Multiplexed target-binding candidate screening analysis

Abstract

A method and system for normalizing a polymerase chain reaction (PCR) amplification process for a plurality of samples containing DNA. Cycle data for performing a PCR amplification process for the plurality of samples is identified. The cycle data includes corresponding cycle numbers for each sample of the plurality of samples. The plurality of samples are sorted into a plurality of bins based on the cycle data such that cycle number variation between bins of the plurality of bins is reduced. A bin cycle number is assigned to each bin of the plurality of bins. The bin cycle number is unique for each bin of the plurality of bins. Bin identification information is generated. An output for performing PCR amplification of the plurality of samples is generated using the plurality of bins and the bin cycle number for each bin of the plurality of bins.

Description

[Technical Field]

[0001] Inventors: Christian N. Cunningham, Kenneth K. Hallenbeck Cross-reference of related applications This application claims priority to U.S. Provisional Patent Application No. 63 / 092,104, “Multiplexed Target-Binding Candidate Screening Analysis,” filed on 15 October 2020, which is incorporated herein by reference in its entirety.

[0002] Field of Invention Methods and systems for improved multiplex screening analysis are provided herein. More specifically, methods and systems for multiplex screening of nucleotide-labeled peptide libraries for target-binding activity are provided. [Background technology]

[0003] Background of the Invention Current multiplexed target binding candidate screening and analysis systems face challenges in simultaneously selecting a multi-nucleotide-containing peptide library for binding to a desired target due to issues such as sample variability and data complexity. Therefore, improved multiplexed target binding candidate screening and analysis systems and methods are needed to facilitate the simultaneous selection of candidate bindants for desired binding targets, such as proteins. [Overview of the project]

[0004] Summary of the Invention The embodiments described herein provide various methods, systems, and computer program products for improved multiplex screening analysis.

[0005] In some embodiments, a method is provided for normalizing multiple libraries of DNA-containing compositions. The method comprises receiving quantification information for each of the multiple libraries of DNA-containing compositions for a first selection round, each library comprising a DNA conjugate, and the first selection round selects the DNA conjugates based on their binding affinity to a target protein. The method further comprises using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each library, and determining whether each DNA-containing composition in the library can or should produce a relevant preset amount of DNA after PCR for the corresponding PCR cycle number. The method further comprises sorting the libraries of DNA-containing compositions into bins using the corresponding PCR cycle numbers thus determined, each bin comprising a different subset of libraries of DNA-containing compositions determined to share a common PCR cycle number for DNA amplification, and each subset of libraries of DNA-containing compositions in the same bin sharing a different common PCR cycle number than that of the other bins of libraries. The method further includes instructing a thermocycler to perform PCR simultaneously on one of the vials in the same run, with a corresponding common number of PCR cycles for a subset of the DNA-containing composition library in the same vial. The method further includes instructing a thermocycler to perform PCR on each of an additional vial with a corresponding common number of PCR cycles so that multiple libraries of DNA-containing composition are normalized.

[0006] In some embodiments, a computer program product is provided, tangibly embodied on a non-temporary machine-readable storage medium, which includes instructions configured to cause one or more data processors to perform a method for normalizing a plurality of libraries of DNA-containing compositions. The method comprises receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each library comprising a DNA conjugate, and the first selection round selecting the DNA conjugates based on their binding affinity to a target protein. The method further comprises using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each library, so that each DNA-containing composition in the library is determined to produce a relevant preset amount of DNA after PCR is performed for the corresponding PCR cycle number. The method further comprises sorting the libraries of DNA-containing compositions into bins using the corresponding PCR cycle numbers thus determined, each bin comprising a different subset of libraries of DNA-containing compositions which is determined to share a common PCR cycle number for DNA amplification, and each subset of libraries of DNA-containing compositions in the same bin shares a different common PCR cycle number than that of the other bins of libraries. The method further includes instructing a thermocycler to perform PCR simultaneously on one of the vials in the same run, with a common number of PCR cycles corresponding to a subset of libraries of DNA-containing compositions in the same vial. The method further includes instructing a thermocycler to perform PCR on each library of DNA-containing compositions in an additional vial, so that multiple libraries of DNA-containing compositions are normalized.

[0007] In some embodiments, a system is provided for normalizing multiple libraries of DNA-containing compositions. The system includes a data store configured to store a dataset containing quantification information for each of the multiple libraries of DNA-containing compositions for each selection round, wherein each library of DNA-containing compositions contains a DNA conjugate, and by each selection round, a DNA conjugate is selected based on its binding affinity to a target protein; one or more data processors; and a computing device communicatively connected to the data store and configured to receive the dataset, the computing device having a non-temporary computer-readable storage medium that, when executed on one or more data processors, causes one or more data processors to perform a method for normalizing multiple libraries of DNA-containing compositions. The method includes sorting libraries of DNA-containing compositions into bins using the dataset, wherein each bin contains a different subset of libraries of DNA-containing compositions determined to share a common number of PCR cycles for DNA amplification using the quantification information, and each subset of libraries of DNA-containing compositions in the same bin shares a different common number of PCR cycles than that of other bins of libraries. The system further includes a thermocycler configured to perform PCR on one of the vials simultaneously in the same run, with a corresponding common number of PCR cycles for the DNA-containing composition in the same vial, and to perform PCR on each library of DNA-containing composition in additional vials so that multiple libraries of DNA-containing composition are normalized.

[0008] In some embodiments, a method is provided for monitoring quantification information of multiple libraries of DNA-containing compositions to detect target binding. The method comprises receiving quantification information for each of multiple libraries of DNA-containing compositions for a first selection round, each library comprising a DNA conjugate, and the first selection round selecting the DNA conjugates based on their binding affinity to a target protein. The method further comprises generating a first window in a graphical user interface that displays the quantification information for each of the libraries for the first selection round. The method further comprises repeating the receiving and generating steps to generate additional windows over a plurality of subsequent selection rounds, each additional window displaying the quantification information for each of the libraries for each of the subsequent selection rounds, such that the quantification information for each of the DNA-containing compositions in the libraries for each round is monitored.

[0009] In some embodiments, a computer program product is provided that is tangibly embodied in a non-temporary machine-readable storage medium for monitoring quantification information of multiple libraries of DNA-containing compositions to detect target binding, the computer program product includes instructions configured to cause one or more data processors to perform a method for monitoring the quantification information of libraries and detecting target binding in a graphical user interface. The method includes, in a first step, receiving quantification information for each of multiple libraries of DNA-containing compositions for a first selection round, each of which libraries of DNA-containing compositions contains a DNA conjugate, and the first selection round selects a DNA conjugate based on its binding affinity to a target protein. The method includes, in a second step, displaying in a graphical user interface a first window containing the quantification information for each of the libraries of DNA-containing compositions after the first selection round, and repeating the first and second steps to generate additional windows over multiple subsequent selections, each of which generates an additional window that displays the quantification information for each of the libraries for each subsequent selection round, such that the quantification information for each of the libraries of each DNA-containing composition for each round is monitored.

[0010] In some embodiments, a system is provided for monitoring quantification information of multiple libraries of DNA-containing compositions to detect target binding. The system includes a data store configured to store a dataset containing the quantification information of each of the multiple libraries of DNA-containing compositions for each selected round, each of the libraries of DNA-containing compositions containing a DNA conjugate, and by each selected round, a DNA conjugate is selected based on its binding affinity to a target protein. The system further includes one or more data processors and a computing device, which is communicably connected to the data store and configured to receive datasets, and comprises a non-temporary computer-readable storage medium, which, when executed on one or more data processors, includes instructions causing one or more data processors to perform a method for displaying the quantification information of each of the libraries of DNA-containing compositions. The method includes generating a graphical user interface, which includes a window selected to display the quantification information of each of the libraries of DNA-containing compositions for any selected round selected to be displayed.

[0011] In one or more embodiments, a method is provided for normalizing a polymerase chain reaction (PCR) amplification process for multiple DNA-containing samples. For the multiple samples, cycle data for performing the PCR amplification process is identified. The cycle data includes the corresponding number of cycles for each sample in the multiple samples. The multiple samples are sorted into multiple bins based on the cycle data so as to reduce the variation in the number of cycles between bins in the multiple bins. A bin cycle count is assigned to each bin in the multiple bins. The bin cycle count is unique to each bin in the multiple bins. Bin identification information is generated. Using the multiple bins and the bin cycle counts for each bin in the multiple bins, an output for performing PCR amplification of the multiple samples is generated.

[0012] In some embodiments, a system is provided comprising one or more data processors and a non-temporary computer-readable storage medium containing instructions, wherein when an instruction is executed on one or more data processors, the non-temporary computer-readable storage medium causes one or more data processors to execute some or all of the methods disclosed herein.

[0013] In some embodiments, a computer program product is provided which is embodied in a non-temporary machine-readable storage medium and includes instructions configured to cause one or more data processors to perform some or all of the methods disclosed herein.

[0014] Some embodiments of this disclosure include a system comprising one or more data processors. In some embodiments, the system includes a non-temporary computer-readable storage medium comprising instructions, wherein when the instructions are executed on one or more data processors, the one or more data processors cause one or more data processors to execute some or all of one or more of the methods and / or some or all of one or more processes disclosed herein. Some embodiments of this disclosure include a computer program product tangibly embodied in a non-temporary machine-readable storage medium comprising instructions configured to cause one or more data processors to execute some or all of one or more of the methods and / or some or all of one or more processes disclosed herein.

[0015] The terms and expressions used are used as terms of explanation and not of limitation, and in the use of such terms and expressions, there is no intention to exclude any equivalents or portions thereof of the features shown and described, but it is recognized that various modifications are possible within the scope of the embodiments recited in the claims. Accordingly, while the embodiments claimed are specifically disclosed as embodiments and as any features, modifications and variations of the concepts disclosed herein may be used by those skilled in the art, and it is to be understood that such modifications and variations are considered to be within the scope of the appended claims.

Brief Description of the Drawings

[0016] The present disclosure is described in conjunction with the following accompanying drawings:

[0017] [Figure 1] Illustrative non-limiting embodiments of a general schematic workflow for screening multiple libraries of DNA-containing compositions for binding to a desired binding target according to various embodiments are shown.

[0018] [Figure 2] Illustrative non-limiting embodiments of a general schematic workflow for normalizing multiple libraries of DNA-containing compositions according to various embodiments are shown.

[0019] [Figure 3A-3C] Illustrative non-limiting embodiments of a workflow for normalizing multiple libraries of DNA-containing compositions to identify candidate DNA conjugates for binding affinity to a binding target according to various embodiments are shown.

[0020] [Figure 4] A flowchart showing a method for normalizing multiple libraries of DNA-containing compositions according to various embodiments.

[0021] [Figure 5]This flowchart shows a method for identifying candidate DNA conjugates based on their binding affinity to a binding target, according to various embodiments.

[0022] [Figure 6] This flowchart shows a method for normalizing a polymerase chain reaction (PCR) amplification process for multiple DNA-containing samples according to various embodiments.

[0023] [Figure 7] This flowchart shows a method for normalizing multiple samples containing DNA, as shown in various embodiments.

[0024] [Figure 8] This flowchart shows a non-limiting, exemplary method 800 for normalizing multiple samples containing DNA, as shown in various embodiments.

[0025] [Figure 9A] This table shows a first round of dynamic binning using an upper bias according to one or more embodiments.

[0026] [Figure 9B] This table shows a fourth round of dynamic binning using an upper bias, according to one or more embodiments.

[0027] [Figure 10] This is a table showing the first round of dynamic binning using a uniform distribution according to one or more embodiments.

[0028] [Figure 11A] This table shows the first round of dynamic binning with a bias on the sample for a number of cycles within a selected range of cycle counts, according to one or more embodiments.

[0029] [Figure 11B] This table shows the fourth round of dynamic binning bias on a sample for a number of cycles within a selected range of cycle counts, according to one or more embodiments.

[0030] [Figure 12] This is a schematic diagram of a non-limiting example of a system configured to normalize multiple libraries of DNA-containing compositions according to various embodiments.

[0031] [Figure 13] This document presents non-limiting exemplary embodiments of a workflow for monitoring the quantification information of each of multiple libraries in order to detect binding to a binding target in a graphical user interface, according to various embodiments.

[0032] [Figure 14] This flowchart shows a method for monitoring the quantification information of each of multiple libraries in order to detect binding to a binding target binding in a graphical user interface, according to various embodiments.

[0033] [Figure 15] This document describes a system and a graphical user interface for monitoring quantification information of multiple nucleotide-labeled peptide libraries in order to detect binding to a binding target, according to various embodiments, and provides non-limiting exemplary embodiments of the graphical user interface.

[0034] [Figure 16] The image depicts screenshots illustrating non-limiting exemplary embodiments of a graphical user interface for monitoring quantification information of a nucleotide-labeled peptide library to detect binding to a binding target, according to various embodiments.

[0035] [Figure 17]The image depicts screenshots illustrating non-limiting exemplary embodiments of a graphical user interface for monitoring quantification information of a nucleotide-labeled peptide library to detect binding to a binding target, according to various embodiments.

[0036] [Figure 18] The image depicts screenshots illustrating non-limiting exemplary embodiments of a graphical user interface for monitoring quantification information of a nucleotide-labeled peptide library to detect binding to a binding target, according to various embodiments.

[0037] [Figure 19] This is a non-limiting example block diagram showing a computer system configured to perform the methods provided herein, according to various embodiments.

[0038] In the accompanying drawings, similar components and / or features may have the same reference label. Furthermore, various components of the same type may be distinguished by following the reference label with a dash and a second label to distinguish similar components. Where only the first reference label is used herein, the description is applicable to any similar component having the same first reference label, regardless of the second reference label. [Modes for carrying out the invention]

[0039] Detailed description of the invention I. Overview This disclosure describes various exemplary embodiments of methods and systems for screening nucleotide-labeled peptide libraries for binding activity to one or more desired targets. However, this disclosure is not limited to these exemplary embodiments and applications, or the manner in which they operate or are described herein. Furthermore, figures may be simplified or partial, and the dimensions of elements in the figures may be exaggerated or disproportionate.

[0040] II. Exemplary Context and Explanation of Terminology It should be understood that the terms used herein are merely for the purpose of describing specific embodiments and are not intended to be limiting.

[0041] Unless otherwise defined, all technical terms, notations, and other scientific, technical, or specialized terms used herein are intended to have the same meaning as those generally understood by those skilled in the art in the field relating to the subject matter described in the claims. In some cases, terms that have a generally understood meaning are defined herein for clarity and / or easy reference, and the inclusion of such definitions herein should not necessarily be interpreted as representing a substantial difference from what is generally understood in the art. Generally, nomenclature and techniques used in relation to chemistry, biochemistry, molecular biology, pharmacology, and toxicology are described herein, are well known and commonly used in the art.

[0042] Where used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms similarly unless explicitly indicated otherwise in the context. Where used herein, the terms “and / or” should be understood to refer to and include any possible combination of one or more of the enumerated items relating to the subject. Where used herein, the terms “includes,” “including,” “comprises,” and / or “comprising” specify the presence of the described features, integers, steps, actions, elements, components, and / or units, but should be understood not to exclude the presence or addition of one or more other features, integers, steps, actions, elements, components, units, and / or groups thereof.

[0043] Throughout this disclosure, various aspects are presented in range form. It should be understood that range form is for convenience and brevity only and should not be interpreted as an inflexible limitation to this disclosure. Therefore, range descriptions should be considered to specifically disclose all possible sub-ranges and the individual numerical values ​​within those ranges. For example, where a range of values ​​is provided, it should be understood that each intermediate value between the upper and lower limits of that range, and any other described or intermediate values ​​within that described range, are included in this disclosure. These smaller upper and lower limits may independently be included in smaller ranges and are also included in this disclosure according to any specifically excluded limits within the described range. If a described range includes one or both limits, the range excluding either or both of those limits is also included in this disclosure. This applies regardless of the breadth of the range.

[0044] As used herein, the term “about” means to include the normal margin of error for each value that is readily known. References to “about” values ​​or parameters herein include (and are described) embodiments that apply to the value or parameter itself. For example, a statement referring to “about X” includes a statement of “X”. In some embodiments, “about” may mean ±15%, ±10%, ±5%, or ±1%, as understood by those skilled in the art.

[0045] Furthermore, wherever the terms “communicate with” or “communicately coupled with” or similar terms are used herein, one element may be capable of communicating directly, indirectly, or both, with another element by one or more wired communication links, one or more wireless communication links, one or more optical communication links, or a combination thereof. Furthermore, wherever a list of elements (e.g., elements a, b, c) is referred to, such a reference is intended to include any one of the enumerated elements, any combination of fewer elements than all of the enumerated elements, and / or all combinations of the enumerated elements.

[0046] As used herein, “substantially” means sufficient to function for the intended purpose. Therefore, the term “substantially” takes into account minor, slight variations from absolute or perfect conditions, dimensions, measurements, results, etc., which are expected by those skilled in the art but do not significantly affect the overall performance. When used in relation to numerical values, or parameters or characteristics that can be expressed numerically, “substantially” means within 10 percent.

[0047] As used herein, the term "ones" means two or more things.

[0048] As used herein, the term “multiple” or “group” may mean two, three, four, five, six, seven, eight, nine, ten, or more.

[0049] As used herein, the term “set” means one or more.

[0050] As used herein, the phrase “at least one of” can mean, when used with a list of items, that one or more different combinations of the enumerated items may be used, and that only one of the items in the list may be required. An item can be a specific object, thing, step, action, process, or category. In other words, “at least one of” means that any combination or any number of items from the list may be used, but not all of the items in the list may be required. For example, but are not limited to, “at least one of item A, item B, or item C” or “at least one of item A, item B, and item C” can mean item A; item A and item B; item B; item A, item B, and item C; item B and item C; or items A and C. In some cases, "at least one of item A, item B, or item C" or "at least one of item A, item B, and item C" could mean, but are not limited to, two of item A, one of item B, and ten of item C; four of item B and seven of item C; or several other suitable combinations.

[0051] "Individual," "subject," or "patient" may be a mammal. Mammals include, but are not limited to, domestic animals (e.g., cattle, sheep, cats, dogs, and horses), primates (e.g., humans and non-human primates, e.g., monkeys), rabbits, and rodents (e.g., mice and rats). In certain embodiments, the individual or subject is a human.

[0052] As used herein, “nucleic acid sequencing data,” “nucleic acid sequencing information,” “nucleic acid sequence,” “genome sequence,” “gene sequence,” or “fragment sequence,” or “nucleic acid sequencing read” may mean any information or data indicating the order of nucleotide bases (e.g., adenine, guanine, cytosine, and thymine / uracil) in a DNA or RNA molecule (e.g., whole genome, whole transcriptome, exome, oligonucleotide, polynucleotide, fragment, etc.). It should be understood that this instruction intends sequence information obtained using all available technologies, platforms, or techniques, including, but not limited to, capillary electrophoresis, microarrays, ligation-based systems, polymerase-based systems, hybridization-based systems, direct or indirect nucleotide identification systems, pyrosequencing, ion or pH-based detection systems, and electronic signature-based systems.

[0053] The terms "nucleotide," "polynucleotide," "nucleic acid," or "oligonucleotide" can refer to a linear polymer of nucleosides (including deoxyribonucleosides, ribonucleosides, or their analogues) joined by nucleoside bonds. Typically, a polynucleotide contains at least three nucleosides. Oligonucleotides usually range in size from a few monomer units, e.g., 3-4, to several hundred monomer units. Whenever a polynucleotide, such as an oligonucleotide, is represented by a sequence of letters such as "ATGCCTG," unless otherwise noted, the nucleotides are in the 5'→3' order from left to right, with "A" meaning deoxyadenosine, "C" meaning deoxycytidine, "G" meaning deoxyguanosine, and "T" meaning thymidine. The letters A, C, G, and T can be used to refer to the base itself, a nucleoside, or a nucleotide containing a base, as is standard in the art.

[0054] As used herein, the term “cell” may be used interchangeably with the term “living cell.” Non-limiting examples of living cells include eukaryotic cells, plant cells, animal cells, e.g., mammalian cells, reptile cells, avian cells, fish cells, etc.; prokaryotic cells, bacterial cells, fungal cells, protozoan cells, etc.; cells dissociated from tissues, e.g., muscle, cartilage, fat, skin, liver, lung, nerve tissue, etc.; immune cells, e.g., T cells, B cells, natural killer cells, macrophages, etc.; embryos (e.g., zygotes), oocytes, eggs, spermatids, hybridomas, cultured cells, cells from cell lines, cancer cells, infected cells, transfected and / or transformed cells, reporter cells, etc. Mammalian cells may be from, for example, humans, mice, rats, horses, goats, sheep, cattle, primates, etc.

[0055] As used herein, genome refers to the genetic material of a cell or organism, including mammals, such as humans. In humans, the genome includes all DNA, such as genes, non-coding DNA, and mitochondrial DNA. The human genome typically contains 23 pairs of linear chromosomes: 22 pairs of autosomes + sex-determining X and Y chromosomes. The 23 pairs of chromosomes contain one copy from each parent. The DNA that makes up the chromosomes is called chromosomal DNA and is located in the nucleus of human cells (nuclear DNA). Mitochondrial DNA is located in mitochondria as a circular chromosome, is inherited only from the mother, and is often referred to as the mitochondrial genome in contrast to the nuclear genome, which is the DNA located in the nucleus.

[0056] The term "sequencing" can refer to any technique known in the art that enables the identification of a sequence of nucleotides of at least a portion of a nucleic acid. Non-exclusive exemplary sequencing techniques include RNA-seq (also known as whole transcriptome sequencing), Illumina® sequencing, direct sequencing, random shotgun sequencing, Sanger dideoxytermination sequencing, whole genome sequencing, massively parallel signature sequencing (MPSS), hybridization sequencing, pyrosequencing, capillary electrophoresis, gel electrophoresis, duplex sequencing, cycle sequencing, and single-nucleotide extension sequencing. This includes single-phase sequencing, high-throughput sequencing, ultra-parallel signature sequencing, emulsion PCR, reversible dye-terminator sequencing, paired-end sequencing, near-term sequencing, exonuclease sequencing, ligation sequencing, short-read sequencing, single-molecule sequencing, synthesis sequencing, real-time sequencing, reverse-terminator sequencing, nanopore sequencing, 454 sequencing, Solexa Genome Analyzer sequencing, SOLiD® sequencing, MS-PET sequencing, mass spectrometry, and any combination thereof.

[0057] The term "RNA-seq (RNA sequencing)" can refer to any step or technique that uses sequencing, such as next-generation sequencing (NGS), to determine the presence, quantity, or sequence of RNA in a biological sample. RNA-seq can analyze the transcriptome of gene expression patterns encoded within RNA.

[0058] The term "next-generation sequencing" (NGS) can refer to sequencing technologies that have increased throughput compared to traditional Sanger and capillary electrophoresis-based methods, such as the ability to generate hundreds of thousands of relatively small sequence reads at once. Some examples of next-generation sequencing technologies, though not limited to these, include synthesis sequencing, ligation sequencing, and hybridization sequencing. More specifically, Illumina's MISEQ, HISEQ, and NEXTSEQ systems, as well as Life Technologies Corp.'s Personal Genome Machine (PGM) and SOLiD sequencing systems, provide massively parallel sequencing of whole or targeted genomes. The SOLiD system and related workflows, protocols, chemistry, etc., are described in detail in PCT Publication WO2006 / 084132, international filing date February 1, 2006, entitled "Reagents, Methods, and Libraries for Bead-Based Sequencing," U.S. Patent Application No. 12 / 873,190, filed August 31, 2010, entitled "Low-Volume Sequencing System and Method of Use," and U.S. Patent Application No. 12 / 873,132, filed August 31, 2010, entitled "Fast-Indexing Filter Wheel and Method of Use," each of these applications in whole being incorporated herein by reference.

[0059] The term "in vitro display" can refer to a system that displays a phenotype together with a genotype by linking the phenotype and the genotype encoding the sequence of the phenotype via non-covalent or covalent bonds. Non-exclusive examples of in vitro displays include mRNA displays, PD displays, STABLE (non-covalent DNA displays), microbead / droplet displays, covalent DNA displays, phage displays, and ribosome displays. In vitro displays can enable the enrichment and amplification (selection) of active species using a replication system reconstituted in a test tube. A major advantage of in vitro display systems is that they allow searching through libraries containing a wide variety of standard and non-standard peptides or combinations thereof, avoiding their use as culture media for prokaryotes and eukaryotes, and enabling the selection of highly active physiological substances (e.g., peptides). In vitro displays can enable searching through libraries with a diversity of 10^13. In some embodiments, mRNA displays are described as examples, but in vitro displays can be used instead.

[0060] The terms "RNA display" or "mRNA display" can refer to an in vitro technique in which expressed proteins or peptides are bound to their encoding nucleic acids by covalent or noncovalent interactions to form an "mRNA / DNA-peptide conjugate" molecule. The protein or peptide component of the mRNA / DNA-peptide conjugate is selected as a candidate for binding to a desired binding target, and the identity of the candidate protein or peptide is determined by sequencing of the attached encoding mRNA component.

[0061] The term "flexizyme" can refer to artificial RNA catalysts developed as aminoacyl-tRNA synthetases. Flexizymes are also known by names such as dinitrobenzyl flexizyme (dFx), enhanced flexizyme (eFx), and aminoflexizyme (aFx). Flexizymes can catalyze the aminoacylation of adenosine at the 3' end using a weakly activated amino acid as a substrate by recognizing the carbonyl group to which the amino acid reacts, the aromatic ring in the side chain or leaving group of the amino acid, or the ACC-3' sequence at the 3' end of the linker.

[0062] The terms “macrocyclic peptide” or “macrocyclic molecule” can refer to a macrocyclic structure of 4, 5, 6, 7, 8, 9, 10, 11, 12, or more amino acids, or a peptide containing any intermediate range or value derived therefrom. As used herein, “macrocyclic structure” refers to a closed ring structure formed on a linear peptide. The ring structure can be formed by directly or via a linker joining two amino acids separated by at least two amino acid residues. A macrocyclic peptide or macrocyclic molecule may contain 1, 2, 3, 4, 5, or more rings.

[0063] The term "Ct (cycle threshold)" can refer to the number of cycles required for a fluorescence signal to exceed a threshold (e.g., exceed the background level). The Ct level is inversely proportional to the amount of candidate nucleic acid in the sample (i.e., a lower Ct level indicates a higher amount of candidate nucleic acid in the sample).

[0064] As used herein, the term “selection” can refer to substantially separating a molecule from other molecules in a population. As used herein, the “selection” step can provide a concentration of the desired molecule at least 2 times, preferably 30 times, more preferably 100 times, and most preferably 1000 times, compared to the undesirable molecules in the population after the selection step. As shown herein, the selection step may be repeated any number of times, and / or different types of selection steps may be combined in a given manner.

[0065] Discovery of target binding candidates

[0066] The various methods and system embodiments described herein enable improved multiplexing methods for detecting peptide candidates in selection for binding to a desired target. For example, RNA display methods can be used here. RNA display generally involves the expression of a protein or peptide, and the expressed protein or peptide is covalently or tightly noncovalently bound to their encoding mRNA to form an RNA / protein fusion molecule. The protein or peptide component of the RNA / protein fusion can be selected for binding to a desired target, and the identity of the protein or peptide can be determined by sequencing of the attached encoding mRNA component.

[0067] Figure 1 shows a non-limiting exemplary embodiment of a general schematic workflow for screening multiple libraries of DNA-containing compositions for binding to a desired target, according to various embodiments.

[0068] Workflow 100 can include, at step 110, obtaining a starting nucleic acid library (e.g., wells in a multi-well plate), and translating the starting nucleic acid library into a peptide library encoded by their corresponding nucleic acids to generate a library of nucleotide-containing conjugates. The starting nucleic acid library can include at least, at most, or about 10, 100, 10 3 、10 4 、10 5 、10 6 、10 7 、10 8 、10 9 、10 10 、10 11 、10 12 、10 13 、10 14 、10 15 、10 16 、10 17 、10 18 、10 19 、or 10 20 (or any intermediate number in the range derived therefrom) conjugates. The starting nucleic acid library can be selected by design preference. For example, the starting nucleic acid library can be selected to have a low abundance of conjugates, and can include about 10, 100, or 10 3 (or any intermediate number in the range derived therefrom) conjugates. The starting nucleic acid library can be selected to have a medium abundance of conjugates, and can include about 10 4 、10 5 、10 6 、10 7 、10 8 [[ID=四十八]]、or 10 9 (or any intermediate number in the range derived therefrom) conjugates. The starting nucleic acid library can be selected to have a high abundance of conjugates, and can include about 10 10 、10 11 、10 12 、10 13 、or 10 14 (or any intermediate number in the range derived therefrom) conjugates.

[0069] According to some embodiments, workflow 100 translates RNA into peptides by adding an in vitro translation mixture. For example, the in vitro translation mixture includes a ribozyme for charging tRNA with standard amino acids, a ribozyme for charging tRNA with non-standard amino acids, or a combination thereof, such as an aminoacyl-tRNA synthetase (also called aaRS or ARS, or tRNA ligase) for adding standard amino acids, a flexizyme for adding non-standard amino acids, or a combination thereof. During the in vitro translation reaction, mRNA molecules become covalently bound to their peptide products via a peptide acceptor (e.g., puromycin) fused to their 3' end. In additional and alternative embodiments, the nucleotide-containing conjugate may include a linker that binds mRNA to the corresponding peptide.

[0070] Peptides can be linear, stapled, cyclic, or a combination thereof. In certain embodiments, cyclic peptides are macrocyclic peptides. Macrocyclic peptides can have one, two, three, or more rings. Macrocyclic peptides can include monocyclic peptides, bicyclic peptides, tetracyclic peptides, or combinations thereof. Libraries of nucleotide-containing conjugates can include RNA conjugated to peptides as mRNA-represented peptides.

[0071] Workflow 100 may include in vitro reverse transcription of a nucleotide-containing conjugate and desalting of the in vitro reverse transcript product in step 120. For example, workflow 100 generates a DNA-mRNA-peptide conjugate by adding a reverse transcription mixture to an mRNA-peptide conjugate. Workflow 100 transfers the resulting DNA-mRNA-peptide conjugate to a desalting column to remove salts and other small molecules, resulting in the generation of a desalted library. The desalted library can be put into a selection round to detect target-binding candidate peptides.

[0072] Workflow 100 may include the selection of target binding candidates from an input library in step 130. The input library may include nucleotide-containing conjugates after in vitro reverse transcription and desalting. Each selection may include positive selection of candidate conjugates that bind to the desired target molecule, negative selection of libraries that bind to the support without the desired target molecule, or a combination thereof.

[0073] For example, the target molecule is bound to a solid support such as agarose beads. The target molecule is directly bound to a solid substrate. In another embodiment, the target molecule is first modified, e.g., biotinylated, and then the modified target molecule is bound to a solid substrate such as beads via modification. Non-limiting examples of solid supports include streptavidin (SA)-M280, neutraavidin-M280, SA-M270, NA-M270, SA-MyOne, NA-MyOne, SA-agarose, and NA-agarose. In additional and alternative embodiments, the solid support further includes magnetic beads, e.g., Dynabeads®. Such magnetic beads allow for the separation of the solid support and any bound nucleotide-containing conjugate from the assay mixture using a magnet.

[0074] In a negative selection, the input library can be completely mixed with empty beads. Any bead-binding members can be removed from the input library. In some embodiments, the first selection round skips the negative selection.

[0075] In positive selection, the input library can be incubated with beads that capture one or more target molecules bound to a solid support, for example, tags displayed on one or more target molecules. For example, a pull-down assay can be performed to wash away unbound nucleotide-containing conjugates and elute candidate binders from beads bound to target proteins, i.e., positive beads.

[0076] Prior to amplification of nucleic acid components, the target-binding nucleotide-containing conjugate can be eluted from the solid support. Any available elution method is intended. Alternatively or additionally, the target-binding nucleotide-containing conjugate can be eluted at high temperatures, e.g., by boiling. Alternatively or additionally, the target-binding nucleotide-containing conjugate is eluted using alkaline conditions, e.g., pH of about 8.0, 8.5, 9.0, 9.5, 10.0, or any intermediate range or value derived therefrom. In additional and alternative embodiments, the target-binding nucleotide-containing conjugate is eluted using acidic conditions, e.g., pH of about 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, or any intermediate range or value derived therefrom.

[0077] For example, positive beads can be transferred to a PCR plate, sealed, and boiled. The positive beads can then be cooled and transferred to a magnetic plate. The supernatant from the magnetic plate can be removed and transferred to a new PCR plate for further analysis of the nucleotide-containing conjugate.

[0078] Workflow 100 may include amplification of selected target binding candidates from the input library in step 140. For example, the selected target binding candidate is a DNA-RNA-peptide conjugate. Workflow 100 amplifies the DNA in the selected target binding candidate by PCR and uses the amplified product as input for the next selection round or analyzes it by sequencing.

[0079] Workflow 100 quantifies and normalizes the selected target binding candidates for DNA amplification in step 140. Workflow 100 measures the DNA concentration in the selected target binding candidates, for example, by quantitative PCR (qPCR). Workflow 100 collects and analyzes the qPCR data for normalization to ensure the appropriate DNA concentration to be used in the next selection round. For example, Workflow 100 can collect Ct values ​​for each selected target binding candidate by qPCR and use this to determine the appropriate PCR cycle for amplifying each selected target binding candidate using PCR.

[0080] In additional and alternative embodiments, RNA in the selected target-binding candidate can be amplified to produce more RNA. Any available method of RNA replication is attempted, for example, using RNA replicase enzymes. In another embodiment, RNA in the eluted target-binding candidate can be transcribed into cDNA before being amplified by PCR.

[0081] Step 140 may include quantification and normalization of selected target binding candidates for amplification, which can be further illustrated in Figures 2-8 as additional and alternative normalization workflows. Visualization of the quantification and normalization results can be described in more detail in Figures 9-14 as a visualization workflow.

[0082] Workflow 100 may include repeated selection of target binding candidates from the input library in step 150. The PCR amplification pool can be subjected to one or more selections, e.g., two, three, four, five, six, seven, eight, nine, ten, or more, to enrich the highest affinity target binding candidates. The selection and amplification process is repeated until the library is dominated by candidates with the desired characteristics. The required number of iterations depends on the diversity of the starting library and the degree of enrichment achieved in the selection step.

[0083] In step 150, the amplified DNA nucleotides are transcribed into mRNA and then translated into peptides to produce an additional library of nucleotide-containing conjugates for another round selection in steps 110, 120, 130, and 140.

[0084] Additionally or alternatively, nucleic acid sequences can be amplified under conditions that introduce mutations into the amplified DNA, thereby introducing further diversity into the selected nucleic acid sequences. This mutation pool of DNA molecules can then be subjected to further rounds of selection.

[0085] Additionally or alternatively, the PCR amplification pool of nucleic acids can be sequenced using any available sequencing method to determine the nucleic acid sequences, e.g., next-generation sequencing (NGS), of all selected nucleotide-containing conjugates. The sequence identity of the selected nucleotide-containing conjugates can then be further used to verify the target binding affinity of the selected nucleotide sequences.

[0086] III. Normalization of nucleotide-containing libraries The various methods and system embodiments described herein enable improved, reliable quantitative evaluation of target binding selection using in vitro displays. In particular, the embodiments described herein allow tracking of the progress and success or failure of simulated selection from one round to another. The methods and systems described herein are robust, reproducible, and can be used to normalize nucleotide-containing libraries for target binding selection.

[0087] Normalization helps minimize variations in the DNA introduced into subsequent rounds between individual DNA-containing compositions, e.g., per-well variations. The input DNA can be used to generate a library of potential binders, and the DNA concentration of the generated library can be measured and recorded as part of the experiment in each selection round. Normalization helps compare the progress and success / failure of simultaneous selection in each selection round.

[0088] One non-limiting advantage is that the normalization methods and systems used herein may allow tracking the progress of several rounds of selection with any possible combination of DNA concentrations as input, while avoiding the need for manual intervention.

[0089] III.A. Normalization Workflow To illustrate a non-limiting, exemplary process for normalizing multiple libraries of DNA-containing compositions according to various embodiments, a general schematic workflow 200 is provided in Figure 2. Such normalization can handle any possible combination of DNA concentrations in different libraries across different experiments without intervention. For example, different experiments may be different selection rounds for target binding candidates, e.g., in vitro display selection. The workflow may include various combinations of features, more or less than those shown in Figure 2. Thus, Figure 2 merely illustrates an example of a possible workflow. Workflow 200 can be implemented, for example, using system 1200 or a similar system described with respect to Figure 12.

[0090] Workflow 200 may include initiating a selection round in step 210 to detect binding to a desired target molecule. The selection round can be initiated by translation, reverse transcription, desalting, and selection to detect binding to the target molecule, as well as quantification of the selected nucleotide-containing composition by, for example, qPCR.

[0091] Workflow 200 may include, in step 220, the collection of qPCR data from selected rounds to detect target binding candidates. Workflow 200 performs qPCR by transferring small samples of each selected nucleotide-containing conjugate to a designated space in a container, e.g., a 384-well plate. In various embodiments, qPCR is used to measure the concentration of candidate DNA in a given sample through repeated cycles of sequence-specific DNA amplification followed by DNA concentration measurement. During subsequent cycles, the amount of each candidate DNA approximately doubles during the exponential phase of amplification. The cycle in which the observed DNA concentration first exceeds a certain threshold is generally called the threshold cycle (Ct). These Ct values ​​represent a quantitative assessment of DNA concentration and are often treated as raw data for subsequent analysis.

[0092] In step 220, qPCR data acquisition may include receiving qPCR data from a qPCR machine, performing data analysis, and exporting the data to a computer. In various embodiments, the most recent qPCR data can be transferred to and read from a database. The Ct values ​​for each sample in one selected round can be extracted from the qPCR data and simultaneously visualized, as described in more detail in Figures 9 to 14.

[0093] Workflow 200 may include sorting multiple DNA-containing compositions in step 230. For example, multiple DNA-containing compositions may be sorted into bins based on their respective quantification information, such as the Ct value of each sample (i.e., DNA-containing composition) or the number of PCR cycles for each sample determined based on the Ct value. The sorting can be automated.

[0094] For example, each bin is determined to normalize the concentration of each DNA-containing composition by sharing a common number of PCR cycles for subsequent amplification. Each bin groups DNA-containing compositions of similar concentrations, for example, by having the same Ct value within a certain range or the same number of PCR cycles within a certain range. The same Ct value within a certain range can refer to a Ct value within an integer value of 1, 2, 3, 4, or 5, or any range or value derived therefrom. The same number of PCR cycles within a certain range can refer to a PCR cycle number within an integer value of 1, 2, 3, 4, or 5, or any range or value derived therefrom.

[0095] For example, all individual wells having Ct values ​​within 3Ct values ​​(e.g., Ct values ​​of 9, 10, and 11) may be combined into a single vial, and the same number of PCR cycles (e.g., 10 PCR cycles) may be applied to the entire vial for subsequent amplification. Each vial can be assigned a corresponding sample with a common PCR cycle assigned based on an identification label such as a barcode and quantification information such as Ct from a qPCR quantitative assay. For example, each PCR cycle in each well or the assigned common PCR cycle may be based on a predetermined formula, for example, each PCR cycle in each well or the assigned common PCR cycle may be the Ct of each well rounded to the nearest integer, or it may be the Ct of each well obtained by adding or subtracting an integer from the rounded integer. If some wells have similar Ct values, some wells may be assigned a common PCR cycle number, or each may have a similar PCR cycle number based on similar Ct values, and the common PCR cycle number may be assigned based on a range of these similar Ct values ​​or similar PCR cycle numbers. In some embodiments, the number of PCR cycles in each well can be equivalent, or adjusted to be equivalent to a common number of PCR cycles shared by several wells having similar Ct values.

[0096] These assignments can be organized into a worklist and transferred to a liquid handler. The liquid handler can run the worklist by selecting samples and transferring the selected samples from the source plate to a plate for PCR amplification using the assigned common PCR cycle. After PCR amplification, the liquid handler can return the thus amplified samples to their original wells in the source plate.

[0097] As shown in Table 1, the number of PCR cycles for future amplification can be determined using the determined qPCR Ct value (Min and Max refer to the minimum and maximum qPCR Ct values ​​in each bin). In Table 1, all samples are sorted into bins according to the predetermined qPCR Ct value, and each bin contains samples that have been determined to share a common number of PCR cycles for future amplification. For example, if a sample has a qPCR Ct of 13, it will be in the third bin and will be allocated to have 15 PCR cycles for subsequent amplification, as shown in Table 1 below ("Number of PCR Cycles").

[0098] As shown in Table 1, any sample with 0 to 9 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 9 cycles of PCR for subsequent amplification. Any sample with 10 to 12 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 12 cycles of PCR for subsequent amplification. Any sample with 13 to 15 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 15 cycles of PCR for subsequent amplification. Any sample with 16 to 18 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 18 cycles of PCR for subsequent amplification. Any sample with 19 to 20 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 20 cycles of PCR for subsequent amplification. Any sample with 21 to 23 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 23 cycles of PCR for subsequent amplification. Any sample with 24 to 26 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 26 cycles of PCR for subsequent amplification. Any sample with 27 to 40 qPCR Ct can be assigned to a bin where all samples in the bin are allocated 28 cycles of PCR for subsequent amplification. [Table 1]

[0099] In additional and alternative embodiments, sorting may include identifying the PCR cycle numerical range for all samples and sorting all samples into an integer number of bottles using the PCR cycle numerical range such that each bottle has an equal number of samples or an equal number of samples within a certain range. An integer number of bottles may be at least, or at most, or about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more. An equal number of samples within a range may mean that each bottle has an equal number of samples, or that the difference in sample size between each bottle does not exceed 1, 2, 3, 4, 5, 6, 7, or 8. In a particular embodiment, the integer number of bottles may be 8 bottles, each of which has an equal number of samples. Thus, in one or more embodiments, samples may be uniformly sorted into a selected number N bottles.

[0100] In each selection round of target binding candidates, the size of each bin can be fixed or dynamic. In some embodiments, the size of each bin can be fixed across selection rounds. In other embodiments, the size of each bin can vary depending on how broadly the range of PCR cycle numbers changes. For example, in earlier rounds, larger bin sizes for each of the integer bins and PCR plates can be automatically generated based on a wider range of PCR cycle numbers. However, in later selection rounds, as the data begins to converge, each of the integer bins and PCR plates can have a much smaller bin size, i.e., a smaller size of sample within each bin, based on a narrower range of PCR cycle numbers. In certain embodiments, the integer is 8. Spreading the sample across a number of bins, e.g., 8 bins, achieves good accuracy normalization.

[0101] Workflow 200 may include the generation of worklists, for example, a forward worklist and a reverse worklist, in step 240. Workflow 200 assigns two worklists to each bin. The forward worklist has instructions for one bin's sample to be selected into the PCR plate from the original wells of the source plate in order to perform PCR based on a common number of PCR cycles assigned to the bin. For example, the source plate may have individual wells A5, B5, and D5 that have the same Ct value and are sorted into the same bin (for example, A5, B5, and D5 refer to rows A, B, and D and column 5 of a 96-well plate). The forward worklist can be generated to select the samples from the same bin, i.e., wells A5, B5, and D5, into the same PCR plate for subsequent PCR amplification. In the reverse worklist, the sample can be returned to the original wells of the source plate after PCR amplification.

[0102] Workflow 200 may include the execution of a forward worklist in step 250. For example, workflow 200 may acquire a PCR plate and assign an arbitrary barcode to the PCR plate. A forward worklist may be executed for a liquid handler to transfer the sample from the original well in the source plate to the corresponding PCR plate. Each bin that shares a common number of PCR cycles for amplification may be assigned to a corresponding PCR plate having a specific barcode, and the assignments may be stored in a database. Thus, in one or more embodiments, a single PCR plate may only receive samples that share a common number of PCR cycles for amplification.

[0103] Workflow 200 may include, in step 260, creating and sending instructions to a thermocycler to perform PCR amplification according to a forward worklist. The instructions are based on a common number of PCR cycles for each bin. The instructions can match the barcode of each PCR plate against a database and inform the PCR thermocycler which barcodes are ready for PCR. For example, when a plate of samples in a single bin is transferred to a corresponding PCR plate, workflow 200 can move the corresponding PCR plate to the PCR thermocycler and update a specified file with the barcode of the PCR plate. Since the database has a file containing a list of barcodes that match the corresponding bins, the PCR thermocycler can access the database, read the file, see which barcodes were loaded onto the PCR plate in the thermocycler, compare it with the database to identify matching bins with the corresponding Ct number from quantification and the common number of PCR cycles allocated for amplification. The instructions can also update the thermocycler to perform how many PCR cycles (i.e., the common number of cycles allocated for amplification) for the corresponding sample, according to the match between the barcode of the PCR plate and the sample bin.

[0104] Workflow 200 may include, in step 270, running a reverse worklist to return the processed sample to the source plate. After PCR, a reverse worklist can be run to return the processed sample, such as the amplified sample in the PCR plate, to the original wells in the source plate so that the amplified DNA in each original well is generated.

[0105] For example, workflow 200 can first receive worklists from the database and execute worklists 1 and 2 to transfer samples from the original wells to the corresponding PCR plates. Workflow 200 may have PCR plates transferred to a PCR thermocycler. Workflow 200 can notify the PCR thermocycler that barcodes 1 and 2 and their corresponding PCR plates are ready for PCR amplification. The PCR thermocycler can check how many PCR cycles of the samples in the first and second vials match those in PCR plates 1 and 2, and then execute the corresponding PCR cycles to amplify the samples in the first and second vials. Worklists 1 and 2 can be executed in reverse to return the amplified samples to the original wells of the source plate. Workflow 200 can then check if worklists for barcodes 3 and 4 exist, and if so, repeat the above steps for worklists 1 and 2. Workflow 200 can receive and execute worklists one, two, three, four, five, six, or more at a time, depending on how many different PCR reactions can be performed simultaneously.

[0106] Workflow 200 may include ending this round at step 280 and repeating the selection process for another round. Subsequent selection rounds may include the same workflow 200, including steps 210, 220, 230, 240, 250, 260, and 270.

[0107] Figures 3A–3C are graphs illustrating non-limiting exemplary embodiments of the normalization workflow 300. The normalization workflow 300 can be repeated at the end of each selection round (except the last selection round) after positive selection for binding to a desired target or negative selection for removing libraries that bind to the support without a desired target molecule, so that libraries with more DNA after selection are determined to undergo more PCR cycles for amplification to normalize the DNA concentration of all libraries.

[0108] In Figure 3A, the normalization workflow 300 includes converting the DNA-containing input library 310 into a library 320 having mRNA display and target binding results after target binding selection, as shown in Figure 1. The amount of DNA in each well can be visualized simultaneously, for example, in a heatmap, as different grades of shading, different colors, different patterns, or a combination thereof.

[0109] In Figure 3B, the DNA concentration in library 320 containing target binding results is measured by qPCR and normalized across different wells. In step 330 of the normalization workflow 300, after qPCR, the number of PCR cycles for each library 320 (e.g., each well in a multi-well plate) in Figure 3A can be calculated as a Ct value and exported to match the corresponding well. For example, a pre-defined criterion can be used to assign the number of PCR cycles for any sample based on adding or subtracting a predetermined number from the Ct value.

[0110] In step 340 of the normalization workflow 300, wells having the same Ct value within a range from PCR quantification, or the same number of PCR cycles for future amplification within a certain range, can be grouped into five bins. For example, the first bin has wells A6, B5, and D5, all with 9 qPCR Cts. The second bin has wells E5, F5, G5, and H5, all with 12 qPCR Cts. The third bin has several wells with similar qPCR Cts of 15 and 18. The fourth bin has several wells with similar qPCR Cts of 18, 20, and 23. The fifth bin has several wells with qPCR Cts of 23 and 26. Each bin group is determined to normalize the DNA amount across all libraries in the same bin and across different bins by conjugating with the same Ct value within a certain range and sharing common PCR cycles for subsequent amplification.

[0111] In 350, a forward worklist instructing to select a vial of sample from the original well of the source plate to transfer to the corresponding PCR plate, and a reverse worklist instructing to return the sample to the original well of the source plate, can be generated, for example, by a database.

[0112] In step 360 of the normalization workflow 300, each bin can be assigned to a corresponding PCR plate with an assigned barcode. For example, a bin with the lowest Ct range or value can be assigned barcode 1. Worklists, such as forward and reverse worklists, can be generated using the barcodes, each containing a list of samples in its bin. This process can then be repeated for all bins. A bin with the second lowest Ct range or value may have barcode 2, a bin with the third lowest Ct range or value may have barcode 3, and so on, until a bin with the highest Ct range or value is assigned barcode N, which is the total number of bins. The number of bins can be at least, approximately, or at most 5, 6, 7, 8, 9, 10, or any range or value derived therefrom, depending on the qPCR data. This can be a dynamic process involving barcode assignment and bin assignment to corresponding barcodes.

[0113] After all bins are assigned a PCR plate barcode and all worklists are generated, the worklists can be stored for a device such as a liquid handler to access the worklists and instruct the device to process the PCR plates for amplification according to the worklists. For example, bins can be processed together with a similar common number of PCR cycles for amplification. A first bin can have a common number of 9 PCR cycles assigned for amplification. A second bin can have a common number of 12 PCR cycles assigned for amplification. A third bin can have a common number of 15 PCR cycles assigned for amplification. A fourth bin can have a common number of 18 PCR cycles assigned for amplification. A fifth bin can have a common number of 18 PCR cycles assigned for amplification. Processing can be carried out from a low PCR cycle count to a high PCR cycle count; for example, PCR plates with barcodes 1 and 2 can be processed together, PCR plates with barcodes 3 and 4 can be processed together, and then a PCR plate with barcode 5 can be processed.

[0114] One non-limiting advantage of this disclosure is that, since a sample in a vial is amplified to have a similar amount of DNA after amplification as a sample in a vial with a high number of PCR cycles, well-to-well variability can be minimized.

[0115] In 370, the forward worklist can be performed by a liquid handler to transfer the samples in each vial from their original wells in the source plate to the corresponding PCR plate assigned to them, and to perform PCR according to a common number of PCR cycles assigned to each vial. After PCR, the reverse worklist can be performed by a liquid handler to return the processed samples containing amplified DNA to their respective original wells in the source plate.

[0116] In Figure 3C, the workflow 300 continues to generate a normalized library 380 that can have the same DNA concentration within a range across all wells. The normalized library 380 can be used as input DNA 390 in a subsequent selection round or for sequencing analysis.

[0117] III.B. Exemplary Normalization Methods A method is provided for normalizing multiple libraries of DNA-containing compositions. This method can be implemented via computer software or hardware. It can also be implemented on a computing device / system that includes a combination of engines for normalizing multiple libraries of DNA-containing compositions. In various embodiments, the computing device / system can be communicatively connected to one or more of the following: a data source, a sample analyzer (e.g., a genome sequencing analyzer), and a display device, either via direct connection or an internet connection.

[0118] III.B.1. Normalization for PCR Referring here to Figure 4, a flowchart is disclosed showing a non-limiting exemplary method 400 for normalization relating to various embodiments. Method 400 may include, in step 402, receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round. For example, each library contains a DNA conjugate, and the DNA conjugate is selected by the first selection round based on its binding affinity to a target protein. For example, the DNA conjugate includes a peptide, such as a macrocyclic molecule. The DNA conjugate may include peptides such as linear or cyclic peptides, or combinations thereof. The cyclic peptide may include a macrocyclic molecule. The macrocyclic molecule may have one, two, three or more rings, or combinations thereof. For example, the quantification information may include the cycle threshold (Ct) of quantitative PCR (qPCR).

[0119] Method 400 may include, in step 404, determining a polymerase chain reaction ("PCR") cycle count specific to each library using quantified information, and determining that the DNA-containing composition of each library is such that it produces a relevant preset amount of DNA after PCR with the corresponding number of PCR cycles. Wells with less DNA have a higher Ct, as determined by qPCR, and require more PCR cycles in amplification to normalize the difference between wells with less DNA and wells with more DNA.

[0120] Method 400 may include, in step 406, sorting libraries of DNA-containing compositions into bins using the corresponding number of PCR cycles determined in step 404. Each bin may contain different subsets of libraries of DNA-containing compositions that are determined to share a common number of PCR cycles for DNA amplification. Libraries in each subset of libraries of DNA-containing compositions in the same bin share a different common number of PCR cycles than the other bins of libraries. In this way, each bin can be assigned a unique number of PCR cycles. For example, at least one of the bins may contain two or more libraries of DNA-containing compositions, e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or more libraries, so that libraries with similar numbers of PCR cycles can be grouped into the same bin and assigned a common number of PCR cycles for future amplification.

[0121] In some embodiments, each of the DNA-containing compositions in any one of the bins is determined to produce the same or similar amount of amplified DNA after PCR is performed with a corresponding number of PCR cycles for the same bin. Thus, the method can normalize the composition of each bin by determining a different number of PCR cycles for each different bin so that the same or similar amount of DNA is present across each bin and across different bins. In some embodiments, the same or similar amounts of DNA may differ by only a fraction of a certain range, e.g., 25%, 20%, 15%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, or less than 1%. The predetermined range can be determined based on binning of Ct values, for example, the range is higher if there is more variance in the Ct values ​​of all conjugates in the bin.

[0122] Method 400 may further include correlating each vial with a corresponding PCR plate in order to perform PCR amplification on the DNA-containing composition in the same vial with a corresponding common number of PCR cycles on the corresponding PCR plate.

[0123] Method 400 may include instructing the thermocycler in step 408 to perform PCR simultaneously on one of the vials in the same run with a common number of PCR cycles corresponding to a subset of the library of DNA-containing compositions in the same vial. Method 400 may further include instructing the thermocycler to perform PCR simultaneously on each of the DNA-containing compositions in an additional vial with an additional corresponding common number of PCR cycles to produce additional amplified DNA.

[0124] Method 400 may further include generating a forward worklist containing a first list corresponding to each DNA-containing composition in each bin that is transferred from its original position on the source plate to the PCR plate, for performing PCR on the same bin of DNA-containing compositions with a corresponding common number of PCR cycles to produce an amplified DNA-containing composition. Method 400 may further include generating a reverse worklist containing a second list corresponding to the amplified DNA-containing compositions that are returned from the PCR plate to their original positions (wells) on the source plate.

[0125] Method 400 may include instructing a thermocycler in step 410 to perform PCR on each of the additional vials with a corresponding common number of PCR cycles so that multiple libraries of DNA-containing compositions are normalized to minimize variability between samples. The normalized libraries can then initiate the next selection round, which may include in vitro translation, reverse transcription, incubation with a desired target or empty beads, washing for non-binding agents, elution of putative binding agents, and amplification of candidate binding agents by the normalization described herein.

[0126] III.B.2. Normalization for identifying candidate DNA conjugates based on binding affinity to target proteins. Referring here to Figure 5, a flowchart is disclosed showing a non-limiting, exemplary method 500 for normalization in target binding selection according to various embodiments. This method can be used to identify candidate DNA conjugates for binding affinity to a target protein. The method may include, in step 502, receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each library containing DNA conjugates, and the first selection round selects DNA conjugates based on their binding affinity to a target protein.

[0127] In step 504, the method may include determining a polymerase chain reaction ("PCR") cycle count specific to each library using quantified information, and determining that the DNA-containing composition of each library produces a relevant predetermined amount of DNA after PCR is performed for the corresponding number of PCR cycles.

[0128] The method may include, in step 506, sorting libraries of DNA-containing compositions into bins, each bin containing a different subset of libraries of DNA-containing compositions determined to share a common number of PCR cycles for DNA amplification, and each subset of libraries of DNA-containing compositions in the same bin sharing a different common number of PCR cycles than that of the other bins of the library. In some embodiments, at least one of the bins contains two or more libraries of DNA-containing compositions, e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or more libraries. In some embodiments, each of the libraries of DNA-containing compositions in any one of the bins is determined to produce substantially the same amount of amplified DNA after PCR is performed on the same bin with the corresponding number of PCR cycles. Thus, the method can normalize the composition of each bin by determining a different number of PCR cycles for each bin so that the same or similar amounts of DNA are present across each bin and across different bins. In some embodiments, the same or similar amounts of DNA may have amounts that differ by an amount within a predetermined range, for example, less than 25%, 20%, 15%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or any range or value derived therefrom.

[0129] The method may include instructing the thermocycler in step 508 to perform PCR simultaneously on one of the vials in the same run, with a common number of PCR cycles corresponding to a subset of the library of DNA-containing compositions in the same vial.

[0130] In step 510, the method may include instructing the thermocycler to perform PCR on each of the additional vials with a corresponding common number of PCR cycles so that multiple libraries of DNA-containing compositions are normalized and amplified DNA is generated for each of the libraries, in order to minimize variability between samples.

[0131] The method may include instructing the sequencer in step 512 to identify candidate DNA conjugates for each library regarding their binding affinity to the target protein from the amplified DNA. Candidate DNA conjugates can be identified by any available sequencing method, such as next-generation sequencing. For example, the sequencer may include a next-generation sequencing system.

[0132] III.B.3. Normalization for PCR amplification using dynamic binning Referring here to Figure 6, a flowchart is shown illustrating a non-limiting, exemplary method 600 for normalizing a polymerase chain reaction (PCR) amplification process for multiple DNA-containing samples, according to various embodiments. Method 600 can be an example of an implementation for normalization that can be performed in step 140 of workflow 100 in Figure 1. In one or more embodiments, Method 600 can be implemented using a computing system, such as the computing device / analysis server 1206 shown in Figure 12, which will be described later. In some cases, Method 600 can be implemented using one or more engines of the computing system (e.g., one or more of the PCR cycle count engine 1208, sorting engine 1210, and amplification engine 1212 shown in Figure 12 above).

[0133] Method 600 may include in step 602 the step of identifying cycle data for performing a PCR amplification process on multiple samples, the cycle data including the corresponding number of cycles (Ct) for each sample of the multiple samples. Multiple samples may also be referred to as multiple libraries. Multiple samples may include, for example, DNA-containing compositions. Cycle data may also be referred to as PCR cycle data. In one or more embodiments, the cycle data is received from a qPCR system. In other embodiments, the cycle data is generated using initial cycle data received from a qPCR system, the initial cycle data including the initial number of cycles for each sample of the multiple samples. Step 602 may include modifying the initial number of cycles for at least one of the multiple samples. For example, in some cases, at least one of the multiple samples may have an initial number of cycles that is "undetermined" or has a null value. Step 602 may also include changing the initial number of cycles for at least one sample to a pre-selected number of cycles (e.g., the same number of cycles as the minimum number of cycles for the multiple samples, 3 cycles, 5 cycles, 10 cycles, or some other number of cycles).

[0134] In some embodiments, step 602 may include adding a selected number of cycles to each initial number of cycles for multiple samples, converting each non-integer number of cycles to an integer number of cycles (e.g., rounding up to the next integer), or both. The selected number of cycles to be added may be, for example, 1, 2, 3, 4, 5, or some other number of cycles. In one example, a number of cycles of 12.2 is converted to an integer value using the "integer" part of the number of cycles which is 12, or by rounding up to the nearest integer which is 13.

[0135] In other embodiments, step 602 may include deriving cycle data from some other form of data, such as the amount of DNA received from the qPCR system.

[0136] Method 600 may include, in step 604, sorting multiple samples into multiple bins based on cycle data such that the variation in the number of cycles within each bin of the multiple bins is reduced. Step 604 can be performed in any of several different ways. In one or more embodiments, step 604 may be performed by distributing multiple samples substantially uniformly into multiple bins based on a selected range of the number of cycles in the cycle data. Substantially uniform distribution can mean sorting multiple samples into multiple bins such that approximately the same number of samples (e.g., no more than one, two, three, or four of the same number) are assigned to each bin.

[0137] The selected range of cycle counts may, for example, be between the minimum and maximum number of cycle counts in the cycle data. As another example, the selected range of cycle counts may be between and include selected low cycle counts (e.g., 3, 6, 5, 6 cycles, etc.) and selected high cycle counts (e.g., 23, 24, 25, 26, 27 cycles, etc.). Variation in the number of cycle counts within each bin can be reduced by assigning samples to the same bin with the same number of cycle counts or corresponding cycle counts within a selected range of cycle counts (e.g., within 1, 2, 3, 5, 6 cycles, etc.).

[0138] In one or more embodiments, step 604 may be performed by first converting each non-integer cycle number in the cycle data to an integer cycle number to form corrected cycle data. The non-integer cycle number (e.g., 13.2) may be rounded up to the nearest integer (e.g., 14). In some cases, the non-integer cycle number (e.g., 13.2) may be converted to its integer (e.g., 13). The multiple samples may then be distributed substantially uniformly across multiple bins based on a selected range of cycle numbers in the corrected cycle data. This distribution may be performed as described above.

[0139] In one or more embodiments, step 604 may further include correcting the distribution of multiple samples in multiple bins such that any samples of multiple samples are grouped together in the same bin by corresponding cycle numbers associated with the same integer value. For example, in some cases, a substantially uniform distribution of multiple samples into multiple bins may result in cycle numbers associated with the same integer value in two (or more) different bins. Cycle numbers associated with the same integer value may include, for example, 13.2, 13.4, and 13.8, all corresponding to the same integer value of 13. In some cases, these cycle numbers can be considered associated with the same integer because, when rounded to the next nearest integer value, they all result in the same integer value of 14. In this example, correcting the distribution ensures that all samples are binned together in the same bin by cycle numbers associated with the integer value of 13 (or, if rounded up, 14).

[0140] Method 600 may include, in step 606, assigning a bin cycle number to each bin of a group of bins. With respect to step 606, the bin cycle number is unique to each bin of the group of bins. In other words, the same bin cycle number cannot be assigned to two bins. The bin cycle number for one of the group of bins can be generated using, for example, a number of cycles selected from a group consisting of the highest number of cycles, the average number of cycles, or the median number of cycles of the set of samples in the bin. For example, the highest number of cycles of the set of samples in a given bin can be used as the bin cycle number for that bin. Alternatively, an integer value associated with the highest number of cycles may be used as the bin cycle number. In some cases, the bin cycle number is the sum of the highest number of cycles of the set of samples and the selected number of cycles, or an integer value of such a sum. The selected number of cycles may be, for example, 1, 2, 3, 4, 5, or any other number of cycles. As an example, if the selected number of cycles is 2 and the highest number of cycles of the set of samples in a bin is 10 cycles, then that bin can be assigned a bin cycle number of 12.

[0141] Method 600 may include generating identification information for a plurality of bins in step 608. The identification information may include a bin identifier for each bin in the plurality of bins. In one or more embodiments, this bin identifier is a unique identifier that uniquely identifies the bin. The bin identifier may be, for example, a barcode. In one or more embodiments, the bin identifier assigned to a bin may be the same as the plate identifier associated with a PCR plate. For example, the bin identifier assigned to a bin may be the barcode of a PCR plate. Such an assignment indicates that the set of samples contained in that bin will be transferred to a PCR plate having the same barcode. In other embodiments, the bin identifier may be matched with the plate identifier of a PCR plate using a database, spreadsheet, or other data format that matches the bin identifier with the plate identifier. In some embodiments, the identification information may include additional information for the plurality of bins, such as, for example, the total number of bins, the total number of sets of samples in each bin, the minimum and / or maximum number of bin cycles associated with each bin, other information that characterizes the plurality of bins as a whole and / or each individual bin, or a combination thereof.

[0142] Method 600 may include, in step 610, generating an output for performing PCR amplification of multiple samples using a plurality of bins and a number of bin cycles for each bin in the plurality of bins. The output may include, for example, a transfer output for use when transferring a set of samples in each bin of the plurality of bins to the corresponding PCR plates of a set of PCR plates, using identification information. For example, the identification information may be used to match the plurality of bins to a set of PCR plates, such that each bin in the plurality of bins matches the corresponding PCR plate of the set of PCR plates.

[0143] In one or more embodiments, the transfer output includes multiple forward worklists for multiple bins. Each forward worklist in the multiple forward worklists is associated with a corresponding bin in the multiple bins. For example, a forward worklist for a bin may include the sequence in which a set of samples in the bin is selected from a source plate holding multiple samples and transferred to a PCR plate. The forward worklist may, for example, identify the samples by the row and column of their wells in the source plate and identify the corresponding wells in the PCR plate to which the samples are transferred. In various embodiments, the transfer output may further include a reverse worklist for each bin, enabling the transfer of a set of samples (after amplification) from the PCR plate to the source plate.

[0144] The output generated in step 610 may further include, for example, an amplified output for use when performing the PCR amplification process. The amplified output may include, for example, instructions for a thermocycler indicating the number of bin cycles associated with each bin (and thus the PCR plate) and / or the number of bin cycles associated with each PCR plate (since the number of bin cycles is associated with the bin corresponding to the PCR plate). The thermocycler can then use this information to perform the PCR.

[0145] In one or more embodiments, each bin uniquely matches a PCR plate. In other words, two bins do not have to be assigned to the same PCR plate. However, in other embodiments, two bins may have the same identifier corresponding to the same PCR plate. Assigning two bins to the same PCR plate can be done, for example, when the number of bin cycles of the two bins differs by less than a selected amount (e.g., about 1, 0.75, 0.5, etc.).

[0146] Method 600 may include, in step 612, transferring a set of samples from each vial of a set of vials to the corresponding PCR plates of a set of PCR plates, based on the output. For example, the set of samples in the vials may be transferred from the source plate to the corresponding PCR plate by a liquid handler.

[0147] Method 600 may include, in step 614, performing a PCR amplification process using a set of PCR plates. In one or more embodiments, the PCR amplification is performed such that the number of amplification cycles for each PCR plate in the set of PCR plates is determined by the number of bin cycles for one or more bins associated with each PCR plate. Before amplification, the multiple samples have varying amounts of DNA. After the PCR amplification process is performed, the multiple samples in the set of PCR plates can become amplified samples having normalized amounts of DNA. In other words, the PCR amplification process is performed such that the amounts of DNA in the amplified samples are approximately the same or similar (e.g., within a selected tolerance range for each other). For example, the normalized amount of DNA may be the amount of DNA that falls within a threshold range (e.g., a percentage range, amount, etc.) for each other. As an example, the normalized amount of DNA may include amounts of DNA that fall within 1%, 2%, 3%, 4%, 5%, 8%, 10%, 15%, or any other percentage range for each other.

[0148] Method 600 can be repeated for each PCR run. In some cases, the selected number of cycles in step 608, which is added to the maximum number of cycles in a bin to form the total number of cycles in that bin, is dynamic in that the selected number of cycles can be changed for each run as needed. For example, if the data after one run shows that the amount of DNA is lower than desired, the selected number of cycles can be increased (e.g., from 2 to 3). However, if the data after another run shows that the amount of DNA is too high, the selected number of cycles can be decreased (e.g., from 2 to 1). Changes to the selected cycles can be made via user input entered by the user, or via

[0149] Figure 7 is a flowchart of a non-limiting exemplary method 700 for normalizing multiple DNA-containing samples, as shown according to various embodiments. Method 700 may be another example of an implementation for normalization that can be performed in step 140 of workflow 100 in Figure 1.

[0150] The method may include, in step 702, identifying multiple cycle numbers for multiple samples, where the multiple cycle numbers include the corresponding cycle numbers for each sample of the multiple samples. Multiple cycle numbers can be identified, for example, by receiving multiple cycle numbers from a qPCR system. In one or more embodiments, multiple cycle numbers are identified by receiving initial cycle numbers from a qPCR system, and the qPCR system is then modified to form multiple cycle numbers (for example, at least one of the initial cycle numbers is modified). This modification can be performed in a manner similar to the modification described above in step 602 of method 600 described above with respect to Figure 6.

[0151] The method may include identifying a distribution of multiple cycle counts in step 704. The distribution may be, for example, a histogram distribution. In one or more embodiments, 60% to 100% of the multiple cycle counts are between a selected low cycle count and a selected high cycle count, and within a selected range including them. The selected low cycle count may be, for example, 2, 3, 4, or 5 cycles. The selected high cycle count may be, for example, 22, 23, 24, 25, 26, or 27 cycles. Thus, in one or more embodiments, the selected range may be between 4 cycles and 24 cycles (including 4 cycles).

[0152] The method may include, in step 706, sorting multiple samples into multiple bins based on a distribution of multiple cycle counts such that cycle count variation is reduced within each bin of multiple bins and any samples of multiple samples are grouped together in the same bin by corresponding cycle counts associated with the same integer value. Step 706 can be performed in any of several different ways.

[0153] In one or more embodiments, step 706 may include assigning any sample from a plurality of samples to the first bin of a plurality of bins with a corresponding number of cycles less than the selected low number of cycles, and assigning any sample from a plurality of samples to the last bin of a plurality of bins with a corresponding number of cycles greater than the selected high number of cycles. For example, if there are eight bins, the selected low number of cycles is 4 cycles, and the selected high number of cycles is 24 cycles, any sample with a corresponding number of cycles less than 4 cycles can be assigned to the first bin, and any sample with a corresponding number of cycles greater than 24 cycles can be assigned to the eighth bin. Thus, outlier cycle numbers are binned in the first and last bins. The remaining portion of the plurality of samples can then be distributed between the set of bins between the first and last bins.

[0154] In some cases, if there are no outlier cycle counts within a selected range (e.g., 100% of the cycle counts are within the selected range), multiple samples can be distributed among multiple bins with a bias to provide more bin separation between lower cycle counts compared to higher cycle counts. For example, samples with lower cycle counts (e.g., between 4 and 16 cycle counts) can be distributed among more bins than samples with higher cycle counts (e.g., between 16 and 24 cycle counts).

[0155] In one or more embodiments, multiple samples are sorted into multiple bins based on a distribution of multiple cycle numbers, biased to provide more bin separation among the cycle numbers corresponding to the majority of the samples. For example, multiple samples may be sorted into multiple bins based on a distribution of multiple cycle numbers, biased to provide more bin separation among a portion of the cycle numbers that lies within one standard deviation of the mean of the multiple cycle numbers compared to another portion of the cycle numbers that lies outside one standard deviation of the mean.

[0156] Step 706 may further include ensuring that all cycle numbers associated with the same integer value are binned together. In some embodiments, two cycle numbers can be considered associated with the same integer value if each of them contains an integer that is the same integer value. For example, 11.42 and 11.75 are both considered associated with the integer value 11. In other embodiments, two cycle numbers can be considered associated with the same integer value if each of them rounds up to the same integer value when rounded up to the nearest integer. For example, 11.42 and 11.75 are both considered associated with the integer value 12 because both cycle numbers are rounded up to 12.

[0157] This method may include, in step 708, assigning a bin cycle number to each bin of a plurality of bins, wherein the bin cycle number is unique to each bin of the plurality of bins. Step 708 may be implemented in different ways. Step 708 can be implemented in a similar manner to step 606 of method 600 described above with respect to Figure 6.

[0158] This method may include, in step 710, generating an output for PCR amplification of multiple samples using multiple bins and the number of bin cycles for each bin in the multiple bins. Step 710 can be performed in a manner similar to step 608 of method 600 described above with respect to Figure 6.

[0159] In step 712, the method may include transferring a set of samples from each of several vials to a corresponding PCR plate in a set of PCR plates, based on the output. For example, a set of samples may be transferred from a source plate to a corresponding PCR plate.

[0160] This method may include, in step 714, performing a PCR amplification process using a set of PCR plates. The PCR amplification process may include performing it on a single PCR plate or a pair of PCR plates at once. Once PCR is performed on the set of PCR plates, the multiple samples in the set of PCR plates can be considered as multiple amplified samples having normalized amounts of DNA.

[0161] Figure 8 is a flowchart of a non-limiting exemplary method 800 for normalizing multiple samples containing DNA, as shown according to various embodiments. Method 800 can be another example of an implementation for normalization that can be performed in step 140 of workflow 100 in Figure 1. In one or more embodiments, at least a portion of Method 800 can be used to implement step 604 of Method 600 described in Figure 6 above and / or steps 704 and 706 of Method 700 described in Figure 7 above.

[0162] Method 800 may include in step 802 converting any non-integer cycle counts of cycle data from multiple samples to integer cycle counts to form corrected cycle data. Non-integer (e.g., decimal) cycle counts may be rounded up or down to the nearest integer. In some embodiments, all non-integer cycle counts are rounded up to the nearest integer. In some cases, step 802 may be an example of an implementation of at least part of step 602 of Method 600 described in Figure 6 above and / or step 702 of Method 700 described in Figure 7 above. In other cases, step 802 may be considered part of step 604 of Method 600 described in Figure 6 above, or an example of an implementation of 704 and / or 706 of Method 700 described in Figure 7 above.

[0163] The method may include determining in step 804 whether any of the cycle numbers in the corrected cycle data are outside a selected range of cycle numbers. The selected range of cycle numbers is the range between a selected low cycle number and a selected high cycle number, including them. The selected low cycle number may be, for example, 2, 3, 4, or 5 cycles. The selected high cycle number may be, for example, 22, 23, 24, 25, 26, or 27 cycles. For example, the selected range of cycle numbers may include, but is not limited to, 5 to 24 cycles.

[0164] If any of the cycle counts are outside the selected range of cycle counts, method 800 may, in step 806, assign any cycle counts outside the selected range to one or more outlier bins. For example, if the total number of available bins is 8, the first bin (e.g., bin 1) and the last bin (e.g., bin 8) may be used as outlier bins. Any cycle count below the selected range of cycle counts may be assigned to the first bin, and any cycle count above the selected range of cycle counts may be assigned to the last bin. Assigning cycle counts to bins includes assigning any samples associated with that cycle count to that bin.

[0165] The method may include, in step 808, assigning unique integer cycle numbers of modified cycle data within a selected range of cycle numbers to N bins. In one or more embodiments, the unique integer cycle numbers are arranged in N bins in ascending order, where N is the number of unique integer cycle numbers.

[0166] This method may include, in step 810, merging adjacent bins of N bins using a distance equation until the target number of bins is reached. The distance equation defines distance as the difference between the minimum number of cycles in bin M and the minimum number of cycles in bin M+1. Adjacent bins with the minimum distance are merged until the target number of bins is reached. The target number of bins may vary based on the number of cycles that fall within a selected range of cycles. For example, the target number of bins may be the total number of available bins (e.g., 8 bins) minus the number of outlier bins used in step 808 (e.g., 1 or 2).

[0167] The method may include adjusting the minimum and maximum number of cycles in each bin in step 812. For example, adjustments may be made to account for rounding up and / or rounding down the number of cycles in step 802. In one or more embodiments, the minimum number of cycles in each bin is decreased by a first adjustment, and the maximum number of cycles in each bin is increased by a second adjustment. The first and second adjustments may be the same or different. The first and second adjustments may be, for example, 0.5. In other examples, the first adjustment may be 0.5 and the second adjustment may be 1.0, or vice versa.

[0168] Referring again to step 804, if none of the cycle numbers are outside the selected range of cycle numbers, method 800 proceeds to step 808 as described above. In these such examples, the target number of bins in step 808 may simply be the total number of available bins.

[0169] In this way, method 800 is a process for sorting cycle counts into multiple bins. After this sorting is performed, each bin can be assigned a bin cycle count, as described in step 606 of method 600 in Figure 6 and step 708 of method 700 in Figure 7.

[0170] III.B.4. Exemplary Results of Dynamic Binning Figure 9A is a table showing the first round of dynamic binning using upper bias according to one or more embodiments. Table 900 shows the results of dynamic binning of samples after qPCR analysis in the first round based on upper bias selection and their corresponding number of cycles.

[0171] Figure 9B is a table showing the fourth round of dynamic binning using upper bias according to one or more embodiments. Table 902 shows the results of dynamic binning of samples after qPCR analysis in the fourth round based on upper bias selection and their corresponding number of cycles.

[0172] Figure 10 is a table showing the first round of dynamic binning using a uniform distribution according to one or more embodiments. Table 1000 shows the results of dynamic binning of samples and their corresponding cycle counts after the first round of qPCR analysis when the samples and their corresponding cycle counts are uniformly distributed across the available bins (8 bins).

[0173] Figure 11A is a table showing a first round of dynamic binning with a bias on samples at a selected range of cycles, according to one or more embodiments. Table 1100 shows the results of dynamic binning of samples and their corresponding cycle numbers after a first round of qPCR analysis based on selection with a bias on samples at a selected range of cycles. This bias is used to reduce the deviation of PCR amplification from a desired number of cycles (e.g., the number of cycles obtained via the qPCR system) for samples within the selected range of cycles. Thus, this type of binning can help ensure that the correct PCR cycles are given to the largest number of intermediate samples (within the selected range of cycles) compared to samples with outlier cycle numbers (outside the selected range of cycles).

[0174] Figure 11B is a table showing a fourth round of dynamic binning bias on samples at a number of cycles within a selected range of cycle counts according to one or more embodiments. Table 1102 shows the results of dynamic binning of samples and their corresponding number of cycle counts after the first round of qPCR analysis based on bias screening of samples at a number of cycles within a selected range of cycle counts.

[0175] Normalization system Figure 12 shows a non-limiting exemplary system configured to normalize multiple libraries in target binding selection, according to various embodiments. System 1200 can include various combinations of features, whether it has more or fewer features than those shown in Figure 12. Thus, Figure 12 merely shows an example of a possible system.

[0176] System 1200 includes a quantitative PCR unit 1202, a data storage unit 1204, a computing device / analysis server 1206, a display 1214, a PCR thermocycler 1216, and a liquid handler 1218. The quantitative PCR unit 1202 is a quantitative PCR instrument, which is a machine that amplifies and detects DNA. The quantitative PCR instrument combines the functions of a thermal cycler and a fluorometer to enable the quantitative PCR process. The quantitative PCR instrument monitors the progress of PCR and the properties of the amplified product by measuring fluorescence.

[0177] The quantitative PCR unit 1202 can be communicatively connected to the data storage unit 1204 via a serial bus (when both form an integrated instrument platform) or via a network connection (when both are distributed / separate devices). The generated qPCR dataset is stored in the data storage unit 1204 for subsequent processing. In various embodiments, one or more raw qPCR datasets may also be stored in the data storage unit 1204 before processing and analysis. Thus, in various embodiments, the data storage unit 1204 can be configured to store qPCR datasets of various embodiments of this specification corresponding to multiple libraries of DNA-containing compositions. In various embodiments, the processed and analyzed qPCR dataset can be supplied in real time to a computing device / analysis server 1206 for further downstream analysis.

[0178] The data storage unit 1204 can be communicatively connected to the computing device / analysis server 1206. In various embodiments, the data storage unit 1204 and the computing device / analysis server 1206 can be part of an integrated device. In various embodiments, the data storage unit 1204 can be hosted by a device different from the computing device / analysis server 1206. In various embodiments, the data storage unit 1204 and the computing device / analysis server 1206 can be part of a distributed network system. In various embodiments, the computing device / analysis server 1206 can be communicatively connected to the data storage unit 1204 via a network connection that can be either a “hardwired” physical network connection (e.g., the Internet, LAN, WAN, VPN, etc.) or a wireless network connection (e.g., Wi-Fi, WLAN, etc.). The computing device / analysis server 1206 can be a workstation, a mainframe computer, a distributed computing node (“cloud computing” or part of a distributed networking system), a personal computer, a mobile device, etc., according to various embodiments. The computing device / analysis server 1206 can be a client computing device. In various embodiments, the computing device / analysis server 1206 may be a personal computing device having a web browser (e.g., INTERNET EXPLORER®, FIREFOX®, Safari®, etc.) which can be used to control the operation of the qPCR unit 1202, data storage unit 1204, display 1214, PCR thermocycler 1216, and liquid handler 1218.

[0179] A computing system, such as a computer device / analysis server 1206, is configured to host one or more PCR cycle count engines 1208, one or more sorting engines 1210, and one or more amplification engines 1212, according to various embodiments. Engines such as the PCR cycle count engine 1208, sorting engine 1210, and amplification engine 1212 can be implemented using software, firmware, hardware, or a combination thereof within the computing system (computer device / analysis server 1206).

[0180] The PCR cycle count engine 1208 is configured to use quantified information to determine a polymerase chain reaction ("PCR") cycle count specific to each library, and the DNA-containing composition of each library is determined to produce a corresponding preset amount of DNA after PCR is performed for the corresponding PCR cycle count.

[0181] The sorting engine 1210 is configured to sort libraries of DNA-containing compositions into bins, each bin containing a different subset of libraries of DNA-containing compositions determined to share a common number of PCR cycles for DNA amplification, and each different subset of libraries of DNA-containing compositions in each bin shares a different common number of PCR cycles. In one or more embodiments, the sorting engine 1210 can be used to perform one or more of the steps 406 in Figure 4, step 506 in Figure 5, steps 602, 604, 606, 608, and 610 in Figure 6, one or more of the steps 702, 704, 706, 708, and 710 in Figure 7, one or more of the steps 802, 804, 806, 808, 810, and 812 in Figure 8, or at least one combination thereof.

[0182] The amplification engine 1212 is configured to instruct the thermocycler 1216 to perform PCR simultaneously on one of the vials in the same run, with a common number of PCR cycles corresponding to a subset of libraries of DNA-containing compositions in the same vial. The amplification engine 1212 is also configured to instruct the thermocycler 1216 to perform PCR on each library of DNA-containing compositions in additional vials so that multiple libraries of DNA-containing compositions are normalized. The amplification engine 1212 can be used to perform, for example, one or more of steps 408 and 410 in Figure 4, one or more of steps 508 and 510 in Figure 5, one or more of steps 610, 612, and 614 in Figure 6, one or more of steps 710, 712, and 714 in Figure 7, or a combination thereof.

[0183] System 1200 further comprises a liquid handler 1218 configured to transfer each library in the same bin from a source plate to a PCR plate, and each library in the same bin is amplified by PCR on the PCR plate with a common number of PCR cycles for the same bin to generate amplified DNA. The liquid handler 1218 is further configured to provide the amplified DNA from all bins for an additional selective round. The amplification engine 1212 is communicatively coupled to the liquid handler 1218 so that it can be instructed to transfer the sample back to the source plate.

[0184] While the computing device / analysis server 1206 receives and processes data from the data storage unit 1204, or after processing is complete, the output results can be displayed as results or summaries on a display or client terminal 1214 that is communicatively connected to the computing device / analysis server 1206. The display or client terminal 1214 can be a client computing device. The display or client terminal 1214 can be a personal computing device having a web browser (e.g., INTERNET EXPLORER®, FIREFOX®, SAFARI®, etc.) that can be used to control the operation of the qPCR unit 1202, data storage unit 1204, PCR cycle engine 1208, sorting engine 1210, amplification engine 1212, PCR thermocycler 1216, and liquid handler 1218.

[0185] It should be understood that various engines can be combined into a single engine, component, or module, or folded, depending on the requirements of a specific application or system architecture. Engines 1208, 1210, and 1212 may have additional engines or components as needed depending on the specific application or system architecture.

[0186] IV. Visualization of Quantitative Information from Nucleotide-Containing Libraries Methods and systems for visualizing and monitoring quantitative information of nucleotide-containing libraries in one or more selection rounds for binding to a desired target can be provided herein. Currently, visualizing a large number of libraries simultaneously is extremely difficult, and comparing different datasets from large selections by moving back and forth between different datasets is time-consuming and prone to errors. The methods and systems provided herein enable simultaneous tracking and monitoring of large datasets in a more efficient and effective manner.

[0187] IV.A. Visualization Workflow To illustrate a non-limiting, exemplary process for visualizing and monitoring quantitative information of multiple libraries of DNA-containing compositions for detecting target binding, according to various embodiments, a general schematic workflow 1300 is provided in Figure 13. Such a graphical user interface can enable simultaneous visual observation and comparison of multiple libraries for selection rounds for target binding and comparisons between rounds. The workflow may include various combinations of features, whether more or less than those shown in Figure 13. Thus, Figure 13 merely illustrates an example of a possible workflow.

[0188] Workflow 1300 may include receiving quantification information for multiple libraries of DNA-containing compositions, including qPCR data, in step 1310. Receiving quantification information may include collecting qPCR data for input molecules, positive molecules, and negative molecules. Prior to each round of target binding selection, qPCR is performed on aliquots of each mRNA-DNA-peptide conjugate library. The Ct generated by this pre-selection reaction represents the number of molecules in each "input" library, as it represents the total amount of each library before any binding step and provides quantification information for input molecules. Quantification information for positive molecules includes Ct generated by qPCR of aliquots of each mRNA-DNA-peptide conjugate library after positive sex selection, i.e., DNA captured from the target binding step of positive selection. Quantification information for negative molecules includes Ct generated by qPCR of aliquots of each mRNA-DNA-peptide conjugate library after negative selection.

[0189] qPCR data can be generated after a series of automated or manual library generation, target binding selection, and DNA measurement by qPCR. Without further processing for visualization as described herein, raw qPCR data, such as a table containing all data from all individual wells across all rounds, is not easily understood or interpreted. For example, in a 136-well plate, there may be 136 experiments with 4 to 10 target binding selection rounds. In a table of raw qPCR data, the Ct levels of DNA in each well across all target binding selection rounds are very difficult to compare with another well in the same selection round, or the same well in a different selection round, in order to provide insight in an efficient and effective way.

[0190] Some embodiments of the visualization methods described herein can solve these problems by simultaneously displaying selected quantifiable information to enable better informed decision-making.

[0191] Workflow 1300 may include transferring quantified data and storing the data in a database in step 1320. Data transfer may include data scraping, in which a computer program extracts data from human-readable output coming from another program, such as Excel. The database stores each automatically or non-automatically exported dataset and all associated metadata (e.g., date, time, and plate barcode).

[0192] Workflow 1300 may include assigning a dataset to a corresponding selection round in step 1330. According to some embodiments, each exported dataset may be assigned to a corresponding selection round by the user.

[0193] Workflow 1300 may include visualizing data on a graphical display surface in step 1340. Once each dataset is assigned to a corresponding bullet, all heatmaps and charts are generated according to the selection of pre-configured criteria or filters. For example, if round-versus-round comparison is selected, a bar graph of round-versus-round comparison of %mRNA recovery is generated (e.g., positive or negative recovery). For example, if mRNA% recovery is selected, a heatmap is generated using mRNA% recovery for each well. For example, if negative molecules are selected after round 1, a heatmap is generated using the qPCR results of negative molecules in each well after the first round. For example, if positive molecules are selected after round 1, a heatmap is generated using mRNA% recovery for each well after the first round (e.g., positive or negative recovery). For example, negative mRNA% recovery is defined as input / positive * 100. For example, the input molecule is multiplied by a predefined multiplier such as input molecule = (input qPCR result * 20 * 50 * 10000), and the user pre-enters these multipliers. For example, the heatmap color definitions for positive and negative molecules are as follows: 10e8 is red, 10e10 is blue, and 10e13 is purple.

[0194] IV.B. Visualization method A method is provided for visualizing quantitative information from multiple libraries of DNA-containing compositions for detecting target binding. This method can be implemented via computer software or hardware. It can also be implemented on a computing device / system that includes a combination of engines for normalizing multiple libraries of DNA-containing compositions. The computing device / system can be communicatively connected to one or more of the following: a data source, a sample analyzer (e.g., a genome sequencing analyzer), and a display device, either directly or via an internet connection.

[0195] Referring here to Figure 14, a flowchart is disclosed showing a non-limiting exemplary method 1400 for normalization relating to various embodiments. Method 1400 may include, in step 1402, receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round. For example, each library of DNA-containing compositions includes a DNA conjugate. The DNA conjugate may include peptides such as linear or cyclic peptides, or combinations thereof. The cyclic peptide may be a macrocycle that includes monocyclic, bicyclic, or tetracyclic peptides. Method 1400 may be part of a screening assay in which the DNA conjugate is selected for binding affinity to a target protein for a first selection round and an additional selection round for binding affinity.

[0196] For example, the quantification information for each DNA-containing composition library includes the cycle threshold (Ct) for quantitative PCR (qPCR) input molecules, positive molecules, negative molecules, or any combination thereof. Additionally and alternatively, the quantification information for each DNA-containing composition library includes the percentage of positive molecules relative to the input molecules, the percentage of negative molecules relative to the input molecules, or a combination thereof.

[0197] In some embodiments, the quantitative information for each library of the DNA-containing composition was obtained by scraping the qPCR data of each library.

[0198] Method 1400 may include, in step 1404, displaying a first window containing quantification information for each of a plurality of DNA-containing compositions within a graphical user interface on a computer screen.

[0199] Method 1400 may include, in step 1406, repeating steps 1402 and 1404 to generate multiple windows, each of which corresponds to quantification information for each of the multiple subsequent round selections, such that the quantification information for each of the libraries is dynamically monitored for detecting target bindings in the multiple subsequent rounds.

[0200] In some embodiments, any window may contain a first graphical element in multiple positions. Each of the first graphical elements may be configured to represent each of the libraries. For example, each library may be in one of the individual spaces of the source plate, and each of the first graphical elements may be configured to correspond horizontally and vertically to each of the individual spaces of the source plate. In some embodiments, each of the first graphical elements may be positioned at the same location across different windows to represent the same well in the source plate.

[0201] Any window may also contain a second graphical element configured to visually distinguish quantification information from different libraries. This second graphical element may include colors, numbers, or a combination thereof.

[0202] Any window may contain a third graphical element configured to set filters and display quantified information for each library selected by the filters. For example, the filters could be user-selected scaffolds, user-selected codons, or user-selected targets. Any window may contain a first, second, or third graphical element, or any additional graphical element, or a combination thereof.

[0203] Method 1400 further includes displaying a selected window that displays quantification information for a selected round while hiding other windows. Method 1400 further includes updating the graphical user interface to display a new window when a new selected round is selected by the user. Method 1400 further includes displaying a first window and additional windows within the same graphical user interface so that round-for-round comparisons are generated. Method 1400 further includes plotting round-for-round comparisons for each of the libraries of DNA-containing compositions on the graphical user interface.

[0204] IVC Visualization System Figure 15 provides a general system 1500 to illustrate a non-limiting, exemplary system for visualizing quantitative information from multiple libraries of DNA-containing compositions for detecting target binding, according to various embodiments. System 1500 may include various combinations of features, whether more or fewer features than those shown in Figure 15. Thus, Figure 15 merely illustrates an example of a possible system.

[0205] System 1500 includes a quantitative PCR unit 1502, a data storage unit 1504, and a computing device / analysis server / display 1506. The quantitative PCR unit 1502 is a quantitative PCR instrument, which is a machine that amplifies and detects DNA. The quantitative PCR instrument combines the functions of a thermal cycler and a fluorometer to enable the quantitative PCR process. The quantitative PCR instrument monitors the progress of PCR and the properties of the amplified product by measuring fluorescence.

[0206] The quantitative PCR unit 1502 can be communicatively connected to the data storage unit 1504 via a serial bus (when both form an integrated instrument platform) or via a network connection (when both are distributed / separate devices). The generated qPCR dataset is stored in the data storage unit 1504 for subsequent processing. One or more raw qPCR datasets may also be stored in the data storage unit 1504 prior to processing and analysis. Thus, in various embodiments, the data storage unit 1504 can be configured to store qPCR datasets of various embodiments of this specification corresponding to multiple libraries of DNA-containing compositions. The processed and analyzed qPCR datasets can be supplied in real time to a computing device / analysis server / display 1506 for further downstream analysis.

[0207] The data storage unit 1504 can be communicatively connected to the computing device / analysis server / display 1506. In various embodiments, the data storage unit 1504 and the computing device / analysis server / display 1506 can be part of an integrated system. In various embodiments, the data storage unit 1504 can be hosted by a device different from the computing device / analysis server / display 1506. In various embodiments, the data storage unit 1504 and the computing device / analysis server / display 1506 can be part of a distributed network system. In various embodiments, the computing device / analysis server / display 1506 can be communicatively connected to the data storage unit 1504 via a network connection that can be either a “hardwired” physical network connection (e.g., the Internet, LAN, WAN, VPN, etc.) or a wireless network connection (e.g., Wi-Fi, WLAN, etc.). In various embodiments, the computing device / analysis server / display 1506 can be a workstation, a mainframe computer, a distributed computing node (“cloud computing” or part of a distributed networking system), a personal computer, a mobile device, etc.

[0208] The computing device / analysis server / display 1506 can be a client computing device. In various embodiments, the computing device / analysis server / display 1506 can be a personal computing device having a web browser (e.g., INTERNET EXPLORER®, FIREFOX®, Safari®, etc.) which can be used to control the operation of the qPCR unit 1502 and the data storage unit 1504.

[0209] One or more graphical user interfaces 1508 can be displayed on the display of the computing device / analysis server / display 1506. In various embodiments, the computing device / analysis server / display 1506 is configured to host one or more graphical user interfaces 1508. For example, a graphical user interface 1508 includes a graphical element 1510 that sets one or more filters to determine specific quantification information for each library to be displayed on the graphical user interface. Non-exclusive exemplary formats of graphical elements may include blank fields, text boxes, checkboxes, pull-down menus, or other input areas from which the user can select data output.

[0210] For example, graphical element 1510 is a filter such as a user-selected scaffold, user-selected codon, or user-selected target. For example, graphical element 1510 is a menu of several options, including but not limited to positive recovery, negative recovery, input, positive melting curve, negative melting curve, enrichment, qPCR Ct cycle, round 1, round 2, round 3, round 4, round 5, round 6, any appropriate number of rounds, or any combination thereof.

[0211] After a graphical element 1510 is selected, one or more corresponding windows 1512 are displayed to show the corresponding quantification information for all wells in a single assay. Each well represents each library in a group of libraries of DNA-containing compositions. For example, window 1512 displays graphical elements 1514, 1516, and grid 1518. Grid 1518 contains columns and rows of quantification information that match the corresponding columns and rows of the source plate in the qPCR assay. Graphical element 1514 displays labels indicating the contents of window 1512 and the corresponding selections on graphical element 1510. For example, if graphical element 1510 is selected to display "Input" and "Round 1", the contents of grid 1518 will show the qPCR results for the input molecules of Round 1, and graphical element 1514 will show "Input qPCR R1". Graphical element 1516 is a filter for selecting a subset of the quantification information displayed in window 1512, such as selecting the qPCR results for input, positive, or negative molecules.

[0212] Figures 16 to 14 are graphs illustrating non-limiting exemplary embodiments of a graphical user interface for visualizing multiple libraries of DNA-containing compositions in target binding selection.

[0213] Figure 16 shows a non-limiting exemplary embodiment of a graphical user interface 1600 for visualizing each of multiple libraries of DNA-containing compositions in a selected target binding selection round. The graphical user interface 1600 includes filters 1602, 1604, 1606, and 1608 that can be selected to display filtered data from quantification information of multiple libraries of DNA-containing compositions. For example, filters include positive recovery, negative recovery, input, positive melting curve, negative melting curve, enrichment, qPCR, Ct cycle, or round number (e.g., round 1 or R1, round 2 or R2, round 3 or R3, round 4 or R4, round 5 or R5, round 6 or R6, etc.). Additional filters may include, but are not limited to, filters 1604, which can select quantitative information of peptides having a specific scaffold for visualization (e.g., peptide lengths in multiple peptide candidate libraries for target binding selection, such as scaffold 1, scaffold 2, scaffold 3); filters 1606, which can select quantitative information of peptides having a specific codon for visualization (e.g., codons used when constructing peptide candidates in multiple libraries for target binding selection, e.g., codon table 1, codon table 2, codon table 3); and filters 1608, which can select quantitative information of peptides screened for a specific target for visualization (e.g., desired protein targets used in target binding screening or selection, e.g., target 1, target 2, target 3). Using specific filters selected by specific user selection values, for example, the quantitative information of each of multiple libraries of DNA-containing compositions, or each selection round matching the selected filters, can be displayed in exemplary graphs 1610-1216 and Figures 17-14.

[0214] Figure 17 shows a non-limiting exemplary embodiment of the graphical user interface 1700 for visualizing each of multiple libraries of DNA-containing compositions in all target binding selection rounds. Figure 17 is a screenshot of the graphical user interface 1700 and includes six heatmaps (colors are represented as shades of gray) that use color to display different DNA concentrations in each well (wells A1 to H12) for each round (R1=Round 1, R2=Round 2, R3=Round 3, R4=Round 4, R5=Round 5, R6=Round 6). "Pos" refers to the qPCR result of DNA concentration after a positive selection round. This is a representative view for monitoring the overall progress of target binding selection and can help the user determine whether the target binding selection in another round is desirable. For example, columns 4-7 of rounds 4, 5 and 6, showing medium DNA concentrations, performed relatively well in target binding selection compared to other columns showing low DNA concentrations. Visualizing this enrichment trend continuing from one round to another helps the user build confidence that the entire selection process is working well.

[0215] Figure 18 shows another non-limiting exemplary embodiment of the graphical user interface 1800 for visualizing each of the multiple libraries of the DNA-containing composition in all target binding selection rounds. Figure 18 is a screenshot of the graphical user interface 1800. The qPCR data for each of the multiple libraries of the DNA-containing composition after selection in each round was analyzed to %mRNA recovery by dividing positive or negative molecules by the input molecules. For example, %mRNA recovery (% positive recovery and % negative recovery) in each round was plotted as a bar graph to show the progress of the experiment for each individual well, e.g., each library of the macrocycle-DNA-RNA conjugate. This data is reviewed in conjunction with a molecular heatmap, as illustrated in Figure 19, to determine whether another round is desirable. %mRNA recovery is calculated from the qPCR data. %mRNA recovery represents the total amount of mRNA / DNA / peptide captured by the target in each library. Positive molecules refer to DNA captured from the target binding step of positive selection. Negative molecules refer to DNA remaining after the empty bead binding step of negative selection. Prior to each round of target binding selection, qPCR is performed on aliquots of each mRNA-DNA-peptide conjugate library. The Ct generated by this pre-selection reaction represents the total amount of each library before the binding step, and therefore represents the number of DNA molecules in each "input" library.

[0216] V. Computer-Implemented Systems In various embodiments, any method for visualizing the simultaneous selection of normalization and target binding candidates across different libraries with different DNA concentrations can be implemented via software, hardware, firmware, or a combination thereof.

[0217] In other words, as depicted in Figure 12, the normalization method disclosed herein can be implemented on a computer system (e.g., a computing device / analysis server), such as computer system 1206. Computer system 1206 (e.g., a computing device / analysis server) can be communicatively connected to data storage device 1204 and display system 1214 via direct connection or network connection (e.g., LAN, WAN, internet, etc.). It should be understood that computer system 1206 (e.g., a computing device / analysis server) shown in Figure 12 may have additional engines or components as needed depending on the specific application or system architecture.

[0218] Furthermore, as depicted in Figure 15, the visualization methods disclosed herein can be implemented on a computer system 1500. In various embodiments, the computer system 1500 (e.g., device / analysis / display system) may include a data storage device 1504 that is communicably connected to a computing device / analysis / display system 1506 via direct connection or network connection (e.g., LAN, WAN, internet, etc.). It should be understood that the computing device / analysis / display system 1500 shown in Figure 15 may include additional engines or components as needed depending on the specific application or system architecture.

[0219] Figure 19 is a block diagram showing a computer system 1900 in which embodiments of this teaching may be implemented. In various embodiments of this teaching, the computer system 1900 may include a bus 1902 or other communication mechanism for communicating information and a processor 1904 coupled to the bus 1902 for processing information. In various embodiments, the computer system 1900 may also include memory, which may be random access memory (RAM) 1906 or other dynamic storage device, coupled to the bus 1902 for determining instructions to be executed by the processor 1904. The memory may also be used to store temporary variables or other intermediate information during the execution of instructions executed by the processor 1904. In various embodiments, the computer system 1900 may further include read-only memory (ROM) 1908 or other static storage device coupled to the bus 1902 for storing static information and instructions for the processor 1904. A storage device 1910, such as a magnetic disk or optical disk, may be provided and coupled to the bus 1902 for storing information and instructions.

[0220] In various embodiments, the processor 1904 may be coupled via a bus 1902 to a display 1912, such as a cathode ray tube (CRT) or liquid crystal display (LCD), to display information to the computer user. An input device 1914, including alphanumeric and other keys, may be coupled to the bus 1902 for communication of information and command selections to the processor 1904. Another type of user input device is a cursor control device, such as a mouse, trackball, or cursor directional keys, for communicating directional information and command selections to the processor 1904 and controlling cursor movement on the display 1912. This input device 1914 typically has two degrees of freedom with two axes, a first axis (i.e., x) and a second axis (i.e., y), allowing the device to specify a position in a plane. However, it should be understood that input devices 1914 considering three-dimensional (x, y, and z) cursor movement are also contemplated herein.

[0221] In accordance with a particular implementation of this teaching, the results may be provided by the computer system 1900 in response to a processor 1904 executing one or more sequences of one or more instructions contained in memory 1906. Such instructions may be read into memory 1906 from another computer-readable medium or computer-readable storage medium, such as a storage device 1910. The execution of a sequence of instructions contained in memory 1906 causes the processor 1904 to execute the process described herein. Alternatively, a hardwired circuit configuration may be used instead of, or in combination with, software instructions to implement this teaching. Thus, the implementation of this teaching is not limited to any specific combination of hardware circuit configuration and software.

[0222] As used herein, the terms “computer-readable medium” (e.g., data store, data storage device, etc.) or “computer-readable storage medium” refer to any medium involved in providing instructions to processor 1904 for execution. Such mediums can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Examples of non-volatile media include, but are not limited to, dynamic memory such as memory 1906. Examples of transmission media include, but are not limited to, coaxial cables, copper wires, and optical fibers, including wires with bus 1902.

[0223] Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, or any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tapes, any other physical media having a pattern of holes, RAM, PROMs, and EPROMs, flash EPROMs, other memory chips or cartridges, or any other tangible media that a computer can read.

[0224] In addition to computer-readable media, instructions or data may be provided as signals on a transmission medium included in a communication device or system to provide a sequence of one or more instructions to a processor 1904 of a computer system 1900 for execution. For example, a communication device may include a transceiver having signals indicating instructions and data. The instructions and data are configured to cause one or more processors to implement the functions outlined in this disclosure. Typical examples of data communication transmission connections, but not limited to these, may include telephone modem connections, wide area networks (WANs), local area networks (LANs), infrared data connections, NFC connections, and the like.

[0225] It should be understood that the flowcharts, diagrams, and accompanying disclosures described herein can be implemented using computer system 1900 as a standalone device or on a distributed network or shared computing resources such as a cloud computing network.

[0226] The methodologies described herein can be implemented by various means depending on the application. For example, these methods can be implemented in hardware, firmware, software, or any combination thereof. In the case of hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, and / or combinations thereof.

[0227] In various embodiments, the methods described herein may be implemented as firmware and / or software programs and applications written in conventional programming languages ​​such as C, C++, and Python. When implemented as firmware and / or software, the embodiments described herein may be implemented on a non-temporary computer-readable medium on which a program causing a computer to perform the methods described herein is stored. The various engines described herein may be provided on a computer system such as computer system 1900, thereby causing processor 1904 to perform the analysis and decision-making provided by these engines in accordance with instructions provided by any one or a combination thereof of user inputs provided via memory components 1906 / 1508 / 1510 and input device 1914.

[0228] While this instruction is described in relation to various embodiments, it is not intended to be limited to such embodiments. On the contrary, this instruction includes various alternatives, modifications, and equivalents, as will be understood by those skilled in the art.

[0229] In describing various embodiments, this specification may present methods and / or processes as steps in a specific sequence. However, unless a method or process depends on the specific sequence of steps described herein, the method or process should not be limited to the specific sequence of steps described herein, and those skilled in the art will readily understand that the order may be changed and still remain within the spirit and scope of various embodiments.

[0230] VI. Description of Embodiments Embodiment 1: A method for normalizing multiple libraries of DNA-containing compositions, comprising: receiving quantification information for each of the multiple libraries of DNA-containing compositions for a first selection round, wherein each library contains a DNA conjugate, and the DNA conjugate is selected by the first selection round based on its binding affinity to a target protein; and using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, wherein each DNA-containing composition in the libraries is determined to produce a corresponding preset amount of DNA after PCR for the corresponding PCR cycle number; and determining a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, wherein the corresponding determined A method for sorting libraries of DNA-containing compositions into bins using PCR cycle counts, wherein each bin contains different subsets of libraries of DNA-containing compositions determined to share a common PCR cycle count for DNA amplification, and each subset of libraries of DNA-containing compositions in the same bin shares a different common PCR cycle count than the other bins of the library; instructing a thermocycler to perform PCR simultaneously on one of the bins in the same run with the corresponding common PCR cycle count for the subsets of libraries of DNA-containing compositions in the same bin; and instructing the thermocycler to perform PCR on each of the additional bins with the corresponding common PCR cycle count so that multiple libraries of DNA-containing compositions are normalized.

[0231] Embodiment 2: The method according to Embodiment 1, wherein the DNA conjugate comprises a peptide.

[0232] Embodiment 3: The method according to Embodiment 2, wherein the peptide comprises a macrocyclic molecule.

[0233] Embodiment 4: The method according to any one of Embodiments 1 to 3, wherein the quantification information includes the cycle threshold (Ct) of quantitative PCR (qPCR).

[0234] Embodiment 5: The method according to any one of Embodiments 1 to 4, wherein at least one of the bottles contains two or more libraries of DNA-containing compositions.

[0235] Embodiment 6: The method according to any one of Embodiments 1 to 5, wherein each of the libraries of DNA-containing compositions in any one of the vials is determined to produce the same amount of amplified DNA after PCR is performed on the same vial for a corresponding number of PCR cycles.

[0236] Embodiment 7: The method according to any one of Embodiments 1 to 6, further comprising instructing a thermocycler to perform PCR simultaneously on each of the DNA-containing compositions in an additional vial with an additional corresponding common PCR cycle number to produce additional amplified DNA.

[0237] Embodiment 8: The method according to any one of Embodiments 1 to 7, further comprising correlating each vial with a corresponding PCR plate in order to perform PCR amplification on the same vial of DNA-containing composition with a corresponding common number of PCR cycles on a corresponding PCR plate.

[0238] Embodiment 9: The method according to any one of Embodiments 1 to 8, further comprising generating a forward worklist containing a first list corresponding to the DNA-containing compositions in each bin transferred from their original position on the source plate to the PCR plate in order to generate amplified DNA-containing compositions.

[0239] Embodiment 10: The method according to any one of Embodiments 1 to 9, further comprising generating a reverse worklist including a second list corresponding to amplified DNA-containing compositions returned from a PCR plate to their original positions on a source plate.

[0240] Embodiment 11: A computer program product tangibly embodied in a non-temporary machine-readable storage medium, comprising instructions configured to cause one or more data processors to perform a method for normalizing a plurality of libraries of DNA-containing compositions, wherein the method comprises: receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each library comprising a DNA conjugate, and the first selection round selecting the DNA conjugates based on their binding affinity to a target protein; and using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, such that each DNA-containing composition in the libraries is determined to produce a corresponding preset amount of DNA after PCR for the corresponding number of PCR cycles. A computer program product comprising: determining the number of ("PCR") cycles; sorting libraries of DNA-containing compositions into bins using the corresponding PCR cycle number thus determined, wherein each bin contains different subsets of libraries of DNA-containing compositions determined to share a common PCR cycle number for DNA amplification, and each subset of libraries of DNA-containing compositions in the same bin shares a different common PCR cycle number than the other bins of the library; instructing a thermocycler to simultaneously perform PCR on one of the bins in the same run with the corresponding common PCR cycle number for the subsets of libraries of DNA-containing compositions in the same bin; and instructing a thermocycler to perform PCR on each library of DNA-containing compositions in additional bins so that multiple libraries of DNA-containing compositions are normalized.

[0241] Embodiment 12: A system comprising: a data store configured to store a dataset for each selection round, each containing quantification information for each of a plurality of libraries of DNA-containing compositions, wherein each library of DNA-containing compositions contains a DNA conjugate, and each selection round selects a DNA conjugate based on its binding affinity to a target protein; one or more data processors; and a computing device communicably connected to the data store and configured to receive datasets, comprising a non-temporary computer-readable storage medium, which, when executed on one or more data processors, causes one or more data processors to perform a method for normalizing the plurality of libraries of DNA-containing compositions, wherein the method is data A system comprising: a computing device that sorts libraries of DNA-containing compositions into bins using a set, wherein each bin contains a different subset of libraries of DNA-containing compositions determined to share a common number of PCR cycles for DNA amplification using quantification information, and each subset of libraries of DNA-containing compositions in the same bin shares a different common number of PCR cycles than the other bins of the library; and a thermocycler configured to simultaneously perform PCR on each library of DNA-containing compositions in additional bins with a common number of PCR cycles corresponding to the DNA-containing compositions in the same bin, in the same run, and so that multiple libraries of DNA-containing compositions are normalized.

[0242] Embodiment 13: The system according to Embodiment 12, further comprising a liquid handler configured to transfer each library in the same vial from a source plate to a PCR plate, wherein each library in the same vial is amplified by PCR on the PCR plate with a common number of PCR cycles for the same vial to generate amplified DNA.

[0243] Embodiment 14: The system according to Embodiment 13, wherein the liquid handler is further configured to provide all the amplified DNA in the vials for an additional selection round.

[0244] Embodiment 15: The system according to any one of embodiments 11 to 14, further comprising a quantitative PCR unit configured to quantify each of the libraries before and after each selection round.

[0245] Embodiment 16: The system according to any one of Embodiments 11 to 15, wherein each of the libraries of DNA-containing compositions in any one of the bins is determined to produce the same amount of amplified DNA after PCR is performed on the same bin for a corresponding number of PCR cycles.

[0246] Embodiment 17: The system according to any one of Embodiments 11 to 16, wherein the method further comprises using quantified information to determine a polymerase chain reaction ("PCR") cycle count specific to each library, and the DNA-containing composition of each library is determined to produce a corresponding preset amount of DNA after PCR is performed for the corresponding number of PCR cycles.

[0247] Embodiment 18: The system according to any one of Embodiments 11 to 17, further comprising correlating each vial with a corresponding PCR plate in order to perform PCR amplification on the same vial of DNA-containing composition with a corresponding common number of PCR cycles on the corresponding PCR plate.

[0248] Embodiment 19: The system according to any one of Embodiments 11 to 18, further comprising generating a forward worklist including a first list of DNA-containing compositions in each bin transferred from their original position on the source plate to the PCR plate for performing PCR with a corresponding common number of PCR cycles to generate amplified DNA.

[0249] Embodiment 20: The system according to any one of Embodiments 11 to 19, further comprising generating a reverse worklist containing a second list corresponding to amplified DNA to be returned from the PCR plate to its original position on the source plate.

[0250] Embodiment 21: A method for identifying candidate DNA conjugates for binding affinity to a target protein, comprising: receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, wherein each library contains a DNA conjugate, and the first selection round selects DNA conjugates based on their binding affinity to a target protein; using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each library, wherein the DNA-containing composition of each library is determined to produce a relevant preset amount of DNA after PCR for the corresponding PCR cycle number; and sorting the libraries of DNA-containing compositions into bins using the PCR cycle numbers thus determined, DN A method comprising: sorting libraries of DNA-containing compositions into bins, each bin containing different subsets of libraries of DNA-containing compositions determined to share a common number of PCR cycles for amplification, such that different subsets of libraries of DNA-containing compositions in the same bin share a different common number of PCR cycles than other bins of the library; instructing a thermocycler to simultaneously perform PCR on one of the bins in the same run for the subsets of libraries of DNA-containing compositions in the same bin, with the corresponding common number of PCR cycles; instructing the thermocycler to perform PCR on each of the additional bins with the corresponding common number of PCR cycles so that the multiple libraries of DNA-containing compositions are normalized and amplified DNA is produced for each library; and instructing a sequencer to identify candidate DNA conjugates for the binding affinity from the amplified DNA to a target protein for each library.

[0251] Embodiment 22: The method according to Embodiment 21, wherein the DNA conjugate comprises a peptide.

[0252] Embodiment 23: The method according to Embodiment 22, wherein the peptide comprises a macrocyclic peptide.

[0253] Embodiment 24: The method according to any one of Embodiments 21 to 23, wherein the quantification information includes a cycle threshold (Ct) for quantitative PCR (qPCR).

[0254] Embodiment 25: The method according to any one of Embodiments 21 to 24, wherein each library of a plurality of DNA-containing compositions is stored in an individual space on a source plate.

[0255] Embodiment 26: The method according to any one of Embodiments 21 to 25, wherein each of the libraries of one of the vials of DNA-containing compositions is determined to produce the same amount of DNA after PCR is performed on the same vial for a corresponding number of PCR cycles.

[0256] Embodiment 27: The method according to any one of Embodiments 21 to 26, wherein each vial is determined to produce the same amount of DNA after PCR has been performed for a corresponding number of PCR cycles.

[0257] Embodiment 28: The method according to any one of Embodiments 21 to 27, further comprising correlating each vial with a corresponding PCR plate in order to perform PCR amplification on the same vial of DNA-containing composition with a corresponding common number of PCR cycles on the corresponding PCR plate.

[0258] Embodiment 29: The method according to any one of Embodiments 21 to 28, further comprising generating a forward worklist including a first list of DNA-containing compositions in each bin transferred from their original position on the source plate to the PCR plate for performing PCR with a corresponding common number of PCR cycles to generate amplified DNA.

[0259] Embodiment 30: The method according to any one of Embodiments 21 to 29, further comprising generating a reverse work list including a second list corresponding to the amplified DNA returned from the PCR plate to the original position of the source plate.

[0260] Embodiment 31: The method according to any one of Embodiments 21 to 30, further comprising repeating steps of selecting a DNA-containing composition from each of the libraries for binding affinity to a target protein and amplifying the DNA-containing composition thus selected.

[0261] Embodiment 32: The method according to any one of Embodiments 21 to 31, comprising instructing a sequencer to identify candidate DNA conjugates for binding affinity to a target protein and instructing the sequencer to sequence the DNA in the candidate DNA conjugates.

[0262] Embodiment 33: The method according to any one of Embodiments 21 to 32, further comprising generating a new library of DNA-containing compositions, including performing in vitro translation on each of the libraries of the source to produce new peptides and performing in vitro reverse transcription on each of the libraries of the source plate to generate a new peptide library of DNA-containing compositions.

[0263] Embodiment 34: The method according to any one of Embodiments 21 to 33, further comprising quantifying each of the libraries.

[0264] Embodiment 35: The method according to any one of Embodiments 21 to 34, further comprising quantifying each of the libraries using quantitative PCR (qPCR).

[0265] Embodiment 36: The method according to any one of Embodiments 21 to 35, further comprising generating a heat map for visualizing the quantification information of each library.

[0266] Embodiment 37: A computer program product tangibly embodied in a non - transitory machine - readable storage medium, including instructions configured to cause one or more data processors to execute a method for monitoring the quantification information of each of a plurality of libraries to detect target bindings on a graphical user interface, the method comprising: receiving quantification information for each of a plurality of libraries of DNA - containing compositions for a first selection round, each library including a DNA conjugate, and the DNA conjugate being selected based on binding affinity to a target protein by the first selection round; using the quantification information to determine a polymerase chain reaction ( "PCR") cycle number specific to each library, such that each DNA - containing composition of the library is determined to produce a preset amount of DNA associated after performing PCR with the corresponding PCR cycle number; sorting the library of DNA - containing compositions into bins, each bin including a different subset of the library of DNA - containing compositions determined to share a common PCR cycle number, and different subsets of the library of DNA - containing compositions within the same bin sharing a common PCR cycle number different from that of the other bins of the library; instructing a thermocycler to simultaneously perform PCR on one of the bins for the DNA - containing compositions of the same bin with the corresponding common PCR cycle number in the same run to generate amplified DNA - containing compositions; and identifying candidate DNA conjugates for binding affinity to the target protein from the amplified DNA - containing compositions.

[0267] Embodiment 38: A system comprising: a data store configured to store a dataset for each selection round containing quantification information for each of a plurality of libraries of DNA-containing compositions, wherein each library of DNA-containing compositions comprises a DNA conjugate, and by each selection round, a DNA conjugate is selected based on its binding affinity to a target protein; one or more data processors; and a computing device configured to receive datasets, which is communicably connected to the data store and comprises a non-temporary computer-readable storage medium containing instructions, wherein, when an instruction is executed on one or more data processors, the one or more data processors execute a method for identifying candidate DNA conjugates for their binding affinity to a target protein, wherein the method uses the quantification information to determine the number of polymerase chain reaction ("PCR") cycles specific to each of the libraries, and each DNA-containing composition of the libraries corresponds to the number of PCR cycles A system comprising: determining a specific polymerase chain reaction ("PCR") cycle count for each library, which is determined to produce a relevant pre-set amount of DNA after performing PCR on a number of libraries; sorting libraries of DNA-containing compositions into bins using the PCR cycle counts thus determined, wherein each bin contains a different subset of libraries of DNA-containing compositions which is determined to share a common PCR cycle count, and each subset of libraries of DNA-containing compositions in the same bin shares a different common PCR cycle count than that of the other bins of the library; instructing a thermocycler to simultaneously perform PCR on one of the bins in the same run with a common PCR cycle count corresponding to the DNA-containing compositions in the same bin, in order to produce amplified DNA-containing compositions; and identifying candidate DNA conjugates from the amplified DNA-containing compositions for binding affinity to a target protein.

[0268] Embodiment 39: The system according to Embodiment 38, further comprising a thermocycler configured to perform PCR simultaneously on one of the vials in the same run, with a common number of PCR cycles corresponding to the DNA-containing composition in the same vial.

[0269] Embodiment 40: The system according to Embodiment 38 or 39, further comprising a quantitative PCR unit configured to quantify each of the libraries before and after each selection round.

[0270] Embodiment 41: A method for monitoring quantification information of multiple libraries of DNA-containing compositions for detecting target binding, comprising: a) receiving quantification information for each of multiple libraries of DNA-containing compositions for a first selection round, wherein each library contains a DNA conjugate, and the DNA conjugate is selected by the first selection round based on its binding affinity to a target protein; b) generating a first window in a graphical user interface that displays the quantification information for each library for the first selection round; and c) repeating a) to b) to generate additional windows over a plurality of subsequent selection rounds, wherein each additional window displays the quantification information for each library for each of the subsequent selection rounds, so that the quantification information for each library of DNA-containing compositions for each round is monitored.

[0271] Embodiment 42: The method according to Embodiment 41, wherein the quantification information for each of the DNA-containing compositions of a) and c) includes a cycle threshold (Ct) for quantitative PCR (qPCR) input molecules, positive molecules, negative molecules, or any combination thereof.

[0272] Embodiment 43: The method according to Embodiment 41 or 42, wherein the quantification information for each of the DNA-containing compositions library of a) and c) includes the percentage of positive molecules relative to the input molecule.

[0273] Embodiment 44: The method according to any one of Embodiments 41 to 43, further comprising displaying a selected window that displays quantification information for a selected round while concealing other windows.

[0274] Embodiment 45: The method according to any one of Embodiments 41 to 44, wherein the quantification information for each library of the DNA-containing compositions of a) and c) is obtained from data scraping of the qPCR data of each library.

[0275] Embodiment 46: The method according to any one of Embodiments 41 to 45, wherein the DNA conjugate comprises a peptide.

[0276] Embodiment 47: The method according to any one of Embodiments 41 to 46, wherein the peptide comprises a macrocyclic molecule.

[0277] Embodiment 48: The method according to any one of embodiments 41 to 47, wherein the first window and additional windows include a first graphical element in multiple locations, and each of the first graphical elements is configured to represent each of the libraries.

[0278] Embodiment 49: The method according to any one of embodiments 41 to 48, wherein each library is located in one of the individual spaces of the source plate, and each of the first graphical elements is configured to correspond horizontally and vertically to each of the individual spaces of the source plate.

[0279] Embodiment 50: The method according to any one of embodiments 41 to 49, wherein each of the first graphical elements is positioned in the same location across different windows to represent the same well in the source plate.

[0280] Embodiment 51: The method according to any one of Embodiments 41 to 50, wherein the first window and additional windows include a second graphical element configured to visually distinguish quantification information from different libraries.

[0281] Embodiment 52: The method according to any one of Embodiments 41 to 51, wherein the second graphical element includes a color or a number.

[0282] Embodiment 53: The method according to any one of Embodiments 41 to 52, wherein the second graphical element includes a number.

[0283] Embodiment 54: The method according to any one of Embodiments 41 to 53, further comprising updating the graphical user interface to display a new window when a new selection round is selected by the user.

[0284] Embodiment 55: The method according to any one of Embodiments 41 to 54, further comprising displaying a first window and an additional window within the same graphical user interface such that a round-to-round comparison is generated.

[0285] Embodiment 56: The method according to any one of Embodiments 41 to 55, wherein the first window and the additional window include a third graphical element configured to set a filter for displaying quantification information of each library selected by the filter.

[0286] Embodiment 57: The method according to any one of Embodiments 41 to 56, wherein the filter is a user-selected scaffold, a user-selected codon, or a user-selected target.

[0287] Embodiment 58: The method according to any one of Embodiments 41 to 57, further comprising plotting a round-to-round comparison for each of the libraries of the DNA-containing composition on the graphical user interface.

[0288] Embodiment 59: A computer program product tangibly embodied in a non-temporary machine-readable storage medium, comprising instructions configured to cause one or more data processors to perform a method for monitoring quantification information of libraries and detecting target binding in a graphical user interface, the method comprising: a) receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, wherein each library of DNA-containing compositions contains a DNA conjugate, and the first selection round selects a DNA conjugate based on its binding affinity to a target protein; b) displaying a first window in a graphical user interface containing the quantification information for each of the libraries of DNA-containing compositions after the first selection round; and c) repeating a) to b) to generate additional windows over a plurality of subsequent selection rounds, wherein each additional window displays the quantification information for each library for each of the subsequent selection rounds, such that the quantification information for each library of DNA-containing compositions for each round is monitored.

[0289] Embodiment 60: A system comprising: a data store configured to store a dataset for each selection round, each containing quantification information for each of a plurality of libraries of DNA-containing compositions, wherein each library of DNA-containing compositions contains a DNA conjugate, and by each selection round, a DNA conjugate is selected based on its binding affinity to a target protein; one or more data processors; and a computing device communicably connected to the data store and configured to receive datasets, comprising a non-temporary computer-readable storage medium, which, when executed on one or more data processors, includes instructions causing one or more data processors to perform a method for displaying quantification information for each of the libraries of DNA-containing compositions, wherein the method includes generating a graphical user interface, which includes a window selected to display quantification information for each of the libraries of DNA-containing compositions for any selection round selected to be displayed.

[0290] Embodiment 61: The system according to Embodiment 60, further comprising a liquid handler configured to transfer each library from a source plate to a PCR plate for PCR amplification.

[0291] Embodiment 62: The system according to Embodiment 61, wherein the liquid handler is further configured to normalize each of the libraries between each of two consecutive selection rounds.

[0292] Embodiment 63: The system according to any one of embodiments 60 to 62, further comprising a thermocycler configured to amplify each library after each selected round.

[0293] Embodiment 64: The system according to any one of embodiments 60 to 63, further comprising a quantitative PCR unit configured to quantify each library before and after each selection round.

[0294] Embodiment 65. A method for normalizing a polymerase chain reaction (PCR) amplification process for multiple samples containing DNA, comprising: identifying cycle data for performing a PCR amplification process for multiple samples, wherein the cycle data includes a corresponding number of cycles for each sample of the multiple samples; sorting the multiple samples into multiple bins based on the cycle data such that the variation in the number of cycles between bins of the multiple bins is reduced; assigning a bin cycle number to each bin of the multiple bins, wherein the bin cycle number is unique to each bin of the multiple bins; generating identification information for the multiple bins; and generating an output for performing PCR amplification of multiple samples using the multiple bins and the bin cycle numbers for each bin of the multiple bins.

[0295] Embodiment 66. The method according to Embodiment 65, wherein multiple samples have varying amounts of DNA, and after the PCR amplification process is performed so that the multiple samples become amplified multiple samples, the amplified multiple samples have a normalized amount of DNA.

[0296] Embodiment 67. The method according to Embodiment 65 or Embodiment 66, wherein generating identification information includes generating a bin identifier for each bin in a plurality of bins.

[0297] Embodiment 68. The method according to any one of embodiments 65 to 67, wherein generating an output is to generate a forward worklist for one of a plurality of bins, the forward worklist comprising the sequence in which a set of samples in a bin is transferred from a source plate to the corresponding PCR plate in the bin.

[0298] Embodiment 69. The method according to any one of embodiments 65-68, wherein the output further includes instructions for a thermocycler for performing a PCR amplification process using a set of PCR plates.

[0299] Embodiment 70. The method according to any one of embodiments 65 to 69, wherein assigning a bin cycle count involves generating a bin cycle count for one of several bins using a group of cycle counts consisting of the highest cycle count for a set of samples in a bin, the average cycle count for a set of samples, the median cycle count for a set of samples, and the sum of the highest cycle count and a selected cycle count.

[0300] Embodiment 71. The method according to Embodiment 70, wherein the selected number of cycles is changed from a first run of the PCR amplification process to a second run of the PCR amplification process.

[0301] Embodiment 72. The method according to any one of Embodiments 65 to 71, wherein the sorting is performed by converting any number of non-integer cycles in the cycle data to an integer number of cycles to form modified cycle data; assigning a unique integer number of cycles in the modified cycle data that falls within a selected range of cycle numbers to N bins; and merging adjacent bins of the N bins using a distance equation until a target number of bins is reached, wherein the target number of bins forms at least a portion of the bins.

[0302] Embodiment 73. The method according to any one of Embodiments 65 to 71, wherein identifying cycle data is receiving initial cycle data from a quantitative PCR (qPCR) system, wherein the initial cycle data includes the initial cycle count for each of a plurality of samples, and modifying the initial cycle count for at least one of the plurality of samples to generate cycle data.

[0303] Embodiment 74. The method according to Embodiment 73, wherein the initial number of cycles for one of the multiple samples is an undetermined value, and the modification includes changing the initial number of cycles for the sample from an undetermined value to a pre-selected number of cycles.

[0304] Embodiment 75. The method according to any one of embodiments 73 to 74, wherein the modification includes at least one of the following: adding two cycles to the initial number of cycles for each sample of a plurality of samples, or converting each non-integer number of cycles to an integer number of cycles.

[0305] Embodiment 76. The method according to any one of Embodiments 65-71 or 72-75, wherein the sorting includes distributing multiple samples into multiple bins based on a selected range of the number of cycles in the cycle data.

[0306] Embodiment 77. The method of Embodiment 76, wherein the distribution includes allocating a portion of several samples to a portion of several bins at corresponding cycle counts outside a selected range of cycle counts, and substantially uniformly distributing the remaining portions of several samples among the remaining portions of several bins at corresponding cycle counts within a selected range of cycle counts.

[0307] Embodiment 78. The method according to any one of Embodiments 65-71 or 72-75, wherein the sorting comprises converting each non-integer number of cycles in the cycle data to an integer number of cycles to form corrected cycle data, and distributing a plurality of samples substantially uniformly into a plurality of bins based on a selected range of cycle numbers in the corrected cycle data.

[0308] Embodiment 79. The method according to any one of embodiments 65 to 78, wherein generating an output includes generating a transfer output for use in transferring a set of samples in each of a set of bins to the corresponding PCR plates of a set of PCR plates, using identification information.

[0309] Embodiment 80. The method according to any one of Embodiments 65 to 71, wherein the plurality of samples have a plurality of corresponding cycle counts, and the sorting is to allocate a first portion of the plurality of samples having a first set of cycle counts less than a plurality of corresponding selected low cycle counts to the first bin of the plurality of bins, a second portion of the plurality of samples having a second set of cycle counts greater than a selected high number to the last bin of the plurality of bins, and the remaining portion of the plurality of samples to a set of bins between the first bin and the last bin.

[0310] Embodiment 81. The method according to any one of Embodiments 65 to 71, wherein multiple samples have multiple corresponding cycle counts, and the sorting further comprises identifying a distribution of multiple corresponding cycle counts.

[0311] Embodiment 82. The method according to Embodiment 81, wherein identifying a distribution is identifying a histogram distribution of a plurality of corresponding cycle numbers, wherein 60% to 100% of the plurality of corresponding cycle numbers are between a selected low cycle number and a selected high cycle number and within a selected range including them.

[0312] Embodiment 83. The method according to Embodiment 82, wherein the selected low cycle count is 4 cycles and the selected high cycle count is 24 cycles.

[0313] Embodiment 84. The method according to Embodiment 82 or Embodiment 83, wherein the sorting includes assigning any sample from a plurality of samples to the first bin of a plurality of bins at a corresponding number of cycles below the selected low number of cycles, and assigning any sample from a plurality of samples to the last bin of a plurality of bins at a corresponding number of cycles above the selected high number of cycles.

[0314] Embodiment 85. The method according to Embodiment 84, further comprising sorting by distributing the remaining portions of multiple samples among a set of bottles between the first and last bottles.

[0315] Embodiment 86. The method according to Embodiment 82 or Embodiment 83, wherein 100% of a plurality of corresponding cycle counts are within a selected range, and the sorting of a plurality of samples into a plurality of bins is biased to distribute the plurality of samples among the plurality of bins so as to provide more bin separation between lower cycle counts compared to higher cycle counts.

[0316] Embodiment 87. The method according to any one of Embodiments 65 to 71, wherein the sorting includes distributing multiple samples into multiple bins based on a selected range of cycle counts in cycle data, and modifying the distribution of multiple samples within the multiple bins such that any samples of the multiple samples with corresponding cycle counts associated with the same integer value are grouped together in the same bin.

[0317] Embodiment 88. The method according to Embodiment 87, wherein multiple samples have multiple corresponding cycle counts, and two of the multiple corresponding cycle counts are associated with the same integer value if they contain an integer where each of the two cycle counts is the same integer value.

[0318] Embodiment 89. The method according to Embodiment 87, wherein multiple samples have multiple corresponding cycle counts, and two of the multiple corresponding cycle counts are associated with the same integer value if each of the two cycle counts is rounded up to the same integer value.

[0319] Embodiment 90. The method according to any one of Embodiments 65 to 71, wherein the sorting is biased to provide more bin separation between a portion of a set of cycles that lies within one standard deviation of the mean of a set of cycles, compared to another portion of a set of cycles that lies outside one standard deviation of the mean, based on the distribution of a set of cycles.

[0320] Embodiment 91. The method according to any one of Embodiments 65 to 90, further comprising transferring a set of samples from each of multiple vials to a corresponding PCR plate of a set of PCR plates based on the output, and performing a PCR amplification process using the set of PCR plates.

[0321] Embodiment 92. The method according to any one of Embodiments 65 to 91, wherein identifying the cycle data includes receiving the cycle data from a quantitative PCR (qPCR) system.

[0322] Embodiment 93. A system comprising one or more data processors and a non-temporary computer-readable storage medium containing instructions that, when executed on the one or more data processors, causes the one or more data processors to execute some or all of the methods disclosed in Embodiments 1 to 10, 21 to 36, 41 to 58, and 65 to 92.

[0323] Embodiment 94. A computer program product tangibly embodied in a temporary machine-readable storage medium, comprising instructions configured to cause one or more data processors to perform all or part of one or more methods described in any one of claims 1 to 10, 21 to 36, 41 to 58, and 65 to 92.

[0324] VII. Additional Considerations The headings and subheadings between sections and subsections in this document are included solely to improve readability and do not imply that features cannot be combined across sections and subsections. Therefore, sections and subsections do not describe separate embodiments.

[0325] Some embodiments of this disclosure include a system comprising one or more data processors. In some embodiments, the system includes a non-temporary computer-readable storage medium comprising instructions, wherein when the instructions are executed on one or more data processors, the one or more data processors cause one or more data processors to execute some or all of one or more of the methods and / or some or all of one or more processes disclosed herein. Some embodiments of this disclosure include a computer program product tangibly embodied in a non-temporary machine-readable storage medium comprising instructions configured to cause one or more data processors to execute some or all of one or more of the methods and / or some or all of one or more processes disclosed herein.

[0326] The subsequent description provides only preferred exemplary embodiments and is not intended to limit the scope, applicability, or configuration of the Disclosure. Rather, the subsequent description of preferred exemplary embodiments provides a possible description for implementing various embodiments for those skilled in the art. It will be understood that various modifications can be made to the function and arrangement of the elements without departing from the spirit and scope set forth in the appended claims.

[0327] Specific details are given in the following description to provide a complete understanding of the embodiments. However, it will be understood that embodiments can be carried out without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form so as not to obscure the embodiments with unnecessary detail. In other examples, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.

[0328] In describing various embodiments, this specification may present methods and / or processes as a specific set of steps. However, unless a method or process depends on a specific sequence of steps described herein, the method or process should not be limited to that specific sequence of steps, and those skilled in the art will readily understand that the order may be changed and still remain within the spirit and scope of various embodiments.

[0329] All references cited herein, including patent applications, patent publications, and UniProtKB / Swiss-Prot accession numbers, are incorporated herein by reference in their entirety, as if each individual reference were specifically and individually indicated to be incorporated by reference.

Claims

1. 1. A method for normalizing multiple libraries of DNA-containing compositions, comprising: receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each of the libraries comprising DNA conjugates, the first selection round selecting the DNA conjugates based on their binding affinity to a target protein; using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, where the DNA-containing composition of each of the libraries is determined to produce an associated pre-determined amount of DNA after performing PCR at a corresponding number of PCR cycles; using the corresponding PCR cycle numbers so determined, sorting the library of DNA-containing compositions into bins, each bin containing a different subset of the library of DNA-containing compositions determined to share a common PCR cycle number for DNA amplification, each subset of the library of DNA-containing compositions within the same bin sharing a common PCR cycle number that is different from other bins of the library; directing a thermocycler to simultaneously perform PCR on one of the bins in the same run with a corresponding common number of PCR cycles for a subset of the library of DNA-containing compositions of the same bin; directing the thermocycler to perform PCR on each of the additional bins at a corresponding common number of PCR cycles such that the multiple libraries of DNA-containing compositions are normalized; A method comprising:

2. The method of claim 1 , wherein the DNA conjugate comprises a peptide.

3. The method of claim 2 , wherein the peptide comprises a macrocycle.

4. 2. The method of claim 1, wherein the quantification information comprises a cycle threshold (Ct) value for quantitative PCR (qPCR).

5. The method of claim 1 , wherein at least one of the bins contains two or more libraries of the DNA-containing compositions.

6. 2. The method of claim 1, wherein each of the libraries of DNA-containing compositions in any one of the bins is determined to produce substantially the same amount of amplified DNA after performing PCR on the same bin with a corresponding number of PCR cycles.

7. 2. The method of claim 1, further comprising instructing a thermocycler to simultaneously perform PCR on each of the additional bins of DNA-containing compositions at additional corresponding common numbers of PCR cycles to produce additional amplified DNA.

8. 2. The method of claim 1, further comprising correlating each bin with a corresponding PCR plate to perform PCR on DNA-containing compositions of the same bin at a corresponding common number of PCR cycles on the corresponding PCR plate.

9. 2. The method of claim 1, further comprising generating a forward worklist including a first list corresponding to the DNA-containing composition of each bin to be transferred from its original position on the source plate to the PCR plate to generate an amplified DNA-containing composition.

10. 10. The method of claim 9, further comprising generating a reverse worklist comprising a second list corresponding to the amplified DNA-containing compositions that are transferred from the PCR plate back to their original positions on a source plate.

11. 1. A computer program product tangibly embodied in a non-transitory machine-readable storage medium comprising instructions configured to cause one or more data processors to execute a method for normalizing a plurality of libraries of DNA-containing compositions, the method comprising: receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each of the libraries comprising DNA conjugates, the first selection round selecting the DNA conjugates based on their binding affinity to a target protein; using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, where the DNA-containing composition of each of the libraries is determined to produce an associated pre-determined amount of DNA after performing PCR at a corresponding number of PCR cycles; using the corresponding PCR cycle numbers so determined, sorting the library of DNA-containing compositions into bins, each bin containing a different subset of the library of DNA-containing compositions determined to share a common PCR cycle number for DNA amplification, each subset of the library of DNA-containing compositions within the same bin sharing a common PCR cycle number that is different from other bins of the library; directing a thermocycler to simultaneously perform PCR on one of the bins in the same run with a corresponding common number of PCR cycles for a subset of the library of DNA-containing compositions of the same bin; directing the thermocycler to perform PCR on each library of DNA-containing compositions in additional bins such that the multiple libraries of DNA-containing compositions are normalized; 2. A computer program product comprising:

12. 1. A system comprising: a data store configured to store a dataset including quantification information for each of a plurality of libraries of DNA-containing compositions for each selection round, each of the libraries of DNA-containing compositions including a DNA conjugate, and each selection round selecting the DNA conjugate based on its binding affinity to a target protein; one or more data processors; a computing device communicatively connected to the data store and configured to receive the dataset, the computing device comprising a non-transitory computer-readable storage medium comprising instructions that, when executed on the one or more data processors, cause the one or more data processors to perform a method for normalizing a plurality of libraries of DNA-containing compositions, the method comprising: using the data set to sort the library of DNA-containing compositions into bins, each bin comprising a different subset of the library of DNA-containing compositions that are determined to share a common number of PCR cycles for DNA amplification using the quantification information, each subset of the library of DNA-containing compositions within the same bin sharing a common number of PCR cycles that is different from that of other bins of the library. a computing device including: a thermocycler configured to simultaneously perform PCR on one of the bins in the same run with a corresponding common number of PCR cycles for the DNA-containing compositions in the same bin, and to perform PCR on each library of DNA-containing compositions in additional bins such that the multiple libraries of DNA-containing compositions are normalized; A system comprising:

13. 13. The system of claim 12, further comprising a liquid handler configured to transfer each library in the same bin from the source plate to a PCR plate, wherein each library in the same bin is amplified by PCR on the PCR plate with a common number of PCR cycles for the same bin to generate amplified DNA.

14. 14. The system of claim 13, wherein the liquid handler is further configured to subject the amplified DNA in all of the bottles to an additional round of selection.

15. The system of claim 12, wherein the system further comprises a quantitative PCR unit configured to quantify each of the libraries before and after each selection round.

16. The system of claim 12, wherein each of the libraries of DNA-containing compositions in any one of the bins is determined to produce substantially identical amounts of amplified DNA after performing PCR on the same bin with a corresponding number of PCR cycles.

17. 13. The system of claim 12, wherein the method further comprises using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific for each library, wherein the DNA-containing composition of each library is determined to produce an associated pre-set amount of DNA after performing PCR at a corresponding number of PCR cycles.

18. 13. The system of claim 12, wherein the method further comprises correlating each bin with a corresponding PCR plate to perform PCR on DNA-containing compositions of the same bin at a corresponding common number of PCR cycles on the corresponding PCR plate.

19. The system of claim 12, wherein the method further comprises generating a forward worklist including a first list corresponding to DNA-containing compositions of each bin to be transferred from an original position of the source plate to a PCR plate for performing PCR with a corresponding common number of PCR cycles to generate amplified DNA.

20. 20. The system of claim 19, wherein the method further comprises generating a reverse worklist comprising a second list corresponding to the amplified DNA that is transferred from the PCR plate back to its original position on the source plate.

21. 1. A method for identifying a candidate DNA conjugate for binding affinity to a target protein, comprising: receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each of the libraries comprising DNA conjugates, the first selection round selecting the DNA conjugates based on their binding affinity to a target protein; using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific for each library, where the DNA-containing composition of each library is determined to produce an associated pre-determined amount of DNA after PCR is performed at a corresponding number of PCR cycles; using the PCR cycle numbers so determined, sorting the library of DNA-containing compositions into bins, each bin containing a different subset of the library of DNA-containing compositions determined to share a common PCR cycle number for DNA amplification, each different subset of the library of DNA-containing compositions within the same bin sharing a common PCR cycle number that is different from other bins of the library; directing a thermocycler to simultaneously perform PCR on one of the bins in the same run with a corresponding common number of PCR cycles for a subset of the library of DNA-containing compositions of the same bin; directing the thermocycler to perform PCR on each of the additional bins at a corresponding common number of PCR cycles such that the multiple libraries of DNA-containing compositions are normalized to generate amplified DNA for each library; directing a sequencer to identify, for each library, candidate DNA conjugates from said amplified DNA for binding affinity to said target protein; A method comprising:

22. The method of claim 21 , wherein the DNA conjugate comprises a peptide.

23. 23. The method of claim 22, wherein the peptide comprises a macrocyclic peptide.

24. 22. The method of claim 21, wherein the quantification information comprises a cycle threshold (Ct) value for quantitative PCR (qPCR).

25. 22. The method of claim 21, wherein each library of the plurality of DNA-containing compositions is stored in an individual space of a source plate.

26. 22. The method of claim 21, wherein each of the libraries of DNA-containing compositions of one of the bins is determined to produce similar amounts of DNA after performing PCR on the same bin with corresponding numbers of PCR cycles.

27. 22. The method of claim 21, wherein each bin is determined to produce a similar amount of DNA after performing PCR with a corresponding number of PCR cycles.

28. 22. The method of claim 21, further comprising correlating each bin with a PCR plate to perform PCR on DNA-containing compositions of the same bin at a corresponding common number of PCR cycles on the PCR plate.

29. 22. The method of claim 21, further comprising generating a forward worklist including a first list corresponding to the DNA-containing composition of each bin to be transferred from its original position on the source plate to the PCR plate for performing PCR with a corresponding common number of PCR cycles to generate amplified DNA.

30. 30. The method of claim 29, further comprising generating a reverse worklist comprising a second list corresponding to the amplified DNA that is transferred from the PCR plate back to its original position on the source plate.

31. An additional selection round will selecting a DNA-containing composition from each of said libraries for binding affinity to said target protein; amplifying such selected DNA-containing compositions; 22. The method of claim 21, comprising repeating:

32. 22. The method of claim 21 , wherein instructing the sequencer to identify the candidate DNA conjugates for binding affinity to the target protein comprises instructing the sequencer to sequence DNA in the candidate DNA conjugates.

33. generating a new library of DNA-containing compositions after each selection round, performing in vitro translation for each of said libraries in the source plate to produce new peptides; performing in vitro reverse transcription on each of said libraries in said source plate to generate a new library of DNA-containing compositions.

22. The method of claim 21 further comprising:

34. 22. The method of claim 21, further comprising quantifying each of the libraries.

35. 22. The method of claim 21, further comprising quantifying each of the libraries using quantitative PCR (qPCR).

36. 22. The method of claim 21, further comprising generating a heat map for visualizing the quantification information for each of the libraries.

37. 1. A computer program product tangibly embodied in a non-transitory machine-readable storage medium, the computer program product comprising instructions configured to cause one or more data processors to execute a method for monitoring quantification information of each of a plurality of libraries to detect target binding on a graphical user interface, the method comprising: receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each of the libraries comprising DNA conjugates, the first selection round selecting the DNA conjugates based on their binding affinity to a target protein; using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, where the DNA-containing composition of each of the libraries is determined to produce an associated pre-determined amount of DNA after performing PCR at a corresponding number of PCR cycles; using the PCR cycle numbers so determined, sorting the library of DNA-containing compositions into bins, each bin containing a different subset of the library of DNA-containing compositions determined to share a common PCR cycle number, each different subset of the library of DNA-containing compositions within the same bin sharing a common PCR cycle number that is different from other bins of the library; directing a thermocycler to simultaneously perform PCR on one of the bins, in the same run, with a corresponding common number of PCR cycles for the DNA-containing compositions of the same bin to generate an amplified DNA-containing composition; identifying candidate DNA conjugates from the amplified DNA-containing composition for binding affinity to the target protein; 2. A computer program product comprising:

38. 1. A system comprising: a data store configured to store a dataset including quantification information for each of a plurality of libraries of DNA-containing compositions for each selection round, each of the libraries of DNA-containing compositions including a DNA conjugate, and each selection round selecting the DNA conjugate based on its binding affinity to a target protein; one or more data processors; a computing device communicatively connected to the data store and configured to receive the dataset, the computing device comprising a non-transitory computer readable storage medium comprising instructions that, when executed on the one or more data processors, cause the one or more data processors to perform a method for identifying candidate DNA conjugates for binding affinity to a target protein, the method comprising: using the quantification information to determine a polymerase chain reaction ("PCR") cycle number specific to each of the libraries, where the DNA-containing composition of each of the libraries is determined to produce an associated pre-determined amount of DNA after performing PCR at a corresponding number of PCR cycles; using the PCR cycle numbers so determined, sorting the library of DNA-containing compositions into bins, each bin containing a different subset of the library of DNA-containing compositions determined to share a common PCR cycle number, each subset of the library of DNA-containing compositions within the same bin sharing a common PCR cycle number that is different from other bins of the library; directing a thermocycler to simultaneously perform PCR on one of the bins, in the same run, with a corresponding common number of PCR cycles for the DNA-containing composition of the same bin to generate an amplified DNA-containing composition; identifying candidate DNA conjugates from the amplified DNA-containing composition for binding affinity to the target protein; a computing device, A system comprising:

39. 39. The system of claim 38, further comprising a thermocycler configured to simultaneously perform PCR in the same run on one of the bins with a corresponding common number of PCR cycles for DNA-containing compositions of the same bin.

40. 40. The system of claim 38, wherein the system further comprises a quantitative PCR unit configured to quantify each of the libraries before and after each selection round.

41. 1. A method for monitoring quantification information of multiple libraries of DNA-containing compositions to detect target binding, comprising: a) receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each of the libraries comprising DNA conjugates, and wherein the first selection round selects the DNA conjugates based on their binding affinity to a target protein; b) generating within a graphical user interface a first window displaying said quantification information for each of said libraries for said first selection round; c) repeating a)-b) to generate additional windows over multiple subsequent selection rounds, each of the additional windows displaying quantification information for each of the libraries for each subsequent selection round such that quantification information for the DNA-containing composition of each of the libraries for each round is monitored; A method comprising:

42. 42. The method of claim 41 , wherein the quantification information for each of the libraries of DNA-containing compositions of a) and c) comprises cycle threshold (Ct) values ​​for quantitative PCR (qPCR) input molecules, positive molecules, negative molecules, or any combination thereof.

43. 42. The method of claim 41, wherein the quantitative information for each of the libraries of DNA-containing compositions of a) and c) comprises a percentage of positive molecules relative to input molecules.

44. 42. The method of claim 41, further comprising displaying a selected window displaying quantification information for a selected round while hiding other windows.

45. 42. The method of claim 41 , wherein the quantification information for each of the libraries of DNA-containing compositions of a) and c) is obtained from data scraping of qPCR data for each of the libraries.

46. 42. The method of claim 41 , wherein the DNA conjugate comprises a peptide.

47. 47. The method of claim 46, wherein the peptide is a macrocycle.

48. 42. The method of claim 41, wherein the first window and the additional window include first graphical elements in a plurality of positions, each of the first graphical elements configured to represent a respective one of the libraries.

49. 49. The method of claim 48, wherein each of the libraries is in one of the individual spaces of a source plate, and each of the first graphical elements is configured to correspond horizontally and vertically to each of the individual spaces of the source plate.

50. 49. The method of claim 48, wherein each of the first graphical elements is positioned at the same location across different windows to represent the same well in a source plate.

51. 42. The method of claim 41, wherein the first window and the additional window include a second graphical element configured to visually distinguish quantification information of different libraries.

52. 52. The method of claim 51, wherein the second graphical element comprises a color or a number.

53. 52. The method of claim 51, wherein the second graphical element comprises a number.

54. 42. The method of claim 41, further comprising updating the graphical user interface to display a new window when a new selection round is selected by a user.

55. 42. The method of claim 41, further comprising displaying the first window and the additional window within the same graphical user interface such that a round-to-round comparison can be generated.

56. 42. The method of claim 41, wherein the first window and the additional window include a third graphical element configured to set the filter to display quantification information for each of the libraries selected by the filter.

57. 57. The method of claim 56, wherein the filter is a user-selected scaffold, a user-selected codon, or a user-selected target.

58. 42. The method of claim 41, further comprising plotting a round-by-round comparison for each of the library of DNA-containing compositions on the graphical user interface.

59. 1. A computer program product tangibly embodied in a non-transitory machine-readable storage medium comprising instructions configured to cause one or more data processors to execute a method for monitoring quantification information of a library and detecting target binding in a graphical user interface, the method comprising: a) receiving quantification information for each of a plurality of libraries of DNA-containing compositions for a first selection round, each of the libraries of DNA-containing compositions comprising DNA conjugates, and the first selection round selects the DNA conjugates based on their binding affinity to a target protein; b) displaying a first window within a graphical user interface, the first window including the quantification information for each of the library of DNA-containing compositions after the first selection round; c) repeating a)-b) to generate additional windows over multiple subsequent selection rounds, each of the additional windows displaying quantification information for each of the libraries for each subsequent selection round such that quantification information for the DNA-containing composition of each of the libraries for each round is monitored; 2. A computer program product comprising:

60. 1. A system comprising: a data store configured to store a dataset including quantification information for each of a plurality of libraries of DNA-containing compositions for each selection round, each of the libraries of DNA-containing compositions including a DNA conjugate, and each selection round selecting the DNA conjugate based on its binding affinity to a target protein; one or more data processors; a computing device communicatively connected to the data store and configured to receive the dataset, the computing device comprising a non-transitory computer readable storage medium comprising instructions, when executed on the one or more data processors, that cause the one or more data processors to perform a method for displaying the quantification information for each of the library of DNA-containing compositions, the method comprising generating a graphical user interface including a window selected to display the quantification information for each of the library of DNA-containing compositions for any selection round selected to be displayed; A system comprising:

61. 61. The system of claim 60, further comprising a liquid handler configured to transfer each of the libraries from a source plate to a PCR plate for PCR amplification.

62. 62. The system of claim 61 , wherein the liquid handler is further configured to normalize each of the libraries between every two successive selection rounds.

63. 61. The system of claim 60, wherein the system further comprises a thermocycler configured to amplify each of the libraries after each selection round.

64. 61. The system of claim 60, wherein the system further comprises a quantitative PCR unit configured to quantify each of the libraries before and after each selection round.

65. 1. A method for normalizing a polymerase chain reaction (PCR) amplification process for a plurality of samples containing DNA, comprising: identifying cycle data for performing the PCR amplification process on the plurality of samples, the cycle data including a corresponding cycle number for each sample of the plurality of samples; sorting the plurality of samples into a plurality of bins based on the cycle data such that bin-to-bin cycle number variation of the plurality of bins is reduced; assigning a bin cycle number to each bin of the plurality of bins, the bin cycle number being unique to each bin of the plurality of bins; generating identities for the plurality of bins; generating an output using the plurality of bins and the bin cycle number for each bin of the plurality of bins for performing PCR amplification of the plurality of samples; A method comprising:

66. 66. The method of claim 65, wherein the plurality of samples has varying amounts of DNA, and after the PCR amplification process is performed such that the plurality of samples becomes a plurality of amplified samples, the amplified plurality of samples has a normalized amount of DNA.

67. generating the identification information, 66. The method of claim 65, comprising generating a bin identifier for each bin of the plurality of bins.

68. generating the output, 66. The method of claim 65, comprising generating a forward worklist for a bin of the plurality of bins, the forward worklist including an order in which a set of samples in the bin are to be transferred from a source plate to a corresponding PCR plate for the bin.

69. 66. The method of claim 65, wherein the output further comprises instructions for a thermocycler to perform the PCR amplification process using a set of PCR plates.

70. assigning the bin cycle number 66. The method of claim 65, comprising generating the bin cycle number for one of the plurality of bins using a cycle number from the group consisting of: a highest cycle number for a set of samples in a bin, an average cycle number for the set of samples, a median cycle number for the set of samples, and a sum of the highest cycle number and a selected cycle number.

71. 71. The method of claim 70, wherein the selected cycle number is changed from a first run of the PCR amplification process to a second run of the PCR amplification process.

72. The selecting step comprises: converting any non-integer cycle numbers of the cycle data to integer cycle numbers to form modified cycle data; assigning unique integer cycle numbers of the modified cycle data within a selected range of cycle numbers to N bins; merging adjacent bins of the N bins using a distance equation until a target number of bins is reached, the target number of bins forming at least a portion of the plurality of bins; 66. The method of claim 65, comprising:

73. identifying the cycle data receiving initial cycle data from a quantitative PCR (qPCR) system, the initial cycle data including an initial cycle number for each sample of the plurality of samples; modifying the initial cycle number of at least one of the plurality of samples to generate the cycle data; 66. The method of claim 65, comprising:

74. the initial cycle number of a sample of the plurality of samples is an undetermined value, and the modifying 74. The method of claim 73, comprising changing the initial cycle number of the sample from the undetermined value to a preselected cycle number.

75. The modification is adding two cycles to the initial number of cycles for each sample of the plurality of samples; or Converting each non-integer number of cycles into an integer number of cycles.

74. The method of claim 73, comprising at least one of:

76. The selecting step comprises:

66. The method of claim 65, comprising distributing the plurality of samples into the plurality of bins based on a selected range of cycle numbers in the cycle data.

77. The distributing step comprises: assigning a portion of the plurality of samples having corresponding cycle numbers outside the selected range of cycle numbers to a portion of the plurality of bins; substantially uniformly distributing a remainder of the plurality of samples having corresponding cycle numbers within the selected range of cycle numbers among a remainder of the plurality of bins; 77. The method of claim 76, comprising:

78. The selecting step comprises: converting each non-integer cycle number in the cycle data to an integer cycle number to form modified cycle data; distributing the plurality of samples substantially uniformly among the plurality of bins based on a selected range of cycle numbers in the modified cycle data; 66. The method of claim 65, comprising:

79. generating the output, 66. The method of claim 65, comprising using the identification information to generate a transfer output for use in transferring a set of samples in each bin of the plurality of bins to a corresponding PCR plate of a set of PCR plates.

80. The plurality of samples has a plurality of corresponding cycle numbers, and the sorting comprises: assigning a first portion of the plurality of samples having a first set of cycle numbers less than a corresponding selected low cycle number to a first bin of the plurality of bins; allocating a second portion of the plurality of samples having a second set of cycle numbers above a selected high number to a last bin of the plurality of bins; distributing a remainder of the plurality of samples among a set of bins between the first bin and the last bin; 66. The method of claim 65, comprising:

81. The plurality of samples has a plurality of corresponding cycle numbers, and the sorting comprises:

66. The method of claim 65, further comprising identifying a distribution of the plurality of corresponding cycle numbers.

82. Identifying the distribution 82. The method of claim 81, comprising identifying a histogram distribution of the plurality of corresponding cycle numbers, wherein between 60% and 100% of the plurality of corresponding cycle numbers are within a selected range between and including a selected low cycle number and a selected high cycle number.

83. 83. The method of claim 82, wherein the selected low cycle number is 4 cycle numbers and the selected high cycle number is 24 cycle numbers.

84. The selecting step comprises: assigning any sample of the plurality of samples having a corresponding cycle number below the selected low cycle number to a first bin of the plurality of bins; assigning any sample of the plurality of samples having a corresponding cycle number above the selected high cycle number to a last bin of the plurality of bins; 83. The method of claim 82, comprising:

85. The selecting step comprises:

85. The method of claim 84, further comprising distributing a remainder of the plurality of samples among a set of bins between the first bin and the last bin.

86. sorting the plurality of samples into the plurality of bins, wherein 100% of the plurality of corresponding cycle numbers are within the selected range; 83. The method of claim 82, comprising distributing the plurality of samples among the plurality of bins in a biased manner to provide more bin separation among lower cycle numbers compared to higher cycle numbers.

87. The selecting step comprises: distributing the plurality of samples into the plurality of bins based on selected ranges of cycle numbers in the cycle data; modifying the distribution of the plurality of samples within the plurality of bins such that any samples among the plurality of samples having corresponding cycle numbers associated with the same integer value are grouped together in the same bin; 66. The method of claim 65, comprising:

88. 88. The method of claim 87, wherein the plurality of samples has a plurality of corresponding cycle numbers, and two cycle numbers of the plurality of corresponding cycle numbers are associated with the same integer value if each of the two cycle numbers comprises an integer that is the same integer value.

89. 88. The method of claim 87, wherein the plurality of samples has a plurality of corresponding cycle numbers, and two cycle numbers of the plurality of corresponding cycle numbers are associated with the same integer value when each of the two cycle numbers is rounded up to the same integer value.

90. The selecting step comprises:

66. The method of claim 65, comprising sorting the plurality of samples into the plurality of bins based on the distribution of the plurality of cycle numbers, biased to provide more bin separation between a portion of the plurality of cycle numbers that is within one standard deviation of the average of the plurality of cycle numbers compared to another portion of the plurality of cycle numbers that is outside one standard deviation of the average.

91. transferring a set of samples in each bin of the plurality of bins to a corresponding PCR plate of a set of PCR plates based on the output; performing the PCR amplification process using the set of PCR plates; 66. The method of claim 65, further comprising:

92. identifying the cycle data 66. The method of claim 65, comprising receiving the cycle data from a quantitative PCR (qPCR) system.

93. 1. A system comprising: one or more data processors; A non-transitory computer readable storage medium comprising instructions which, when executed on said one or more data processors, cause said one or more data processors to perform part or all of one or more methods according to any one of claims 1 to 10, 21 to 36, 41 to 58 and 65 to 92. A system comprising:

94. A computer program product embodied in a non-transitory machine-readable storage medium comprising instructions configured to cause one or more data processors to perform part or all of one or more of the methods recited in any one of claims 1 to 10, 21 to 36, 41 to 58, and 65 to 92.

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