective MHC molecule 922, 932 (illustrated as shaded shapes) and amino acids that are unbound to the respective MHC molecule 922, 932 (illustrated as white shapes). An antigenrecognition molecule 940 includes a receptor 942 that can bind to amino acids of a peptide in an MHC-target peptide complex that are unbound to the MHC molecule. The antigen-recognition molecule 940 may also bind to off-target peptides which have a similar' configuration of amino acids (compared to the MHC-target peptide complex) that are unbound to the respective MHC molecule in an MHC-peptide complex.

[0322] Various methods described herein may relate to identifying (e.g., ranking / selecting) target peptides and / or to identifying (e.g., ranking / selecting) off-target peptides for a given target peptide. Any of these methods may further comprise synthesizing a target peptide and / or one or more off- target peptides identified. Methods for peptide synthesis include those known in the ait and described herein. Any of these methods may further comprise isolating (e.g., purifying) a targetpeptide and / or one or more off-target peptides identified. Methods for peptide isolation and / or purification include those known in the art and described herein. Any of these methods may further comprise loading a target peptide and / or one or more off-target peptides to an MHC molecule or any suitable component thereof to form a pMHC complex as described elsewhere herein. Any of these methods may further comprise binding a target peptide-MHC complex and / or one or more off-target peptide-MHC complexes to an antigen-recognition molecule (e.g., an antibody, TCR, or CAR). For example, any of these methods may comprise screening a target peptide-MHC complex and / or one or more off-target peptide MHC complexes for binding to an antigen-recognition molecule. Any of these methods may comprise incubating and / or contacting a target peptide and / or one or more off-target peptides with one or more cells (e.g., pulsing cells with peptide as described elsewhere herein).

[0323] In a further aspect, provided herein are off-target peptides identified using the methods described herein. Accordingly, the present disclosure also provides libraries (e.g., target-specific libraries) comprising one or more of the off-target peptides identified using the methods described herein. In some embodiments, the libraries of the present disclosure may include the target peptides associated with the off-target peptides as well. In some embodiments, the libraries of the present disclosure may include off-target peptides identified by analyzing experimental structures of a pHLA in complex with an antigen-recognition molecule.

[0324] In some embodiments, off-target peptides identified using the methods described herein may be identified for a Protein Preferentially Expressed Antigen in Melanoma (PRAME) target peptide, e.g., for PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75). PRAME is also known as Melanoma Antigen Preferentially Expressed In Tumors (MAPE), Opa-Interacting Protein 4 (OIP4 or OIP-4), or Cancer / Testis Antigen 130 (CT130). Although not wishing to be bound by theory, PRAME is a cytoplasmic cancer-testis antigen recognized by cytolytic T lymphocytes that is preferentially expressed in most human melanomas and whose expression is associated with, e.g., solid tumors, acute and chronic leukemias, and Hodgkin’s lymphomas. Solid cancers in which PRAME is frequently expressed include, without limitation, head and neck cancer, renal cell carcinoma, breast cancer, and non-small-cell lung cancer.

[0325] Authors have determined that PRAME RNA expression can occur in large subsets of ovarian (90%), uterine, (90%), triple-negative breast cancer (TNBC [80%]), and lung (70%) tumors. Immunohistochemistry (IHC)-based pathological findings demonstrated very lowexpression of PRAME in normal testes, ovarian granulosa, adrenal glands, and kidney tubules. PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) of the present disclosure was found by mass spectrometry techniques in 81% HLA-A2+ melanoma, 58% of uterine, 50% TNBC, and 40% of ovarian tumor patient samples.

[0326] The PRAME gene is a protein coding gene. The PRAME gene encodes the PRAME protein, a transcriptional repressor of nuclear- retinoic acid receptor signaling that confers a growth advantage to cancer cells likely via this function. PRAME prevents retinoic acid-mediated cell proliferation arrest, differentiation, and apoptosis. Alternative splicing leads to multiple transcript variants. PRAME is not expressed in normal tissues, except the testes, other than limited expression in the ovaries, adrenals, and endometrium. PRAME is an intracellular protein, and cannot be targeted by antibodies or conventional CAR T-cells that are restricted to cell surface antigens. As discussed in further detail herein, Authors contemplate using a variety of platforms for targeting PRAME such as, but not limited to, alternative format multispecific (e.g., bispecific) antibodies or antigen-binding fragments thereof, CAR T-cells (e.g., scFv-based CAR T cells) and engineered (T-cell receptor) TCR-T cells, and cancer vaccines. In one embodiment, anti-tumor TCRs may be engineered into T cells for cell-based therapy. In one embodiment, an anti-tumor TCR targeting PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75)-HLA-A*02:01 can be developed for an HLA-A*02:01 / PRAME425-433-targeted autologous TCR T cell therapy.

[0327] Without wishing to be bound by theory, TCRs can be a promising therapeutic modality for the treatment of patients with solid tumors. TCRs greatly expand the repertoire of tumor antigens that can be targeted using immunotherapy, compared to CARs and traditional antibodies. Over 75% of proteins reside exclusively within intracellular compartments. Tumor-associated antigens (TAAs) and tumor- specific antigens (TSAs) typically consist of peptides derived from intracellular proteins that are loaded onto MHC. TCRs recognize tumor antigens via interactions with peptide-MHC (pMHC) complexes. Intracellular antigens undergo proteasomal cleavage to generate antigenic peptides. Peptides are transported into the ER, where they are further processed and loaded onto MHC. pMHC complexes are subsequently trafficked to the cell surface to enable extracellular presentation of intracellular antigens. TCRs are therefore a powerful tool that which can use to leverage the adaptive immune system in targeting and eliminating solid tumors. Ensuring tumor specificity of a target p-MHC is not enough for therapeutic TCR / antibody development; off-target toxicity remains a challenge.

[0328] In some embodiments, the cancer is a hematologic malignancy, for example, a lymphoma, a leukemia, or a myeloma. In some embodiments, the lymphoma is Hodgkin's lymphoma or nonHodgkin’s lymphoma. In some embodiments, the leukemia is chronic lymphocytic leukemia (CLL), acute lymphocytic leukemia (ALL), chronic myeloid leukemia (CML), or acute myeloid leukemia (AML). In some embodiments, the cancer is a solid cancer. In one embodiment, the cancer is a head and neck cancer. In one embodiment, the cancer is a renal cell carcinoma. In one embodiment, the cancer is a breast cancer, e.g., triple-negative breast cancer (TNBC). In one embodiment, the cancer is a non-small cell lung cancer (NSCLC), for example, lung adenocarcinoma. In one embodiment, the cancer is liver hepatocellular carcinoma (HCC). In one embodiment, the cancer is lung squamous cell carcinoma (SCC). In one embodiment, the cancer is bladder cancer. In one embodiment, the cancer is esophageal cancer. In one embodiment, the cancer is uveal melanoma. In one embodiment, the cancer is nasopharyngeal cancer. In one embodiment, the cancer is synovial sarcoma. In one embodiment, the cancer is ovarian cancer. In one embodiment, the cancer is uterine cancer. In one embodiment, the cancer is endometrial cancer. In one embodiment, the cancer is melanoma.

[0329] In various embodiments, Authors contemplate using a variety of platforms for targeting a PRAME, such as, but not limited to, alternative format multispecific (e.g., bispecific) antibodies or antigen-binding fragments thereof, CAR T-cells (e.g., scFv-based CAR T cells) and engineered (T-cell receptor) TCR-T cells, and cancer vaccines. In one embodiment, anti-tumor TCRs may be engineered into T cells for cell -based therapy. In one embodiment, an anti-tumor TCR targeting PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75)-HLA-C*08:02 can be developed for an HLA-A*02:01 / PRAME425 33-targeted autologous TCR T cell therapy.

[0330] Without wishing to be bound by theory, TCRs can be a promising therapeutic modality for the treatment of patients with solid tumors. TCRs greatly expand the repertoire of tumor antigens that can be targeted using immunotherapy, compared to CARs and traditional antibodies. Over 75% of proteins reside exclusively within intracellular compartments. Tumor- associated antigens (TAAs) and tumor- specific antigens (TSAs) typically consist of peptides derived from intracellular proteins that are loaded onto MHC. TCRs recognize tumor antigens via interactions with peptide-MHC (pMHC) complexes. Intracellular antigens undergo proteasomal cleavage to generate antigenic peptides. Peptides are transported into the ER, where they are further processed and loaded onto MHC. pMHC complexes are subsequently trafficked to the cellsurface to enable extracellular presentation of intracellular antigens. TCRs are therefore a powerful tool that which can use to leverage the adaptive immune system in targeting and eliminating solid tumors. Ensuring tumor specificity of a target pMHC is not enough for therapeutic TCR / antibody development; off-target toxicity remains a challenge.

[0331] In certain embodiments, the PRAME target peptide described herein is wild type. In certain embodiments, the PRAME target peptide described herein comprises a mutation (e.g., a deletion, a substitution, or an addition). Non-limiting examples of amino acid mutations comprise amino acid insertions, substitutions, and / or deletions. Inserted amino acid residues may be inserted at any position and inserted amino acid residues may be inserted in a way such that some of or all the inserted amino acid residues are immediately adjacent to one another or such that none of the inserted amino acid residues are immediately adjacent to one another. Amino acid substitution means exchanging an amino acid residue for a replacement amino acid residue at the same position.

[0332] A PRAME target peptide of the present disclosure can comprise about 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 25, 30, 35, 40, 50, 60, 70, 80, 90, or 100 amino, or more acid residues of the PRAME protein. The substitution may be at any position along the length of the target peptide. For example, it may be located in the C terminal third of the target peptide, the central third of the target peptide, or the N terminal third of the target peptide

[0333] In some embodiments, the target peptide (e.g., PRAME target peptide) is 5-40 amino acids in length, or 5-33 amino acids in length, or 5-30 amino acids in length, or 5-23 amino acids in length, 5-20 amino acids in length, or 5-17 amino acids in length, or 5-14 amino acids in length, or 5-12 amino acids in length, or 5-11 amino acids in length, or 5-10 amino acids in length, or 6- 40 amino acids in length, or 6-33 amino acids in length, or 6-30 amino acids in length, or 6-23 amino acids in length, or 6-20 amino acids in length, or 6-17 amino acids in length, or 6-14 amino acids in length, or 6-12 amino acids in length, or 6-11 amino acids in length, or 6-10 amino acids in length, or 7-40 amino acids in length, or 7-33 amino acids in length, or 7-30 amino acids in length, or 7-23 amino acids in length, or 7-20 amino acids in length, or 7-17 amino acids in length, or 7-14 amino acids in length, or 7-12 amino acids in length, or 7-11 amino acids in length, or 7- 10 amino acids in length, or 8-40 amino acids in length, or 8-33 amino acids in length, or 8-30 amino acids in length, or 8-23 amino acids in length, or 8-20 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-40 amino acids in length, or 9-33 amino acids inlength, 9-30 amino acids in length, or 9-23 amino acids in length, or 9-20 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9- 11 amino acids in length, or 9-10 amino acids in length, or 10-40 amino acids in length, or 10-33 amino acids in length, or 10-30 amino acids in length, or 10-23 amino acids in length, or 10-20 amino acids in length, or 10-17 amino acids in length, or 10-14 amino acids in length, or 10-12 amino acids in length, or 10-11 amino acids in length, or 11-40 amino acids in length, or 11-33 amino acids in length, or 11-30 amino acids in length, or 11-23 amino acids in length, or 11-20 amino acids in length, or 11-17 amino acids in length, or 11-14 amino acids in length, or 11-12 amino acids in length, or 12-40 amino acids in length, or 12-33 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 40 amino acids in length, or 39 amino acids in length, or 38 amino acids in length, or 37 amino acids in length, or 36 amino acids in length, or 35 amino acids in length, or 34 amino acids in length, or 33 amino acids in length, or 32 amino acids in length, or 31 amino acids in length, or 30 amino acids in length, or 29 amino acids in length, or 28 amino acids in length, or 27 amino acids in length, or 26 amino acids in length, or 25 amino acids in length, or 24 amino acids in length, or 23 amino acids in length, or 22 amino acids in length, or 21 amino acids in length, or 20 amino acids in length, or 19 amino acids in length, or 18 amino acids in length, or 17 amino acids in length, or 16 amino acids in length, or 15 amino acids in length, or 14 amino acids in length, or 13 amino acids in length, or 12 amino acids in length, or 11 amino acids in length, or 10 amino acids in length, or 9 amino acids in length, or 8 amino acids in length, or 7 amino acids in length, or 6 amino acids in length, or 5 amino acids in length.

[0334] In some embodiments, the target peptide (e.g., PRAME target peptide) is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8-23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9- 20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

[0335] In some embodiments, the PRAME target peptide disclosed herein is a PRAME425 33 peptide having an amino acid sequence of SLLQHLIGL (SEQ ID NO: 75). This peptide sequence has been identified as being on various cancer tissues, including, e.g., melanoma, renal cell carcinoma, lung carcinoma, and mammary carcinoma. See, e.g., Kessler et al., J Exp Med. 2001 Jan 1 ;193(l):73-88; Gloger et al., Cancer Immunol Immunother. 2016 Nov;65(l l):1377-1393. In some embodiments, the PRAME target peptide may be encoded by or derived from any portion or length of a full-length PRAME amino acid or nucleotide sequence known to a person of ordinary skill in the ail, see, e.g., NCBI Reference Sequences NM_001291715.2 and NP_001278644.1, which are each herein incorporated by reference in their entirety.

[0336] In various embodiments, a peptide library of the present disclosure may comprise one or more off-target peptides identified for PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) as described herein. In some embodiments, off-target peptides for PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) can include any of those listed in Table 1 and / or Table 8, or fragments or derivatives thereof. Table 8 is presented and further elaborated upon in detail in Example 6 below.

[0337] Table 1 further includes a ranked order as determined by a structural similarity metric (RMSD) (out of 232 potential off-target peptides) as described in Example 3; the DoS (i.e., the degree of sequence similarity of the off-target peptide with the target peptide considering all amino acid positions); the predicted binding affinity of each off-target peptide represented by the half maximal inhibitory concentration (IC50) value and a binding affinity percentile rank value; a description of the off-target gene corresponding to each of the off-target peptides; the mRNA level (TMP from GTEx) in the normal tissue with the highest expression for each off-target gene, including the top three highly expressing normal tissues; as well as a description of which peptides were present in the internal immunopeptidomics database of MHC-bound peptides identified by mass spectrometry (Mass Spec) in tissue samples, as determined experimentally using exemplary methods of the disclosure.Table 1. Examples of Off-target Peptides for PRAME425-433 Target SLLQHLIGL (SEQ ID NO: 75)

[0338] In some embodiments, potential off-targets associated with the PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75)-HLA-A*02:01 (i) have a DoS of at least 4, (ii) were identified by a bioinformatic screen, such as the PIGSPRED method, which filters for peptides having demonstrated and / or predicted peptide-MHC binding and gene expression in normal human tissue, and (iii) either demonstrated cross-reactivity with an antigen-recognition molecule targeting PRAME425-433 and / or were detected in tissue samples via mass spectrometry.

[0339] In a specific embodiment, off-target peptide LLLPHLHGL (SEQ ID NO: 150) (TMEM205 gene) has a DoS of 6. In a specific embodiment, off-target peptide ILIEHLYGL (SEQ ID NO: 151) (LRP1 gene) has a DoS of 5. In a specific embodiment, off-target HTLDHLHGV (SEQ ID NO: 152) (TTC17 gene) has a DoS of 4. In a specific embodiment, off-target peptide SLQPHLLGL (SEQ ID NO: 153) (INA VA gene) has a DoS of 6.

[0340] In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) comprises an amino acid sequence of any of SEQ ID NOs: 76-98 and 150-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists essentially of an amino acid sequence of any of SEQ ID NOs: 76-98 and 150- 181. In some embodiments, an off-target peptide associated with PRAME425-433 targetSLLQHLIGL (SEQ ID NO: 75) consists of an amino acid sequence of any one of SEQ ID NOs: 76-98 and 150-181.

[0341] In various embodiments, a peptide library of one or more off-target peptides for an identified target peptide may further comprise the target peptide itself (e.g., PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75)). In some embodiments, the target peptide comprises an amino acid sequence of SEQ ID NO: 75 or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, the target peptide consists essentially of an amino acid sequence of SEQ ID NO: 75. In some embodiments, the target peptide consists of an amino acid sequence of SEQ ID NO: 75. In various embodiments, a peptide library of one or more off-target peptides for an identified target peptide, optionally including the target peptide itself (e.g., PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75)) may further include other variants of the target peptide, such as a wild-type / non-mutated version of the target peptide. The target peptide and / or wild-type version of the target peptide may be used, for example, in comparison studies with the one or more off-target peptides, such as to assess antigen-recognition molecule crossreactivity with off-target peptides.

[0342] In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) may be cross -reactive to an antigen-recognition molecule targeting PRAME425-433 such as an antibody or TCR, e.g., a TCR described herein (e.g., PRAME TCR). In some embodiments, an antigen-recognition molecule described herein, such as an antibody or TCR, may react to cells that present PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) in complex with HLA-A*02:01 on a cell surface. In some embodiments, an antigenrecognition molecule described herein, such as an antibody or TCR, may be cross-reactive with an off-target peptide associated with PRAME 25-133 SLLQHLIGL (SEQ ID NO: 75). In specific embodiments, the antigen-recognition molecule (e.g., PRAME TCR) is cross-reactive with off- target peptides LLLPHLHGL (SEQ ID NO: 150) (TMEM205 gene); ILIEHLYGL (SEQ ID NO: 151) (LRP1 gene); HTLDHLHGV (SEQ ID NO: 152) (TTC17 gene); and / or SLQPHLLGL (SEQ ID NO: 153) (INAVA gene). In some specific embodiments, the antigen-recognition molecule (e.g., PRAME TCR) is cross-reactive with ILIEHLYGL (SEQ ID NO: 151) (LRP1 gene).

[0343] The LRP1 gene encodes LRP1 (Low-density lipoprotein receptor-related protein 1, also known as CD91) protein, a member of the low-density lipoprotein receptor family of proteins. LRP1 is a large (-600 kDa, -85 kbp) protein involved in several essential endocytic and signalingprocesses which plays important role in development. LRP1 recognizes more than 30 distinct ligands and has a wide normal tissue expression profile, particularly in vasculature. LRPl-dircctcd toxicity could be potentially devastating due to expression in several essential tissues including vasculature, central nervous system (CNS), lung, etc. Literature review suggests that several disease states can induce upregulation of LRP1 (mRNA and protein) across multiple tissue types, for example, heart (ventricles) (ischemic cardio myopathy); coronary artery, aorta, pulmonary artery (atherosclerosis); brain / nervous system (Alzheimer’ s disease, multiple sclerosis); liver (high cholesterol, upregulation following statin treatment); and kidney (fibrotic kidney, renal injury).

[0344] In some embodiments, the off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) has 9 amino acids. In some embodiments, the off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) can have a similar conformation to PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75), for example, at TCR interacting residue positions determined experimentally herein to be important for TCR interaction (e.g., backbone residues at positions 4, 5, 6, and 8). Off-target peptides of a PRAME425-433 SLLQHLIGL (SEQ ID NO: 75)-HLA-A*02:01 complex can be ranked according to root mean square deviation (RMSD) of the respective off-target peptide backbone conformation relative to the target peptide backbone conformation. The off-target peptides can be sorted by median RMSD value, e.g., for the 30 refined lowest energy MHC-off-target models. A lower RMSD value can indicate a higher degree of structural similarity . Non-limiting examples of off-target peptides having a high degree of structural similarity relative to the target peptide include off-target peptides having the amino acid sequence of SEQ ID NOs: 151-152 and 154-181. In some embodiments, an off-target peptide may be non-reactive to a TCR described herein (e.g., PRAME TCR) as determined by exemplary method described herein. Such off-target peptide may have a dissimilar conformation to the PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75).

[0345] In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) comprises an amino acid sequence of any of SEQ ID NOs: 76-98 and 150-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists essentially of an amino acid sequence of any of SEQ ID NOs: 76-98 and 150- 181. In some embodiments, an off-target peptide associated with PRAME425-433 targetSLLQHLIGL (SEQ ID NO: 75) consists of an amino acid sequence of any one of SEQ ID NOs: 76-98 and 150-181.

[0346] In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) comprises an amino acid sequence of any of SEQ ID NOs: 151- 152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists essentially of an amino acid sequence of any of SEQ ID NOs: 151-152 and 154-181. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181.

[0347] In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) comprises an amino acid sequence of any of SEQ ID NOs: 150- 153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists essentially of an amino acid sequence of any of SEQ ID NOs: 150-153. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists of an amino acid sequence of any one of SEQ ID NOs: 150-153.

[0348] In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) comprises an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists essentially of an amino acid sequence of SEQ ID NO: 151. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) consists of an amino acid sequence of SEQ ID NO: 151.

[0349] In some embodiments, a peptide library comprising off-target peptides described herein may comprise two or more of any of various off-target peptides described herein. As a non-limiting example, a peptide library comprising off-target peptides may comprise two or more peptides each selected from the amino acid sequences of SEQ ID NOs: 76-98 and 150-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative. As another non-limiting example, a peptide library comprising off-target peptides may comprise two or more peptides each selected from the amino acid sequences of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptablesalt thereof, or a fragment or derivative. As yet another non-limiting example, a peptide library comprising off-target peptides may comprise two or more peptides each selected from the amino acid sequences of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative. In a specific embodiment, the off-target peptide, or fragment or derivative thereof, can be, e.g., 8-14 amino acids in length. In another specific embodiment, the off-target peptide, or fragment or derivative thereof, can be, e.g., 12-20 amino acids in length. In some embodiments, the peptides within a peptide library described herein can each present in a complex with a major histocompatibility complex (MHC) molecule described herein. In certain embodiments, the MHC molecule is a class I MHC molecule such as, but not limited to, a class I human leukocyte antigen (HLA) molecule. The class I human leukocyte antigen (HLA) molecule can be an HLA-A molecule. In some embodiments, the HLA-A molecule is an HLA-A2 molecule. In some specific embodiments, the HLA-A2 molecule is HLA-A*02:01 molecule.

[0350] In some embodiments, a peptide within an MHC-peptide complex described herein, e.g., a PRAME425-433 peptide complex, and / or an MHC-off-target peptide complex described herein, e.g., an MHC-off-target peptide complex comprising an off-target peptide associated with PRAME425-433 SLLQHLIGL (SEQ ID NO: 75), can be covalently bound to an MHC described herein.

[0351] In some embodiments, a peptide within an MHC-peptide complex described herein, e.g., a PRAME425-433 peptide complex, and / or an MHC-off-target peptide complex described herein, e.g., an MHC-off-target peptide complex comprising an off-target peptide associated with PRAME425-433 SLLQHLIGL (SEQ ID NO: 75), can be non-covalently bound to an MHC described herein.

[0352] In various embodiments, the present disclosure provides a library comprising two or more proteins or fragments thereof each comprising one or more off-target peptides described herein. In some embodiments, each off-target peptide can be selected from the amino acid sequences of SEQ ID NOs: 76-98 and 150-181. In some embodiments, each off-target peptide can be selected from the amino acid sequences of SEQ ID NOs: 151-152 and 154-181. In some embodiments, each off- target peptide can be selected from the amino acid sequences of SEQ ID NOs: 150-153. Pep tide libraries of present disclosure may comprise any number of a plurality of peptides as desired. For example, a peptide library of the present disclosure may comprise at least 2 peptides, at least 3 peptides, at least 4 peptides, at least 5 peptides, at least 6 peptides, at least 7 peptides, at least 8peptides, at least 9 peptides, at least 10 peptides, at least 20 peptides, at least 30 peptides, at least 40 peptides, at least 50 peptides, or about 2-5 peptides, about 2-10 peptides, about 5-15 peptides, about 10-20 peptides, about 10-30 peptides, about 12-25 peptides, about 20-30 peptides, about 25- 50 peptides, about 40-80 peptides, about 50-100 peptides, about 60-120 peptides, about 70-140 peptides, about 80-160 peptides, about 90-180 peptides, about 100-200 peptides, about 110-220 peptides, about 120-240 peptides, about 130-260 peptides, about 140-280 peptides, about 150-300 peptides, about 160-320 peptides, about 170-340 peptides, about 180-360 peptides, about 190-380 peptides, about 200-400 peptides, about 210-420 peptides, about 220-440 peptides, about 230-460 peptides, about 240-480 peptides, about 250-500 peptides, about 260-520 peptides, about 270-540 peptides, about 280-560 peptides, about 290-580 peptides, about 300-600 peptides, about 310-620 peptides, about 320-640 peptides, about 330-660 peptides, about 340-680 peptides, about 350-700 peptides, about 360-720 peptides, about 370-740 peptides, about 380-760 peptides, about 390-780 peptides, about 400-800 peptides, about 410-820 peptides, about 420-840 peptides, about 430-860 peptides, about 440-880 peptides, about 450-900 peptides, about 460-920 peptides, about 470-940 peptides, about 480-960 peptides, about 490-980 peptides, about 500-1000 peptides, etc.

[0353] In a further aspect, provided herein are databases including computational representations of the off-target peptides identified using the methods described herein. The database can include information for each of the off-target peptides represented in any one of the exemplary libraries disclosed hereinabove. Accordingly, the databases may include computational representations of the target peptides associated with the off-target peptides as well. The computer-readable representations of the peptides in the database can include a peptide sequence or a computer model of the peptide.

[0354] A peptide of the disclosure may be synthetically produced or produced by hydrolysis. Synthetically produced peptides can include randomly generated peptides, specifically designed peptides, and peptides where at least some of the amino acid positions are conserved among several peptides and the remaining positions are random. Alternatively, a peptide of the present disclosure may be produced by expression in a heterologous host cell.

[0355] In some embodiments, peptides of the disclosure can be synthesized by e.g., solid phase synthesis. As such, the peptides may be immobilized, for example to a solid support such as a bead. Peptides of the disclosure may be synthesized by the Fmoc-polyamide mode of solid-phase peptide synthesis. Temporary N-amino group protection is afforded by the 9-fluorenylmethyloxycarbonyl (Fmoc) group. Repetitive cleavage of this highly base-labile protecting group is done using 20% piperidine in N, N-dimcthylformamidc. Side-chain functionalities may be protected as their butyl ethers (in the case of serine threonine and tyrosine), butyl esters (in the case of glutamic acid and aspartic acid), butyloxycarbonyl derivative (in the case of lysine and histidine), trityl derivative (in the case of cysteine) and 4-methoxy -2,3,6- trimethylbenzenesulphonyl derivative (in the case of arginine). Where glutamine or asparagine are C-terminal residues, use is made of the 4,4'-dimethoxybenzhydryl group for protection of the side chain amido functionalities. The solid- phase support is based on a polydimethyl-acrylamide polymer constituted from the three monomers dimethylacrylamide (backbone-monomer), bisacryloylethylene diamine (cross linker) and acryloylsarcosine methyl ester (functionalizing agent). The peptide-to-resin cleavable linked agent used is the acid-labile 4-hydroxymethyl- phenoxyacetic acid derivative. All amino acid derivatives are added as their preformed symmetrical anhydride derivatives except for asparagine and glutamine, which are added using a reversed N, N-dicyclohexyl-carbodiimide / l-hydroxybenzotriazole mediated coupling procedure. All coupling and deprotection reactions are monitored using ninhydrin, trinitrobenzene sulphonic acid or isotin test procedures. Upon completion of synthesis, peptides are cleaved from the resin support with concomitant removal of side-chain protecting groups by treatment with 95% trifluoroacetic acid containing a 50% scavenger mix. Scavengers commonly used include ethanedithiol, phenol, anisole and water, the exact choice depending on the constituent amino acids of the peptide being synthesized. Also, a combination of solid phase and solution phase methodologies for the synthesis of peptides is possible.

[0356] Trifluoroacetic acid is removed by evaporation in vacuo, with subsequent trituration with diethyl ether affording the crude peptide. Any scavengers present are removed by a simple extraction procedure which on lyophilization of the aqueous phase affords the crude peptide free of scavengers.

[0357] Purification may be performed by techniques such as re-crystallization, ion-exchange chromatography, size exclusion chromatography, hydrophobic interaction chromatography and reverse-phase high performance liquid chromatography using e.g., acetonitrile / water gradient separation, or a combination thereof.

[0358] Peptides may be analyzed using thin layer chromatography, electrophoresis, in particular capillary electrophoresis, solid phase extraction (CSPE), reverse-phase high performance liquidchromatography, amino-acid analysis after acid hydrolysis and by fast atom bombardment (FAB) mass spcctromctric analysis, as well as MALDI and ESI-Q-TOF mass spcctromctric analysis.

[0359] Alternatively, the peptide may be produced by recombinant expression in a heterologous host cell. Such methods typically involve the use of a vector comprising a nucleic acid sequence encoding the peptide to be expressed, to express the polypeptide in vivo; for example, in bacteria, yeast, insect or mammalian cells.

[0360] In further embodiments, in vitro cell-free systems may be used. The peptides may be isolated and / or may be provided in substantially pure form. For example, they may be provided in a form which is substantially free of other peptides or proteins.

[0361] A peptide, or fragment or derivative thereof, disclosed herein (e.g., an isolated peptide, an off-target peptide, a target peptide, a peptide within a peptide library, a peptide within an MHC- peptide complex, etc.) may vary in length.

[0362] In some embodiments, the peptides of the disclosure may be 5-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-9 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-10 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-11 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-26 amino acids in length. In someembodiments, the peptides of the disclosure may be 5-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 5-40 amino acids in length. In various embodiments, the peptides of the disclosure may be 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or 40 amino acids in length.

[0363] In some embodiments, the peptides of the disclosure may be 6-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-9 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-10 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-11 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-21 amino acids in length. In someembodiments, the peptides of the disclosure may be 6-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 6-40 amino acids in length.

[0364] In some embodiments, the peptides of the disclosure may be 7-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-9 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-10 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-11 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-19 amino acids in length. In someembodiments, the peptides of the disclosure may be 7-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 7-40 amino acids in length.

[0365] In some embodiments, the peptides of the disclosure may be 8-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-9 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-10 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-11 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-17 amino acids in length. In someembodiments, the peptides of the disclosure may be 8-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 8-40 amino acids in length.

[0366] In some embodiments, the peptides of the disclosure may be 9-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-10 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-11 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-16 amino acids in length. In someembodiments, the peptides of the disclosure may be 9-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 9-40 amino acids in length.

[0367] In some embodiments, the peptides of the disclosure may be 10-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 10-11 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-16 amino acids in length. In someembodiments, the peptides of the disclosure may be 10-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 10-40 amino acids in length.

[0368] In some embodiments, the peptides of the disclosure may be 11-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 11-12 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-17 amino acids in length. In someembodiments, the peptides of the disclosure may be 11-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-19 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-21 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-22 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-23 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-24 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-25 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-26 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-29 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-31 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 11-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 11-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-16 amino acids in length.

[0369] In some embodiments, the peptides of the disclosure may be 12-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 12-13 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-18 amino acids in length. In someembodiments, the peptides of the disclosure may be 12-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 12-40 amino acids in length.

[0370] In some embodiments, the peptides of the disclosure may be 13-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 13-14 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-21 amino acids in length. In someembodiments, the peptides of the disclosure may be 13-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-23 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-25 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-26 ammo acidslength. In some embodiments, the peptides of the disclosure may be 13-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-28 ammo acidslength. In some embodiments, the peptides of the disclosure may be 13-29 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-30 ammo acidslength. In some embodiments, the peptides of the disclosure may be 13-31 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 13-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 13-39 amino acids in length.

[0371] In some embodiments, the peptides of the disclosure may be 14-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 14-15 amino acids in length. In some embodiments, the peptides of the disclosure may be 14-16 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-17 amino acids in length. In some embodiments, the peptides of the disclosure may be 14-18 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-19 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-20 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-21 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-22 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-23 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-24 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 14-26 ammo acids in length. In someembodiments, the peptides of the disclosure may be 14-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 14-28 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 14-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-31 ammo acidslength. In some embodiments, the peptides of the disclosure may be 14-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-33 ammo acidslength. In some embodiments, the peptides of the disclosure may be 14-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-35 ammo acidslength. In some embodiments, the peptides of the disclosure may be 14-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 14-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 14-39 amino acids in length.

[0372] In some embodiments, the peptides of the disclosure may be 15-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 15-16 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-17 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-18 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-19 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-20 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-21 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-22 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-24 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-25 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-26 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-28 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-29 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 15-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-32 ammo acids in length. In someembodiments, the peptides of the disclosure may be 15-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 15-40 amino acids in length.

[0373] In some embodiments, the peptides of the disclosure may be 16-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-17 amino acids in length. In some In some embodiments, the peptides of the disclosure may be 16-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-19 amino acids in length, embodiments, the peptides of the disclosure may be 16-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-23 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-24 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-25 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-26 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-28 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-31 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 16-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-38 ammo acids in length. In some embodiments, the peptides of thedisclosure may be 16-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 16-40 amino acids in length.

[0374] In some embodiments, the peptides of the disclosure may be 17-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 17-18 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 17-40 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-22 amino acids in length.

[0375] In some embodiments, the peptides of the disclosure may be 18-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 18-19 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-21 amino acids in length. In someembodiments, the peptides of the disclosure may be 18-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 18-40 amino acids in length.

[0376] In some embodiments, the peptides of the disclosure may be 19-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 19-20 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-30 amino acids in length. In someembodiments, the peptides of the disclosure may be 19-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 19-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-39 ammo acids in length. In some embodiments, the peptides of the disclosure may be 19-40 amino acids in length.

[0377] In some embodiments, the peptides of the disclosure may be 20-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 20-21 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 20-40 amino acids in length.

[0378] In some embodiments, the peptides of the disclosure may be 21-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 21-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 21-22 amino acids in length. In some embodiments, the peptides of the disclosure may be 21-24 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-25 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-26 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-28 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-29 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-31 amino acidslength. In some embodiments, the peptides of the disclosure may be 21-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-39 ammo acids in length. In some embodiments, the peptides of the disclosure may be 21-40 amino acids in length.

[0379] In some embodiments, the peptides of the disclosure may be 22-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 22-23 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-24 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-25 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-26 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-28 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-29 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 22-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-32 ammo acids in length. In someembodiments, the peptides of the disclosure may be 22-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 22-40 amino acids in length.

[0380] In some embodiments, the peptides of the disclosure may be 23-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 23-24 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-27 amino acids in length. In some embodiments, peptides of the disclosure may be 23-28 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-32 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-33 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-35 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-37 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 23-40 amino acids in length.

[0381] In some embodiments, the peptides of the disclosure may be 24-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 24-25 amino acids in length. In some embodiments, the peptides of the disclosure may be 24-26 ammo acids in length. In some embodiments, the peptides of the disclosure may be 24-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 24-28 ammo acids in length. In someembodiments, the peptides of the disclosure may be 24-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 24-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 24-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 24-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 24-33 ammo acidslength. In some embodiments, the peptides of the disclosure may be 24-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 24-35 ammo acidslength. In some embodiments, the peptides of the disclosure may be 24-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 24-37 ammo acidslength. In some embodiments, the peptides of the disclosure may be 24-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 24-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 24-40 amino acids in length.

[0382] In some embodiments, the peptides of the disclosure may be 25-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 25-26 amino acids in length. In some embodiments, the peptides of the disclosure may be 25-27 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-28 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-29 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-31 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 25-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-39 ammo acids in length. In some embodiments, the peptides of the disclosure may be 25-40 amino acids in length.

[0383] In some embodiments, the peptides of the disclosure may be 26-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 26-27 amino acids in length. In some embodiments, the peptides of the disclosure may be 26-28 amino acids in length. In someembodiments, the peptides of the disclosure may be 26-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 26-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 26-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 26-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 26-33 ammo acidslength. In some embodiments, the peptides of the disclosure may be 26-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 26-35 ammo acidslength. In some embodiments, the peptides of the disclosure may be 26-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 26-37 ammo acidslength. In some embodiments, the peptides of the disclosure may be 26-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 26-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 26-40 amino acids in length.

[0384] In some embodiments, the peptides of the disclosure may be 27-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 27-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 27-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-34 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 27-39 amino acids in length. In some embodiments, the peptides of the disclosure may be 27-40 amino acids in length.

[0385] In some embodiments, the peptides of the disclosure may be 28-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 28-29 amino acids in length. In some embodiments, the peptides of the disclosure may be 28-30 ammo acids in length. In some embodiments, the peptides of the disclosure may be 28-31 ammo acids in length. In some embodiments, the peptides of the disclosure may be 28-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 28-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 28-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 28-35 ammo acids in length. In someembodiments, the peptides of the disclosure may be 28-36 amino acids in length. In some embodiments, the peptides of the disclosure may be 28-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 28-38 amino acids in length. In some embodiments, the peptides of the disclosure may be 28-39 ammo acids in length. In some embodiments, the peptides of the disclosure may be 28-40 amino acids in length.

[0386] In some embodiments, the peptides of the disclosure may be 29-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 29-30 amino acids in length. In some embodiments, the peptides of the disclosure may be 29-31 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 29-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-39 ammo acids in length. In some embodiments, the peptides of the disclosure may be 29-40 amino acids in length.

[0387] In some embodiments, the peptides of the disclosure may be 30-40 amino acids in length.In some embodiments, the peptides of the disclosure may be 30-31 amino acids in length. In some embodiments, the peptides of the disclosure may be 30-32 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-33 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-34 amino acids in length. In some embodiments, the peptides of the disclosure may be 30-35 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-36 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-37 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-38 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-39 ammo acids in length. In some embodiments, the peptides of the disclosure may be 30-40 amino acids in length.

[0388] In some embodiments, the peptides of the disclosure may be 5-40 amino acids in length, or 5-33 amino acids in length, or 5-30 amino acids in length, or 5-23 amino acids in length, 5-20 amino acids in length, or 5-17 amino acids in length, or 5-14 amino acids in length, or 5-12 aminoacids in length, or 5-1 1 amino acids in length, or 5-10 amino acids in length, or 6-40 amino acids in length, or 6-33 amino acids in length, or 6-30 amino acids in length, or 6-23 amino acids in length, or 6-20 amino acids in length, or 6-17 amino acids in length, or 6-14 amino acids in length, or 6-12 amino acids in length, or 6-11 amino acids in length, or 6-10 amino acids in length, or 7-40 amino acids in length, or 7-33 amino acids in length, or 7-30 amino acids in length, or 7-23 amino acids in length, or 7-20 amino acids in length, or 7-17 amino acids in length, or 7-14 amino acids in length, or 7-12 amino acids in length, or 7-11 amino acids in length, or 7-10 amino acids in length, or 8-40 amino acids in length, or 8-33 amino acids in length, or 8-30 amino acids in length, or 8-23 amino acids in length, or 8-20 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8- 10 amino acids in length, or 9-40 amino acids in length, or 9-33 amino acids in length, 9-30 amino acids in length, or 9-23 amino acids in length, or 9-20 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 10-40 amino acids in length, or 10-33 amino acids in length, or 10-30 amino acids in length, or 10-23 amino acids in length, or 10-20 amino acids in length, or 10-17 amino acids in length, or 10-14 amino acids in length, or 10-12 amino acids in length, or 10-11 amino acids in length, or 11-40 amino acids in length, or 11-33 amino acids in length, or 11-30 amino acids in length, or 11-23 amino acids in length, or 11-20 amino acids in length, or 11-17 amino acids in length, or 11-14 amino acids in length, or 11-12 amino acids in length, or 12-40 amino acids in length, or 12-33 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 40 amino acids in length, or 39 amino acids in length, or 38 amino acids in length, or 37 amino acids in length, or 36 amino acids in length, or 35 amino acids in length, or 34 amino acids in length, or 33 amino acids in length, or 32 amino acids in length, or 31 amino acids in length, or 30 amino acids in length, or 29 amino acids in length, or 28 amino acids in length, or 27 amino acids in length, or 26 amino acids in length, or 25 amino acids in length, or 24 amino acids in length, or 23 amino acids in length, or 22 amino acids in length, or 21 amino acids in length, or 20 amino acids in length, or 19 amino acids in length, or 18 amino acids in length, or 17 amino acids in length, or 16 amino acids in length, or 15 amino acids in length, or 14 amino acids in length, or 13 amino acids in length, or 12 amino acids in length, or 11amino acids in length, or 10 amino acids in length, or 9 amino acids in length, or 8 amino acids in length, or 7 amino acids in length, or 6 amino acids in length, or 5 amino acids in length.

[0389] In some embodiments, the peptides of the disclosure may be 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8-23 amino acids in length, or 8- 17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

[0390] The peptides of the disclosure may comprise one or more chemical modifications. Nonlimiting examples of chemical modifications include, for example, phosphorylation, acetylation, deamidation acylation, amidination, pyridoxylation of lysine, reductive alkylation, trinitrobenzylation of amino groups with 2,4,6-trinitrobenzene sulphonic acid (TNBS), amide modification of carboxyl groups and sulphydryl modification by performic acid oxidation of cysteine to cysteic acid, formation of mercurial derivatives, formation of mixed disulfides with other thiol compounds, reaction with maleimide, carboxymethylation with iodoacetic acid or iodoacetamide and carbamoylation with cyanate at alkaline pH. Chemical modifications may correspond to those that are not present in vivo.

[0391] For example, modification of, for example, arginyl residues in proteins may be based on the reaction of vicinal dicarbonyl compounds such as phenylglyoxal, 2,3-butanedione, and 1,2- cyclohexanedione to form an adduct. Another example is the reaction of methylglyoxal with arginine residues. Cysteine can be modified without concomitant modification of other nucleophilic sites such as lysine and histidine. Selective reduction of disulfide bonds in proteins can also be performed. Disulfide bonds can be formed and oxidized during the heat treatment of biopharmaceuticals. Woodward’s Reagent K may be used to modify specific glutamic acid residues. N-(3-(dimethylamino)propyl)-N'-ethylcarbodiimide can be used to form intra-molecular crosslinks between a lysine residue and a glutamic acid residue. For example, diethylpyrocarbonate and 4-hydroxy-2-nonenal can be used to modify histidyl residues in proteins. The reaction of lysine residues and other a-amino groups is, for example, useful in binding ofpeptides to surfaces or the cross-linking of proteins / peptides. Lysine is the site of attachment of poly(cthylcnc)glycol and the major site of modification in the glycosylation of proteins. Methionine residues in proteins can be modified with e.g., iodoacetamide, bromoethylamine, and chloramine T. Tetranitromethane and N-acetylimidazole can be used for the modification of tyrosyl residues. Cross-linking via the formation of dityrosine can be accomplished with hydrogen peroxide / copper ions. N-bromosuccinimide, 2-hydroxy-5-nitrobenzyl bromide or 3-bromo-3- methyl-2-(2-nitrophenylmercapto)-3H-indole (BPNS-skatole) have been used in recent studies for the modification of tryptophan.

[0392] Peptides described herein may comprise one or more (e.g., 1, 2, 3, or 4) amino acid substitutions and / or insertions and / or deletions. Amino acid substitution means that an amino acid residue is substituted for a replacement amino acid residue at the same position. Inserted amino acid residues may be inserted at any position and may be inserted such that some or all of the inserted amino acid residues are immediately adjacent one another or may be inserted such that none of the inserted amino acid residues is immediately adjacent another inserted amino acid residue. One or more (e.g., 1, 2, 3 or 4) amino acids may be substituted and / or inserted and / or deleted from the sequence of any one of SEQ ID NOs: 76-98 and 150-181. Each substitution and / or insertion and / or deletion can take place at any position of any one of SEQ ID NOs: 76-98 and ISO- 181.

[0393] In some embodiments, the peptides of the disclosure may comprise additional amino acids (e.g., 1, 2, 3 or 4) at the C-terminal end and / or at the N-terminal end of the sequence of any one SEQ ID NOs: 76-98 and 150-181. A peptide of the disclosure may comprise the amino acid sequence of any one of SEQ ID NOs: 76-98 and 150-181 except for one or more (e.g., 1, 2, 3, or 4) amino acid substitutions, insertions or deletions.

[0394] Amino acid substitutions may be conservative, by which it is meant the substituted amino acid has similar chemical properties to the original amino acid. For example, the following groups of amino acids share similar chemical properties such as size, charge, and polarity: Group 1 - Ala, Ser, Thr, Pro, Gly; Group 2 - Asp, Asn, Glu, Gin; Group 3 - His, Arg, Lys; Group 4 - Met, Leu, He, Vai, Cys; Group 5 - Phe, Thy, Trp.

[0395] In another aspect, the disclosure provides a complex of a peptide of the disclosure and an MHC molecule (pMHC complex). Preferably, the peptide is bound to the peptide binding groove of the MHC molecule. In some embodiments, the peptide and the MHC molecule form a non-covalent complex. In other embodiments, the peptide and the MHC molecule may be covalently linked, for example, via a linker. Accordingly, the present disclosure also provides libraries comprising one or more of the pMHC complexes described herein.

[0396] An exemplary pMHC complex library of the present disclosure may comprise one or more pMHC complexes comprising an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) as described herein. In some embodiments, off-target peptides associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) include those listed in Table 1 and / or Table 8 herein. In some embodiments, an off-target peptide associated with PRAME425- 433 target SLLQHLIGL (SEQ ID NO: 75) present in pMHC complexes comprises an amino acid sequence of any of SEQ ID NOs: 76-98 and 150-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME42.W 3 target SLLQHLIGL (SEQ ID NO: 75) present in pMHC complexes comprises an amino acid sequence of any of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) present in pMHC complexes comprises an amino acid sequence of any of SEQ ID NOs: 150-153, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) present in a pMHC complex consists essentially of an amino acid sequence of any of SEQ ID NOs: 76-98 and 150-181. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) present in a pMHC complex consists essentially of an amino acid sequence of any of SEQ ID NOs: 151-152 and 154-181. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) present in a pMHC complex consists essentially of an amino acid sequence of any of SEQ ID NOs: 150-153. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) present in a pMHC complex consists of an amino acid sequence of any one of SEQ ID NOs: 76-98 and 150-181. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQ ID NO: 75) present in a pMHC complex consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181. In some embodiments, an off-target peptide associated with PRAME425-433 target SLLQHLIGL (SEQID NO: 75) present in a pMHC complex consists of an amino acid sequence of any one of SEQ ID NOs: 150-153.

[0397] pMHC complex libraries of present disclosure may comprise any number of a plurality of pMHC complexes as desired. For example, a pMHC complex library of the present disclosure may comprise at least 2 pMHC complexes, at least 3 pMHC complexes, at least 4 pMHC complexes, at least 5 pMHC complexes, at least 6 pMHC complexes, at least 7 pMHC complexes, at least 8 pMHC complexes, at least 9 pMHC complexes, at least 10 pMHC complexes, at least 20 pMHC complexes, at least 30 pMHC complexes, at least 40 pMHC complexes, at least 50 pMHC complexes, or about 2-5 pMHC complexes, about 2-10 pMHC complexes, about 5-15 pMHC complexes, about 10-20 pMHC complexes, about 10-30 pMHC complexes, about 12-25 pMHC complexes, about 20-30 pMHC complexes, about 25-50 pMHC complexes, about 40-80 pMHC complexes, about 50-100 pMHC complexes, about 60-120 pMHC complexes, about 70-140 pMHC complexes, about 80-160 pMHC complexes, about 90-180 pMHC complexes, about 100- 200 pMHC complexes, about 110-220 pMHC complexes, about 120-240 pMHC complexes, about 130-260 pMHC complexes, about 140-280 pMHC complexes, about 150-300 pMHC complexes, about 160-320 pMHC complexes, about 170-340 pMHC complexes, about 180-360 pMHC complexes, about 190-380 pMHC complexes, about 200-400 pMHC complexes, about 210-420 pMHC complexes, about 220-440 pMHC complexes, about 230-460 pMHC complexes, about 240-480 pMHC complexes, about 250-500 pMHC complexes, about 260-520 pMHC complexes, about 270-540 pMHC complexes, about 280-560 pMHC complexes, about 290-580 pMHC complexes, about 300-600 pMHC complexes, about 310-620 pMHC complexes, about 320-640 pMHC complexes, about 330-660 pMHC complexes, about 340-680 pMHC complexes, about 350-700 pMHC complexes, about 360-720 pMHC complexes, about 370-740 pMHC complexes, about 380-760 pMHC complexes, about 390-780 pMHC complexes, about 400-800 pMHC complexes, about 410-820 pMHC complexes, about 420-840 pMHC complexes, about 430-860 pMHC complexes, about 440-880 pMHC complexes, about 450-900 pMHC complexes, about 460-920 pMHC complexes, about 470-940 pMHC complexes, about 480-960 pMHC complexes, about 490-980 pMHC complexes, about 500-1000 pMHC complexes, etc.

[0398] MHC molecules used in pMHC complexes described herein include naturally occurring full-length MHC molecules as well as individual chains of MHC molecules (e.g., MHC class I a (heavy) chain, p2-microglobulin, MHC class II a chain, and MHC class II P chain), individualsubunits of such chains of MHCs (e.g., al , a2 and / or a3 subunits of MHC class I a chain, al and / or a2 subunits of MHC class II a chain, pi and / or 02 subunits of MHC class II P chain) as well as fragments, mutants, and various derivatives thereof (including fusion proteins, e.g., fusions with viral envelope proteins or fusogens), wherein such fragments, mutants, and derivatives retain the ability to display an antigenic determinant for recognition by an antigen- recognition molecule.

[0399] Naturally-occurring MHC molecules are encoded by a cluster of genes on human chromosome 6 or mouse chromosome 17. MHCs are also referred to as H-2 in mice and Human Leucocyte Antigen (HLA) in humans. MHC class I molecules specifically bind CD8 molecules expressed on cytotoxic T lymphocytes (CD8+ T cells), whereas MHC class II molecules specifically bind CD4 molecules expressed on helper T lymphocytes (CD4+ T cells). MHCs include, but are not limited to, HLA specificities such as A (e.g., A1-A74), B (e.g., B1-B77), C (e.g., Cl-Cl l), D (e.g., D1-D26), E, G, DR (e.g., DR1-DR8), DQ (e.g., DQ1-DQ9) and DP (e.g., DP1-DP6).

[0400] In some embodiments, the MHC molecule in a pMHC complex of the present disclosure is a human leukocyte antigen (HLA) molecule. The MHC molecule may be a human HLA molecule selected from the group consisting of HLA-A, HLA-B, HLA-C, HLA-E, HLA-F, and HLA-G. In some embodiments, the MHC class I or MHC II polypeptides may be derived from any functional human HLA-A, B, C, DR, or DQ molecules. Non-limiting examples of HLA-A alleles comprise, without limitation, A*01:01, A*02:01, A*02:02, A*03:01, A*l l:01, A*23:01, A*24:02, A*25:01, A*26:01, A*29:01, A*29:02, A*31:01, A*32:01, A*33:01, A*34:01, A*36:01, A*43:01, A*66:01, A*68:01, A*69:01, A*74:01, and A*80:01. Non-limiting examples of HLA-B alleles comprise, without limitation, B*07:02. B*08:01, B*13:01, B*14:01, B*14:02, B*15:01, B*18:01, B*18:02, B*27:01, B*27:02, B*35:01, B*35:02, B*37:01, B*38:01, B*39:01, B*40:01, B*41:01, B*42:01, B*44:02, B*45:01, B*46:01, B*47:01, B*48:01, B*49:01, B*50:01, B*51:01, B*52:01, B*53:01, B*54:01, B*55:01, B*55:02, B*56:01, B*57:01, B*58:01, B*59:01, B*67:01, B*73:01, B*15:17, B*81:01, B*82:01, and B*83:01. Non-limiting examples of HLA-C alleles comprise, without limitation, C*01:01, C*02:02, C*O3:O3, C*04:01, C*05:01, C*06:02, C*07:01, C*07:02, C*08:02, C*12:03, C*14:01, C*15:02, C*16:01, C*17:01, and. C*18:01. Nonlimiting examples of HLA-DR alleles comprise, without limitation, DRBl*01:01, DRBl*01:03, DRBl*15:01, DRB1*15:O2, DRB1*16:O1, DRB1*16:O2, DRBl*03:01, DRBl*04:01,DRBl*04:04, DRBl*l l:01, DRB1*12:O1, DRBl*13:01, DRB1*13:O2, DRB1*14:O1,DRB 1 * 14:02, DRB 1 *07:01 , DRB 1 *08:01 , DRB 1 *08:02, DRB 1*08:03, DRB 1 *09:01 , and DRBl*10:01.

[0401] In some embodiments, the MHC class I molecule may be selected from HLA-A*02, HLA- A*01, HLA-A*03, HLA-A*11, HLA-A*23, HLA-A*24, HLA-B*07, HLA-B*08, HLA-B*40, HLA-B*44, HLA-B*15, HLA-C*04, HLA*C*03, and HLA-C*07. There are also allelic variants of the above HLA types, all of which are encompassed by the present disclosure.

[0402] In some embodiments, the MHC molecule may be HLA-A*02:01 or HLA-A*01:01.

[0403] Naturally occurring MHC class I molecules consist of an a (heavy) chain associated with |32-microglobulin. The heavy chain consists of subunits al-a3. The P2-microglobulin protein and a3 subunit of the heavy chain are associated. In certain embodiments, p2-microglobulin and 3 subunit are covalently bound. In certain embodiments, p2-microglobulin and a3 subunit are noncov alently bound. The al and 2 subunits of the heavy chain fold to form a groove for a peptide to be displayed and recognized by TCR.

[0404] In some embodiments, the MHC contained in a pMHC complex of the disclosure comprises (i) a class I MHC polypeptide or a fragment, mutant or derivative thereof, and, optionally, (ii) a p2 microglobulin polypeptide or a fragment, mutant or derivative thereof. In one specific embodiment, the class I MHC polypeptide is linked to the P2 microglobulin polypeptide by a peptide linker.

[0405] pMHC complexes of the disclosure may be isolated and / or in a substantially pure form. For example, the complex may be provided in a form which is substantially free of other peptides or proteins. MHC molecules as disclosed herein can include recombinant MHC molecules, non- naturally occurring MHC molecules, and functionally equivalent fragments of MHC, including derivatives or variants thereof, provided that peptide binding is retained. For example, MHC molecules may be attached to a solid support, in soluble form, attached to a tag, biotinylated and / or in multimeric form. A peptide disclosed herein may be covalently attached to the MHC.

[0406] Methods to produce soluble recombinant MHC molecules with which peptides disclosed herein can form a complex include, but are not limited to, expression and purification from E. coll cells or insect cells. Alternatively, MHC molecules may be produced synthetically, or using cell free systems.

[0407] The peptides disclosed herein may be presented on the surface of a cell in complex with MHC. Thus, the present disclosure also provides a cell presenting on its surface a pMHC complexIl ldisclosed herein. Such a cell may he a mammalian cell, preferably a cell of the immune system, and a specialized antigen-presenting cell (APC) such as a dendritic cell or a B cell. The cell may be an immortalized cell. The cell may be a cell that does not naturally present the peptide of interest. In certain embodiments, the cell may be a cell that is deficient in presenting endogenous peptides in complex with MHC on the cell surface. For example, the cell may be a cell that has been genetically modified to be deficient in endogenous peptide presentation, such as a cell that has been modified to be transporter associated with antigen processing (TAP) deficient. The cell may be a cell that requires loading exogenous peptide on the cell surface in order to measurably detect antigen-recognition molecule binding to the peptide. Incubation of the cell with exogenous 02 microglobulin (02m) may increase the loading / presentation of exogenously administered peptides. Preferred cells may include T2 cells, which arc well known in the ait. See, e.g., Elliot et al., I Exp Med. 1995 Apr 1 ; 181(4): 1481-91, which is herein incorporated by reference in its entirety. Cells presenting a peptide or pMHC complex of the disclosure may be isolated, preferably in the form of a homogenous population, or provided in a substantially pure form. Such cells may not naturally present a pMHC complex of the disclosure, or alternatively said cells may present the pMHC complex at a level higher than they would in nature. Cells presenting pMHC complexes may be obtained by pulsing said cells with one or more peptides (e.g., 2 to 10, 2 to 20, 2 to 30, 5 to 25, 5 to 20, or 10 to 15 peptides) of the disclosure, or genetically modifying the cells (via DNA or RNA transfer) to express one or more peptides (e.g., 2 to 10, 2 to 20, 2 to 30, 5 to 25, 5 to 20, or 10 to 15 peptides) of the disclosure. Pulsing involves incubating the cells with the peptide for several hours using peptide concentrations typically ranging from 10-5to 10-12M. Pulsing may also involve incubating the cells with exogenous 02m molecules, for example at the same or in similar concentrations as the peptide. Such cells may additionally be transduced with HLA molecules, such as HLA-A*02 to further induce presentation of the peptide(s). Cells may be produced recombinantly. Cells presenting peptides of the disclosure may be used to isolate antigen-binding molecules (e.g., antibodies, T cells, TCRs and CARs) which can bind to the cells.

[0408] Peptides or pMHC complexes disclosed herein may be fused or conjugated to one or more heterologous molecules. Peptides or pMHC complexes of the disclosed herein may also be in multimeric form. Accordingly, the present disclosure also provides fusion proteins, conjugates, and oligomeric complexes comprising a peptide or a pMHC complex of the disclosure.

[0409] In some embodiments, peptides are fused or conjugated to one or more heterologous molecules which can include an MHC molecule (or fragments thereof).

[0410] Heterologous molecules suitable for genetical fusion and / or chemical conjugation with the peptides or the pMHC complexes of the disclosure include, but are not limited to, peptides, polypeptides, small molecules, polymers, nucleic acids, lipids, sugars, etc. The heterologous molecule(s) may be fused at the N- and / or C-terminus of the peptide and / or another polypeptide chain in the pMHC complex.

[0411] Heterologous peptides and polypeptides include, but are not limited to, an epitope (e.g., FLAG) or a tag sequence (e.g., Hise (SEQ ID NO: 149), and the like) to allow for the detection and / or isolation of a fusion protein; a transmembrane receptor protein or a portion thereof, such as an extracellular domain or a transmembrane and intracellular domain; a ligand or a portion thereof which binds to a transmembrane receptor protein; an enzyme or portion thereof which is catalytically active; a polypeptide or peptide which promotes oligomerization, such as a leucine zipper domain; a polypeptide or peptide which increases stability, such as an immunoglobulin constant region (e.g., an Fc domain); a half-life-extending sequence comprising a combination of two or more (e.g., 2, 5, 10, 15, 20, 25, etc.) naturally occurring or non-naturally occurring charged and / or uncharged amino acids (e.g., Ser, Gly, Glu or Asp) designed to form a predominantly hydrophilic or predominantly hydrophobic fusion partner for a fusion protein; a functional or nonfunctional antibody (e.g., an antibody that is specific for dendritic cells), or a heavy or light chain thereof; and a polypeptide which has an activity different from fusion proteins of the present disclosure.

[0412] In some embodiments, fusion proteins of the disclosure may comprise one or more affinity tags, e.g., to allow for affinity purification or coupling to another molecule. Examples of affinity tags include, but are not limited to, a Hise (SEQ ID NO: 149) tag, an Avi-tag, a biotin, a hemagglutinin (HA) tag, a FLAG tag, a Myc tag, a GST tag, a MBP tag, a chitin binding protein tag, a calmodulin tag, a V5 tag, a streptavidin binding tag, a green fluorescent protein (GFP), YFP, RFP, CFP, mCherry, tdTomato, SUMO tag, and Ubiquitin tag.

[0413] Peptides or pMHC complexes of the disclosure may be provided in soluble form, or may be immobilized by attachment to a suitable solid support. Examples of solid supports include, but are not limited to, a bead (e.g., a magnetic bead), a membrane, sepharose, a plate, a tube, a column, etc. pMHC complexes may be attached, for example, to an ELISA plate, a magnetic bead, or asurface plasmon resonance biosensor chip. Methods of attaching peptides or pMHC complexes to a solid support arc known to the skilled person, and include, for example, using an affinity binding pair, e.g., biotin and streptavidin, or antibodies and antigens. In some embodiments, peptides or pMHC complexes are labeled with biotin and attached to streptavidin-coated surfaces.

[0414] In another aspect, the disclosure provides an isolated polynucleotide comprising a nucleic acid sequence encoding one or more peptide(s) and / or peptide-based molecules (such as complexes (e.g., pMHC complexes), fusion proteins, or conjugates comprising the described peptides) of the disclosure. The polynucleotide may be, for example, DNA, cDNA, PNA, RNA or combinations thereof, either single- and / or double- stranded, or native or stabilized forms of polynucleotides, such as, for example, polynucleotides with a phosphorothioate backbone and it may or may not contain introns so long as it codes for the peptide.

[0415] In some embodiments, a polynucleotide described herein encodes a peptide comprising an amino acid sequence of any one of SEQ ID NOs : 76-98 and 150- 181 , or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting essentially of an amino acid sequence of any one of SEQ ID NOs: 76-98 and 150-181, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting of an amino acid sequence of any one of SEQ ID NOs: 76-98 and 150-181, or a fragment or derivative thereof.

[0416] In some embodiments, a polynucleotide described herein encodes a peptide comprising an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting essentially of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154- 181, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting of an amino acid sequence of any one of SEQ ID NOs: 151- 152 and 154-181, or a fragment or derivative thereof

[0417] In some embodiments, a polynucleotide described herein encodes a peptide comprising an amino acid sequence of any one of SEQ ID NOs: 150-153, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting essentially of an amino acid sequence of any one of SEQ ID NOs: 150-153, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptideconsisting of an amino acid sequence of any one of SEQ ID NOs: 150- 153, or a fragment or derivative thereof.

[0418] In some embodiments, a polynucleotide described herein encodes a peptide comprising an amino acid sequence of SEQ ID NOs: 151, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting essentially of an amino acid sequence of SEQ ID NOs: 151, or a fragment or derivative thereof. In some embodiments, the polynucleotide described herein encodes a peptide consisting of an amino acid sequence of SEQ ID NOs: 151, or a fragment or derivative thereof.

[0419] In a further aspect, the disclosure provides a vector comprising a nucleic acid sequence of the disclosure. The vector may include, in addition to a nucleic acid sequence encoding only a peptide of the disclosure, one or more additional nucleic acid sequences encoding one or more additional peptides. Such additional peptides may, once expressed, be fused to the N-terminus or the C-terminus of the peptide of the disclosure. Examples of such additional peptides are detailed in the sections above. In one embodiment, the vector includes a nucleic acid sequence encoding a peptide or protein tag such as, for example, a biotinylation site, a FLAG-tag, a MYC-tag, an HA- tag, a GST-tag, a Strep-tag or a poly-histidine tag.

[0420] The off-target peptides identified herein may be us...

Claims

CLAIMSWhat is claimed is:

1. An isolated peptide comprising an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

2. The peptide of claim 1, or a pharmaceutically acceptable salt thereof, wherein the isolated peptide comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154- 181.

3. The peptide of claim 2, or a pharmaceutically acceptable salt thereof, wherein the isolated peptide consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154- 181.

4. The peptide of claim 1, or a pharmaceutically acceptable salt thereof, wherein the isolated peptide comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150.

5. The peptide of claim 4, or a pharmaceutically acceptable salt thereof, wherein the isolated peptide consists of an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150.

6. The peptide of claim 1 or a pharmaceutically acceptable salt thereof, wherein the isolated peptide comprises an amino acid sequence of SEQ ID NO: 151.

7. The peptide of claim 6, or a pharmaceutically acceptable salt thereof, wherein the isolated peptide consists of an amino acid sequence of SEQ ID NO: 151.

8. The peptide of any one of claims 1-7, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, wherein the isolated peptide comprises one or more non-proteogenic amino acids, one or more non-naturally occurring amino acids, one or more non-nativc peptide bonds, or any combination thereof, optionally wherein the isolated peptide comprises one or more reverse peptide bonds, one or more D-isomers of amino acids, one or more chemical modifications, or any combination thereof.

9. The peptide of any one of claims 1-8, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, wherein the isolated peptide is produced by expression in a heterologous host cell.

10. The peptide of any one of claims 1-9, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, wherein the isolated peptide is produced synthetically.

11. The peptide of any one of claims 1-10, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, wherein the isolated peptide, or fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8-23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

12. A fusion protein comprising one or more peptides of any one of claims 1-11, or fragments or derivatives thereof, fused to one or more heterologous molecules.

13. The fusion protein of claim 12, wherein the one or more heterologous molecules comprise an MHC molecule, or a fragment or derivative thereof.

14. The fusion protein of claim 13, wherein the MHC molecule is a class I MHC molecule.

15. The fusion protein of claim 14, wherein the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

16. The fusion protein of claim 15, wherein the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

17. The fusion protein of claim 16, wherein the HLA-A molecule is an HLA-A*02:01 molecule.

18. A conjugate comprising one or more peptides of any one of claims 1-11, or fragments or derivatives thereof, conjugated to one or more heterologous molecules.

19. The conjugate of claim 18, wherein the one or more heterologous molecules comprise an MHC molecule, or a fragment or derivative thereof.

20. The conjugate of claim 19, wherein the MHC molecule is a class I MHC molecule.

21. The conjugate of claim 20, wherein the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

22. The conjugate of claim 21, wherein the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

23. The conjugate of claim 22, wherein the HLA-A molecule is an HLA-A*02:0i molecule.

24. The conjugate of claim 18, wherein the one or more peptides, or fragments or derivatives thereof, are conjugated to a particle or a solid support.

25. An oligomeric complex comprising two or more isolated peptides of any one of claims 1- 11, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

26. A non-covalcnt complex comprising (i) the isolated peptide of any one of claims 1-11 or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and (ii) an MHC molecule, or a fragment or derivative thereof.

27. The non-covalent complex of claim 26, wherein the MHC molecule is a class I MHC molecule.

28. The non-covalent complex of claim 27, wherein the class I MHC molecule is a class I human leukocyte antigen (HL A) molecule.

29. The non-covalent complex of claim 28, wherein the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

30. The non-covalent complex of claim 29, wherein the HLA-A molecule is an HLA-A*02:01 molecule.

31. A composition comprising (i) one or more isolated peptides of any one of claims 1-11, one or more fusion proteins of any one of claims 12-17, one or more conjugates of any one of claims 18-24, one or more oligomeric complexes of claim 25, or one or more non-covalent complexes of any one of claims 26-30, or any combination thereof; and (ii) a carrier or excipient.

32. An isolated cell comprising the one or more fusion proteins of any one of claims 12-17, one or more conjugates of any one of claims 18-24, one or more oligomeric complexes of claim 25, or one or more non-covalent complexes of any one of claims 26-30, or any combination thereof.

33. The isolated cell of claim 32, wherein the isolated cell is an immune cell.

34. The isolated cell of claim 32 or claim 33, wherein the isolated cell is an antigen-presenting cell (APC).

35. An isolated polynucleotide comprising a nucleotide sequence encoding one or more isolated peptides of any one of claims 1-11 or one or more fusion proteins of any one of claims 12-17.

36. The isolated polynucleotide of claim 35, wherein the nucleotide sequence is operably linked to a promoter.

37. The isolated polynucleotide of claim 35 or claim 36, wherein the isolated polynucleotide comprises DNA.

38. The isolated polynucleotide of claim 35 or claim 36, wherein the isolated polynucleotide comprises RNA.

39. The isolated polynucleotide of claim 38, wherein the RNA is mRNA.

40. The isolated polynucleotide of claim 38, wherein the RNA is self-replicating RNA.

41. A vector comprising the isolated polynucleotide of any one of claims 35-40.

42. The vector of claim 41, wherein the vector is an expression vector.

43. The vector of claim 41 or claim 42, wherein the vector is a viral vector.

44. A host cell comprising the isolated polynucleotide of any one of claims 35-40 or the vector of any one of claims 41-43.

45. The host cell of claim 44, wherein the host cell is a prokaryotic cell.

46. The host cell of claim 44, wherein the host cell is a eukaryotic cell.

47. The host cell of claim 46, wherein the host cell is an immune cell.

48. The host cell of claim 46 or claim 47, wherein the host cell is an antigen-presenting cell(APC).

49. A composition comprising (i) the isolated polynucleotide of any one of claims 35-40 or the vector of any one of claims 41-43; and (ii) a carrier or excipient.

50. The composition of claim 49, wherein the carrier is a lipid nanoparticle carrier.

51. A composition comprising (i) one or more isolated peptides of any one of claims 1-11, one or more fusion proteins of any one of claims 12-17, one or more conjugates of any one of claims 18-24, one or more oligomeric complexes of claim 25, one or more non-covalent complexes of any one of claims 26-30, or one or more cells of any one of claims 32-34 and 44-48, or any combination thereof, conjugated to a solid support.

52. The composition of claim 51, wherein the solid support is a multi- well plate.

53. A kit comprising:(i) a) one or more isolated peptides of any one of claims 1-11; b) one or more fusion proteins of any one of claims 12-17; c) one or more conjugates of any one of claims 18-24; d) one or more oligomeric complexes of claim 25; e) one or more non- covalent complexes of any one of claims 26-30; f) one or more compositions of any one of claims 31 and 49-52; g) one or more cells of any one of claims 32-34 and 44-48; h) one or more polynucleotides of any one of claims 35-40; and / or i) one or more vectors of any one of claims 41-43;(ii) optionally, an antigen-recognition molecule that targets PRAME425-433 peptide; and / or(iii) optionally, packaging and / or instructions for use for the same.

54. The kit of claim 53, wherein the antigen-recognition molcculc(s) comprises an antibody, a T cell receptor (TCR), or a chimeric antigen receptor (CAR).

55. An in vitro method of assessing off-target effects of an antigen-recognition molecule that targets PRAME425-433 peptide, comprising: a) contacting the antigen-recognition molecule with PRAME425-433 peptide presented in a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-PRAME425-433 peptide complex); b) contacting the antigen-recognition molecule with one or more off-target peptides, wherein each of said off-target peptides (i) comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and (ii) is presented in a complex with the same kind of MHC molecule, or the fragment or derivative thereof, as in (a) (MHC-off-target peptide complex); and c) determining the level of binding of the antigen-recognition molecule to the MHC- PRAME425-433 peptide complex and each of the MHC-off-target peptide complexes.

56. An in vitro method of assessing off-target effects of an antigen-recognition molecule that targets PRAME425-433 peptide, comprising: a) contacting the antigen-recognition molecule with one or more off-target peptides, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and wherein each of said off-target peptides is presented in one of the following forms: (1) as a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-off-target peptide complex), (2) as a peptide, or (3) as a protein or fragment thereof comprising said peptide; and b) determining the level of binding of the antigen-recognition molecule to said one or more MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides.

57. The method of claim 55 or claim 56, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

58. The method of claim 57, wherein each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

59. The method of claim 55 or claim 56, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

60. The method of claim 59, wherein each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

61. The method of claim 55 or claim 56, wherein the off-target peptide comprises an amino acid sequence of SEQ ID NOs: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

62. The method of claim 61, wherein the off-target peptide consists of an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

63. The method of any one of claims 55-62, further comprising determining that the antigenrecognition molecule is likely to have off-target effects if it detectably binds to at least one MHC-off-target peptide complex, off-target peptide or protein or fragment thereof comprising said off-target peptide.

64. A method for selecting an antigen-recognition molecule that targets PRAME425-433 peptide, comprising: a) contacting a plurality of antigen-recognition molecules with PRAME425-433 peptide presented in a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-PRAME425-433 peptide complex); b) contacting the same plurality of antigen-recognition molecules with one or more off-target peptides, (i) wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, and (ii) wherein each of said off-target peptides is presented in one of the following forms: (1) as a complex with the same kind of MHC molecule, or the fragment or derivative thereof as in (a) (MHC-off-target peptide complex), (2) as a peptide, or (3) as a protein or fragment thereof comprising said off-target peptide; c) selecting one or more antigen-recognition molecules based on their level of binding to MHC-PRAME425 -433 peptide complex and based at least in part on the number of different MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides detectably bound by each of the antigen-recognition molecules; and d) optionally, repeating steps (a)-(c) using the one or more selected antigenrecognition molecules.

65. The method of claim 64, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

66. The method of claim 65, wherein each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

67. The method of claim 64, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

68. The method of claim 67, wherein each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

69. The method of claim 64, wherein the off-target peptide comprises an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

70. The method of claim 69, wherein the off-target peptide consists of an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

71. The method of any one of claims 64-70, wherein the one or more selected antigenrecognition molecules detectably bind no more than five MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides.

72. The method of claim 71, wherein the one or more selected antigen-recognition molecules do not detectably bind to any of the tested MHC-off-target peptide complexes, off-target peptides or proteins or fragments thereof comprising said off-target peptides.

73. The method of any one of claims 64-72, wherein the plurality of antigen-recognition molecules is in a library.

74. The method of claim 73, wherein the library is a phage display library or a yeast library.

75. The method of any one of claims 55-74, wherein one or more of the MHC-PRAME425 33 peptide complexes, MHC-off-targct peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides, are immobilized on a solid support.

76. The method of any one of claims 55-74, wherein one or more of the MHC-PRAME425-433 peptide complexes, MHC-off-target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides, are present on a surface of a cell.

77. The method of claim 63 or 76, wherein the antigen-recognition molecule is likely to have off-target effects if it detectably binds to at least one MHC-off-target peptide complex, or off-target peptide or protein or fragment thereof comprising said off-target peptide, when the off-target peptide is present on a surface of a cell at a copy number of at least about 1,000 copies / cell.

78. The method of any one of claims 64-74 and 76, wherein the one or more selected antigenrecognition molecules do not detectably bind to any of the tested MHC-off-target peptide complexes, or off-target peptides or proteins or fragments thereof comprising said off- target peptides, when the off-target peptide is present on a surface of a cell at a copy number of at least about 1,000 copies / cell.

79. The method of any one of claims 64-74 and 76, wherein each of said one or more off-target peptides is presented as an MHC-off-target peptide complex, or a fragment or derivative thereof, on a surface of a cell at a copy number of at least about 1,000 copies / cell.

80. The method of any one of claims 55-79, wherein one or more of the MHC-PRAME425 33 peptide complexes, MHC-off-target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides are present in a soluble form.

81. The method of any one of claims 55-80, wherein the level of binding is determined by detecting the amount of antigen-recognition molecules bound to the MHC-PRAME425-433peptide complexes, MHC-off-target peptide complexes, off-target peptides, or proteins or fragments thereof comprising said off-target peptides.

82. The method of any one of claims 55-81, wherein the method is performed in a high- throughput format.

83. The method of claim 82, wherein the method is performed in a multi- well plate.

84. A method of enriching a sample for antigen-recognition molecules that target PRAME425- 433 peptide, comprising: a) contacting a sample comprising a plurality of antigen-recognition molecules with PRAME425-133 peptide presented in a complex with a major histocompatibility complex (MHC) molecule, or a fragment or derivative thereof (MHC-PRAME425- 433 peptide complex) in the presence of one or more off-target peptides, wherein each of said off-target peptides (i) comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof, wherein each of said one or more off-target peptides is presented in one of the following forms: (1) as a complex with an MHC molecule, or a fragment or derivative thereof (MHC-off- target peptide complex), (2) as a peptide, or (3) as a protein or fragment thereof comprising said off-target peptide; b) enriching the sample by isolating the antigen-recognition molecules that are detectably bound to said MHC-PRAME425-433 peptide complex; and c) optionally, repeating steps (a)-(b) using the enriched sample.

85. The method of claim 84, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

86. The method of claim 85, wherein each of said off-target peptides consists of amino acid sequence of any one of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

87. The method of claim 84, wherein each of said off-target peptides comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

88. The method of claim 87, wherein each of said off-target peptides consists of an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

89. The method of claim 84, wherein the off-target peptide comprises an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

90. The method of claim 89, wherein the off-target peptide consists of an amino acid sequence of SEQ ID NO: 151, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

91. The method of any one of claims 84-90, wherein said MHC-PRAME425-433 peptide complex is present on a cell or solid support and said off-target peptides or proteins or fragments thereof comprising said off-target peptides or MHC-off-target peptide complexes are present in solution.

92. The method of any one of claims 84-91 , wherein said MHC-PRAME425-433 peptide complex is labeled and said off-target peptides or proteins or fragments thereof comprising said off- target peptides or MHC-off-target peptide complexes are not labeled or are labeled differently.

93. The method of any one of claims 55-92, wherein the PRAME425-433 peptide comprises the amino acid sequence of SLLQHLIGL (SEQ ID NO: 75).

94. The method of claim 93, wherein the PRAME425-433 peptide consists of the amino acid sequence SLLQHLIGL (SEQ ID NOs: 75).

95. The method of any one of claims 55-94, wherein the off-target peptide comprises an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181.

96. The method of claim 95, wherein the off-target peptide consists of an amino acid sequence of any one of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181.

97. The method of any one of claims 55-96, wherein each of said off-target peptides is presented as an MHC-off-target peptide complex.

98. The method of claim 97, wherein the MHC molecule is a class I MHC molecule.

99. The method of claim 98, wherein the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

100. The method of claim 99, wherein the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

101. The method of claim 100, wherein the HLA-A molecule is an HLA-A*02:01 molecule.

102. The method of any one of claims 55-101, wherein the peptide within the MHC-PRAME425- 433 peptide complex and / or MHC-off-target peptide complex is covalently bound to the MHC.

103. The method of any one of claims 55-101 , wherein the peptide within the MHC-PRAME425- 433 peptide complex and / or MHC-off-targct peptide complex is non-covalcntly bound to the MHC.

104. The method of any one of claims 55-103, wherein the antigen-recognition molecule(s) comprises an antibody, a T cell receptor (TCR), or a chimeric antigen receptor (CAR).

105. The method of any one of claims 55-104, wherein each of said off-target peptides, or a fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8-23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

106. A library of off-target peptides, said library comprising two or more off-target peptides each selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

107. The library of claim 106, said library comprising two or more off-target peptides each selected from the amino acid sequences of SEQ ID NOs: 151-152 and 154-181, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

108. The library of claim 106, said library comprising two or more off-target peptides each selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, and 150, or a pharmaceutically acceptable salt thereof, or a fragment or derivative thereof.

109. The library of any one of claims 106-108, wherein the at least two off-target peptides are each present in a complex with a major histocompatibility complex (MHC) molecule.

110. The library of claim 109, wherein the MHC molecule is a class I MHC molecule.

111. The library of claim 110, wherein the class I MHC molecule is a class I human leukocyte antigen (HLA) molecule.

112. The library of claim 111, wherein the class I HLA molecule is an HLA-A molecule, optionally an HLA-A2 molecule.

113. The library of claim 112, wherein the HLA-A molecule is an HLA-A*02:01 molecule.

114. The library of any one of claims 106-113, wherein the peptide within the MHC-off-target peptide complex is covalently bound to the MHC.

115. The library of any one of claims 106-113, wherein the peptide within the MHC-off-target peptide complex is non-covalently bound to the MHC.

116. A library comprising two or more proteins or fragments thereof each comprising one or more off-target peptides, wherein each of said off-target peptides is selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, 150, 76-98, and 154-181, or fragments or derivatives thereof.

117. The library of claim 116, wherein each of said off-target peptides is selected from the amino acid sequences of SEQ ID NOs: 151-152 and 154-181, or fragments or derivatives thereof.

118. The library of claim 116, wherein each said off-target peptides is selected from the amino acid sequences of SEQ ID NOs: 151, 152, 153, and 150, or fragments or derivatives thereof.

119. The library of any one of claims 106-1 18, wherein each of said off-target peptides, or a fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8-23 amino acids in length, or 8-17 amino acids in length, or 8-14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

120. A library comprising: a) two or more isolated peptides of any one of claims 1-11; b) two or more fusion proteins of any one of claims 12-17; c) two or more conjugates of any one of claims 18-24; d) two or more oligomeric complexes of claim 25; e) two or more non- covalent complexes of any one of claims 26-30; f) two or more compositions of any one of claims 31 and 49-52; g) two or more cells of any one of claims 32-34 and 44-48; h) two or more polynucleotides of any one of claims 35-40; and / or i) two or more vectors of any one of claims 41-43, optionally wherein each element of the library exists in a separate container.

121. The library of claims 120, wherein each of said isolated peptides, or a fragment or derivative thereof, is 5-30 amino acids in length, or 8-30 amino acids in length, or 8-20 amino acids in length, or 8-23 amino acids in length, or 8-17 amino acids in length, or 8- 14 amino acids in length, or 8-12 amino acids in length, or 8-11 amino acids in length, or 8-10 amino acids in length, or 9-30 amino acids in length, or 9-20 amino acids in length, or 9-23 amino acids in length, or 9-17 amino acids in length, or 9-14 amino acids in length, or 9-12 amino acids in length, or 9-11 amino acids in length, or 9-10 amino acids in length, or 12-30 amino acids in length, or 12-23 amino acids in length, or 12-20 amino acids in length, or 12-17 amino acids in length, or 12-14 amino acids in length, or 12 amino acids in length, or 10 amino acids in length, or 9 amino acids in length.

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