Antibody structures comprising helical complementarity determining regions

Abstract

Provided herein are antibody structures comprising at least one CDR comprising a rigid structure, related compositions and methods, such methods include methods of producing the antibody structures comprising at least one CDR comprising a rigid structure as provided herein as well as methods of administering the antibody structures, such as by oral delivery.

Description

[0001]ANTIBODY STRUCTURES COMPRISING HELICAL COMPLEMENTARITY DETERMINING REGIONS RELATED APPLICATIONS This application claims the benefit of priority under 35 U.S.C. § 119(e) of U.S. Provisional Application Serial No.63 / 645,056, filed on May 9, 2024, the entire contents of which are incorporated herein by reference. REFERENCE TO AN ELECTRONIC SEQUENCE LISTING The contents of the electronic sequence listing (A144670001WO00-SEQ-JAV.xml; Size: 15,106 bytes; and Date of Creation: May 8, 2025) are herein incorporated by reference in its entirety. FIELD OF THE INVENTION The invention relates at least in part to antibody structures comprising at least one complementarity determining region (CDR) comprising a rigid structure, such as a helical structure, related compositions and methods, such methods include methods of administering the antibody structures, such as orally, as well as methods of producing the antibody structures comprising at least one CDR comprising a rigid structure. SUMMARY OF THE INVENTION Provided herein, in one aspect, is an antibody structure comprising at least one CDR that binds a target, wherein the at least one CDR comprises a rigid structure. In one embodiment of any one of the compositions or methods provided herein, the rigid structure is an alpha helix structure. In one embodiment of any one of the compositions or methods provided herein, the antibody structure has a binding affinity of at least 10-7M. In one embodiment of any one of the compositions or methods provided herein, the antibody structure has a binding affinity of no more than 10-8M or no more than 10-9M. In one embodiment of any one of the compositions or methods provided herein, the antibody structure has a binding affinity of between 10-7M and 10-9M. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation at an intestinal pH, such as at a pH of 6.5. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation in simulated intestinal fluid, such as the simulated intestinal fluid of Table 2. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation in simulated intestinal fluid, such as the simulated intestinal fluid of Table 2, for at least 1 hour. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation in the presence of a protease. In one embodiment of any one of the compositions or methods provided herein, the antibody structure is stable or resistant to degradation in the presence of any one or more of the proteases provided herein. In one embodiment of any one of the compositions or methods provided herein, the antibody structure is stable or resistant to degradation in the presence of trypsin and / or chymotrypsin. In one embodiment of any one of the compositions or methods provided herein, the antibody structure is thermostable. In one embodiment of any one of the compositions or methods provided herein, the antibody structure is stable or resistant to degradation at a temperature of at least or equal to 37ºC. In one embodiment of any one of the compositions or methods provided herein, the antibody structure comprises at least two CDRs, each comprising a rigid structure. In one embodiment of any one of the compositions or methods provided herein, the antibody structure comprises three CDRs that each comprise a rigid structure. In one embodiment of any one of the compositions or methods provided herein, the antibody structure comprises a CDR1 and / or CDR3 that each comprise a rigid structure. In one embodiment of any one of such compositions or methods provided herein, the rigid structure is an alpha helix structure. In one embodiment of any one of the compositions or methods provided herein, the antibody structure further comprises an antibody scaffold. In one embodiment of any one of the compositions or methods provided herein, the antibody scaffold comprises a single- domain antibody (sdAb), single-chain variable fragment (scFv), Fab’, fragment antigen binding (Fab), F(ab’)2or a full-length antibody without the CDR loop(s) that comprise the rigid structures(s). In one embodiment of any one of the compositions or methods provided herein, the at least one CDR comprising a rigid structure replaces a CDR1 loop or CDR3 loop. In one embodiment of any one of the compositions or methods provided herein, the at least two CDRs comprising a rigid structure replaces a CDR1 loop and a CDR3 loop. In one embodiment of any one of the compositions or methods provided herein, the three CDRs comprising a rigid structure replaces a CDR1 loop, a CDR2 loop and a CDR3 loop. In one embodiment of any one of the compositions or methods provided herein, the replacing CDRs comprising a rigid structure are on each variable domain of an antibody structure provided herein. In one embodiment of any one of the compositions or methods provided herein, each CDR comprising a rigid structure is 5-18 residues in length. In one embodiment of any one of the compositions or methods provided herein, each CDR comprising a rigid structure is 6- 14 residues in length. In one embodiment of any one of the compositions or methods provided herein, each CDR comprising a rigid structure is 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 residues in length. In one embodiment of any one of the compositions or methods provided herein, the antibody structure further comprises at least one linker at the N-terminus and / or C-terminus of at least one CDR comprising a rigid structure. In one embodiment of any one of the compositions or methods provided herein, the antibody structure further comprises at least one linker at the N-terminus and / or C-terminus of each CDR comprising a rigid structure. In one embodiment of any one of the compositions or methods provided herein, the linker does not form an alpha helix or beta sheet secondary structure. In one embodiment of any one of the compositions or methods provided herein, the linker at an N-terminus is 1-8 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at an N-terminus is 1-5 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at an N-terminus is 1, 2, 3, 4, 5, 6, 7, or 8 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at a C-terminus of a CDR comprising a rigid structure that replaces a CDR1 loop is 1-8 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at a C-terminus of a CDR comprising a rigid structure that replaces a CDR1 loop is 1-5 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at a C-terminus of a CDR comprising a rigid structure that replaces a CDR1 loop, is 1, 2, 3, 4, 5, 6, 7, or 8 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at a C-terminus of a CDR comprising a rigid structure that replaces a CDR3 loop is 1- 10 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at a C-terminus of a CDR comprising a rigid structure that replaces a CDR3 loop is 2-7 residues in length. In one embodiment of any one of the compositions or methods provided herein, the linker at a C-terminus of a CDR comprising a rigid structure that replaces a CDR3 loop is 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 residues in length. In one embodiment of any one of the compositions or methods provided herein, the antibody structures have or are selected or designed to have specific features. Such features, include, but are not limited to, being stable or resistant to degradation in an intestinal environment and / or being stable or resistant to degradation by one or more proteases and / or thermostability, as provided herein. In one embodiment of any one of the compositions or methods provided herein, the alpha helices comprise the sequence of any one of the alpha helices provided herein. In one embodiment of any one of the compositions or methods provided herein, the sequence of any one of the alpha helices comprises the sequence set forth as SEQ ID NOs: 5, 6, 8, 9, 12 or 13. In one embodiment of any one of the compositions or methods provided herein, the sequence of any one of the alpha helices comprises the sequence set forth as SEQ ID NOs: 2 (shown in bold). In one embodiment of any one of the compositions or methods provided herein, the antibody structure comprises the sequence of any one of the antibody structures provided herein or an antigen-binding fragment thereof. In one embodiment of any one of the compositions or methods provided herein, the antibody structure comprises the sequence of any one of SEQ ID NOs: 2, 4, 7 and 11 or an antigen-binding fragment thereof. In one aspect, compositions comprising any one of the antibody structures provided herein are provided. In one embodiment of any one of the compositions provided herein, the composition further comprises a pharmaceutically acceptable carrier. In one aspect, a method of administering any one of the antibody structures or any one of the compositions provided herein to a subject is provided. In one embodiment, the administering is done by oral delivery. In one aspect, a method for producing any one of the antibody structures provided herein is provided. In one embodiment of any one of the methods provided herein, a method for producing an antibody structure comprising at least one CDR that comprises a rigid structure that binds a target, comprises a) computationally generating a backbone comprising at least one rigid structure (e.g., an alpha helix) and an antibody scaffold, and b) generating an amino acid sequence such that the at least one CDR that comprises a rigid structure binds to the target, and c) optionally, evaluating the produced antibody structure using a protein structure prediction model. In one embodiment of any one of the methods provided herein, a) comprises using a diffusion model with fold conditioning. In one embodiment of any one of the methods provided herein, the fold conditioning comprises specifying secondary structural elements. In one embodiment of any one of the methods provided herein, the secondary structural elements comprise the at least one rigid structure (e.g., an alpha helix) and one or more structural elements of an antibody scaffold. In one embodiment of any one of the methods provided herein, a) comprises i) generating a backbone comprising an antibody scaffold using a diffusion model with fold conditioning, ii) generating a backbone comprising at least two rigid structures (e.g., at least two alpha helices) that bind to a target using a diffusion model with fold conditioning as well as a target structure and target residues on the target structure, and iii) grafting two of the rigid structures (e.g., helices) of ii) onto the backbone of i). In one embodiment of any one of the methods provided herein, the fold conditioning comprises specifying secondary structural elements. In one embodiment of any one of the methods provided herein, the secondary structural elements for i) comprise one or more structural elements of an antibody scaffold without providing a target. In one embodiment of any one of the foregoing, b) occurs before or after iii). In one embodiment of any one of the methods provided herein, a) comprises providing a target structure and target residues on the target structure using a diffusion model with fold conditioning. In one embodiment of any one of the methods provided herein, the fold conditioning comprises specifying secondary structural elements. In one embodiment of any one of the methods provided herein, the secondary structural elements comprise the at least one rigid structure (e.g., alpha helix) and one or more structural elements of an antibody scaffold. In one embodiment of any one of the methods provided herein, b) comprises using a message-passing neural network model. In one aspect, a method for producing an antibody structure comprising at least one CDR that comprises a rigid structure that binds a target, comprising computationally generating a backbone, such as by using a denoising diffusion probabilistic model, optionally with fold conditioning, is provided. In one embodiment, the fold may be specified by providing each secondary structural element (alpha helix, beta sheet, or loop), its length in number of residues, and / or its contacts with other secondary structural elements. In one embodiment of the foregoing method, an antibody scaffold, such as a single domain antibody, fold is specified with at least one CDR (e.g., CDR1 and / or CDR3 and / or CDR2) replaced with a CDR comprising alpha helix(ces). In one embodiment of the foregoing method, the backbone is designed to bind to a target, such as by providing a target structure and desired residues on that structure (i.e., the epitope) for binding. In one embodiment, such a backbone is designed using a docking approach. In one embodiment, a docking approach comprises generating a backbone for an antibody structure with CDR(s) comprising a helix without providing a target, using a diffusion model with fold conditioning to specify the fold, and generating a backbone consisting of two or three helices in a helical bundle fold to bind to a target using the diffusion model with fold conditioning as well as the target structure and target residues on that structure. In one embodiment, the foregoing method may further comprise using at least two of the helices to dock the backbone at specified target residues on the target structure. In one embodiment of any one of the methods provided herein, the method further comprises generating amino acid sequences for the backbone, such as by using a message- passing neural network model. In such an embodiment, the sequences for the target and the antibody scaffold are provided along with a backbone structure of the complex (consisting of target and antibody structure with helical CDR(s)), and sequence(s) may be generated for the helical CDR(s) in this context. In one embodiment of any one of the methods provided herein, the method further comprises redesigning amino acids of the antibody scaffold sequence to better support the helical CDR(s). In one embodiment of any one of the methods provided herein, the method further comprises evaluating a design such as by using a protein structure prediction model. In one embodiment of any one of the methods provided herein, amino acid sequences are generated or selected that provide the antibody structures with specific features. Such features, include but are not limited to, being stable or resistant to degradation in an intestinal environment and / or being stable or resistant to degradation by one or more proteases and / or thermostability, as provided herein. BRIEF DESCRIPTION OF THE FIGURES Figure 1 provides an example nanobody (VHH) with helical CDR1 and CDR3. Figure 2 provides an alternate view of the example nanobody (VHH) with helical CDR1 and CDR3. Figure 3 illustrates a nanobody with helical CDR1 and CDR3 designed to bind to PD-L1, design model of complex aligned to predicted structure of complex. Figure 4 illustrates the nanobody with helical CDR1 and CDR3 designed to bind to PD- L1, interface detail of predicted structure of complex. Figure 5 provides an illustration of a computational design model of hCDR_InsR_1:InsR complex and predicted structure of hCDR_InsR_1:InsR complex overlaid. Figure 6 provides hCDR_InsR_1:InsR complex interface detail. Figure 7 provides results from a hCDR_InsR_1 biolayer interferometry binding experiment. Figure 8 provides results from a hCDR_InsR_1 simulated intestinal fluid incubation experiment. Figure 9 illustrates a computational design model of hCDR_InsR_2:InsR complex and predicted structure of hCDR_InsR_2:InsR complex overlaid. Figure 10 illustrates hCDR_InsR_2 interface detail. Figure 11 provides results from a hCDR_InsR_2 biolayer interferometry binding experiment. Figure 12 illustrates a computational design model of hCDR_TrkA_1:TrkA complex and predicted structure of hCDR_TrkA_1:TrkA complex overlaid. Figure 13 illustrates hCDR_TrkA_1:TrkA complex interface detail. Figure 14 provides results from a hCDR_TrkA_1 simulated intestinal fluid incubation experiment. DETAILED DESCRIPTION OF THE INVENTION Before describing the present invention in detail, it is to be understood that this invention is not limited to particularly exemplified materials or process parameters as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments of the invention only, and is not intended to be limiting of the use of alternative terminology to describe the present invention. All publications, patents and patent applications cited herein, whether supra or infra, are hereby incorporated by reference in their entirety for all purposes. Such incorporation by reference is not intended to be an admission that any of the incorporated publications, patents and patent applications cited herein constitute prior art. As used in this specification and the appended claims, the singular forms "a," "an" and "the" include plural referents unless the content clearly dictates otherwise. For example, reference to "a molecule" includes a mixture of two or more such molecules or a plurality of such molecules, and the like. As used herein, the term “comprise” or variations thereof such as “comprises” or “comprising” are to be read to indicate the inclusion of any recited integer (e.g. a feature, element, characteristic, property, method / process step or limitation) or group of integers (e.g. features, elements, characteristics, properties, method / process steps or limitations) but not the exclusion of any other integer or group of integers. Thus, as used herein, the term “comprising” is inclusive and does not exclude additional, unrecited integers or method / process steps. In embodiments of any of the compositions and methods provided herein, “comprising” may be replaced with “consisting essentially of” or “consisting of”. The phrase “consisting essentially of” is used herein to require the specified integer(s) or steps as well as those which do not materially affect the character or function of the claimed invention. As used herein, the term “consisting” is used to indicate the presence of the recited integer (e.g. a feature, element, characteristic, property, method / process step or limitation) or group of integers (e.g. features, elements, characteristics, properties, method / process steps or limitations) alone. Introduction Generally, the antibody drug development process consists of three broad stages: discovery, optimization, and development. Discovery refers to the process of finding an initial antibody sequence or sequences. Optimization involves altering this sequence to improve desired properties, for example binding affinity or stability. Development includes all steps after the final antibody sequence is fixed, in which formulation and manufacturing are established for the drug candidate, animal testing is used to assess safety and determine first-in-human dose, and clinical trials are conducted. The discovery stage includes methods such as immunization, display technologies (e.g., yeast, phage), and B cell isolation, which may be used separately or in combination to discover drug candidates from very large (i.e., >108) libraries of potential sequences. Antibody libraries may consist of the native antibody repertoire from animals (including somatic hypermutation of antibodies recognizing a target) or synthetic libraries designed by scientists or generated through machine learning. Current discovery methods screen these libraries in order to identify antibody sequences that bind to a given target. These discovery methods provide very limited control over the epitope to which the antibody paratope binds. Furthermore, the experimental conditions associated with these methods may not accurately represent the target in its native context, leading to ineffective drugs in later stages of development. Candidates discovered through these methods do not achieve the full set of the desired drug properties, because their discovery is limited by traits specific to the selection methods (e.g., high surface expression on yeast for yeast display). As a result, candidate antibodies may have limited efficacy when moved to the native system and may not exhibit the properties required for manufacturing and formulation as an antibody drug. These candidate antibodies require significant optimization and development in order to produce functional drugs. The optimization stage involves the generation (either manually or via machine learning) and testing of further libraries consisting of variants of the candidate antibodies in order to identify high-value variants with desired drug properties. This includes high- throughput methods such as display technologies and low-throughput methods such as biolayer interferometry. Antibody optimization is typically an iterative process where select properties may be improved individually or in combination. The final selection of high-value variants requires balancing tradeoffs between multiple desired drug properties. The development stage consists of the remaining steps in the pipeline prior to the final drug production, including pre-clinical trials, clinical trials, and any additional development of the drug. Due to the difficulties with performing the above steps, alternative methodology for antibody development have been employed. For example, CDR grafting, which refers to the transfer of CDR loops from one antibody onto another through replacement of the CDR sequence, has been a part of the antibody engineering toolkit for decades. In addition, the grafting of peptides to replace one or multiple CDR loops has also been used in specific cases to enable antibody design (8, 10). In recent years, machine learning has been applied to protein structure prediction to achieve high-accuracy prediction (up to atomic-accuracy) for many proteins (1, 2). However, these methods are typically unable to accurately predict the structure of antibody CDR loops due to their high conformational diversity (3). Also, while, generally, high-affinity binding proteins (“binders”) with the ability to bind to a wide range of targets can be created (4), processes can be improved through the incorporation of machine learning methods including diffusion models and graph neural networks (5-7). Such processes do not require iterative optimization but rather rely on the design of de novo proteins with binding interfaces that feature well-defined secondary structural elements (e.g., alpha helices and beta sheets). Antibody drug development has not fully benefited from such tools, and it has remained difficult to predict the structure and binding of antibodies. The inventors have surprisingly and unexpectedly discovered that the problems and limitations noted above can be overcome by practicing the invention disclosed herein. Methods and compositions are provided that offer solutions to the aforementioned obstacles to effective design of antibody structures, which antibody structures comprise a CDR comprising a rigid structure. Preferably, the rigid structure is conferred with an alpha helix. The invention will now be described in more detail below. Antibody Structures with CDRs Comprising Rigid Structures Provided herein are antibody structures, which comprise a specific number of CDRs comprising a rigid structure and an antibody scaffold. An “antibody structure” as provided herein is a polypeptide that has the structure of a typical antibody or antigen-binding fragment thereof where at least one CDR comprises a rigid structure. Thus, as used herein, an “antibody scaffold” refers to the structure of an antibody or antigen-binding fragment thereof save for the CDR loop(s) that are replaced with the CDR(s) comprising a rigid structure as provided herein. In some embodiments, the antibody scaffold comprises CDR loops that are not replaced with a CDR comprising a rigid structure. In some embodiments, however, the antibody scaffold does not comprise any CDR loops, as the CDR loops have each been replaced with a CDR comprising a rigid structure. In one embodiment of any one of the CDRs provided herein, the rigid structure replaces all or part of a CDR. Typical antibodies are generally glycoproteins comprising at least two heavy (H) chains and two light (L) chains inter-connected by disulfide bonds. Each heavy chain is comprised of a heavy chain variable region (abbreviated herein as HCVR or VH) and a heavy chain constant region. The heavy chain constant region is comprised of three domains, CH1, CH2 and CH3. Each light chain is comprised of a light chain variable region (abbreviated herein as LCVR or VL) and a light chain constant region. The light chain constant region is comprised of one domain, CL. The VH and VL regions can be further subdivided into regions of hypervariability, termed complementarity determining regions (CDRs), interspersed with regions that are more conserved, termed framework regions (FRs). Each VH and VL is composed of three CDRs and four FRs, arranged from amino-terminus to carboxy-terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4. The variable regions of the heavy and light chains contain a binding domain that interacts with a target (an antigen). The constant regions of the antibodies may mediate the binding of the immunoglobulin to host tissues or factors, including various cells of the immune system (e.g., effector cells) and the first component (C1q) of the classical complement system. Antigen-binding fragments of a typical antibody refers to one or more portions of an antibody that retain the ability to bind specifically to a target (antigen). The antigen-binding function of an antibody can be performed by fragments of a full-length antibody, and antigen- binding fragments include such fragments. Examples of antigen-binding fragments include (i) a Fab fragment, a monovalent fragment consisting of the VL, VH, CLand CH1 domains; (ii) a F(ab′)2 fragment, a bivalent fragment comprising two Fab fragments linked by a disulfide bridge at the hinge region; (iii) a Fd fragment consisting of the VH and CH1 domains; (iv) a Fv fragment consisting of the VL and VH domains of a single arm of an antibody, (v) a dAb fragment (Ward et al., (1989) Nature 341:544-546), which consists of a VH domain., and (vi) a sdAb, single-domain antibody or nanobody. Furthermore, although the two domains of the Fv fragment, V and VH, are coded for by separate genes, they can be joined, using recombinant methods, by a synthetic linker that enables them to be made as a single protein chain in which the VL and VH regions pair to form monovalent molecules (known as single chain Fv (scFv); see e.g., Bird et al. (1988) Science 242:423-426; and Huston et al. (1988) Proc. Natl. Acad. Sci. USA 85:5879-5883). Such single chain antibodies are also considered as examples of antigen-binding fragments of a typical antibody. The antibody scaffolds of the compositions and methods provided herein can be any one of the foregoing structures but without the CDR(s) that are replaced as provided herein or without any CDR(s) as provided herein. In some embodiments, antibody scaffolds and sequences can come from known antibodies or newly discovered antibodies. The antibody scaffolds may be from a crystal structure or a predicted structure, in other embodiments. The antibody structures provided herein can comprise any one of the antibody scaffolds provided herein. A key feature in the development of the antibody structures provided herein is the introduction of a rigid structure, which restricts a CDR conformation(s). As used herein, a “rigid structure” is any structure that can restrict a CDR conformation and that can allow the use of protein design tools, such as those which otherwise may be largely ineffective in designing CDR loops. The rigid structure may be an alpha helix. “Alpha helix” refers to a sequence of amino acids that can be twisted into a coil (a helix). Generally, the alpha helix has a right-handed helix conformation in which backbone N−H groups hydrogen bond to the backbone C=O groups of the amino acid that is four residues earlier in the protein sequence, respectively. In one embodiment of any one of the compositions or methods provided herein, the alpha helix may have the sequence of any one of the alpha helices provided herein. The antibody structures provided herein can bind a target. As used herein, a “target” is any molecule to which specific binding is desired. As used herein, “specific binding” refers to a molecule binding to a predetermined target with at least two-fold greater affinity than its affinity for binding to a non-specific target. In one embodiment, the antibody structure has a binding affinity of at least 10-7M. In one embodiment, the antibody structures have a binding affinity of no more than 10-8M or 10-9M. In one embodiment, the antibody structures have a binding affinity of between 10-7M and 10-9M. The binding affinity of antibody structures can be determined by a variety of methods known in the art. For example, binding affinity can be determined as provided in the Examples, for example, by loading biotinylated target antigen onto streptavidin coated biosensor and measuring association and dissociation of His-tag purified antibody structure. Binding affinity can also be determined by Enzyme-Linked Immunosorbent Assay (ELISA), Surface Plasmon Resonance (SPR), Mass Photometry (MP), Cell-Based Fluorescent Assays and Chaotrope- Based Assays, in embodiments. The at least one CDR comprising a rigid structure of the antibody structures provided herein is used in place of an antibody or antigen-binding fragment CDR loop. The CDRs comprising a rigid structure provided herein can be used in place of a CDR1, CDR2, or CDR3 loop of an antibody or antigen-binding fragment. In the antibody structures provided herein, there may be CDRs comprising a rigid structure that replace one, two or all three of the CDR loops. In some embodiments, the CDR comprising a rigid structure replaces a CDR1 and / or CDR3 loop, as it has been found that a CDR2 loop is not necessarily required for antibody or antigen-binding fragment binding. In some embodiments, CDRs comprising a rigid structure replace CDR1, CDR2 and CDR3 loops. The replaced CDRs may be of one, two, three or all four variable domains, in some embodiments depending on the antibody scaffold of the antibody structure. The CDRs comprising a rigid structure, preferably, are of a length that provides specific binding to a target and adopts at least in part a secondary structure (e.g., alpha helical) but that does not introduce too much strain into the structure such that stable folding is negatively impacted. For example, a CDR comprising a rigid structure can have a length of 5-18 residues, 5-17 residues, 5-16 residues, 5-15 residues, 5-14 residues, 5-13, residues, 5- 12 residues, 5-11 residues, 5-10 residues, 5-9 residues, 5-8 residues, or 5-7 residues. As another example, a CDR comprising a rigid structure can have a length of 6-18 residues, 6-17 residues, 6-16 residues, 6-15 residues, 6-14 residues, 6-13, residues, 6-12 residues, 6-11 residues, 6-10 residues, 6-9 residues, or 6-8 residues. As a further example, a CDR comprising a rigid structure can have a length of 7-18 residues, 7-17 residues, 7-16 residues, 7-15 residues, 7-14 residues, 7-13, residues, 7-12 residues, 7-11 residues, 7-10 residues, or 7- 9 residues. As still a further example, a CDR comprising a rigid structure can have a length of 8-18 residues, 8-17 residues, 8-16 residues, 8-15 residues, 8-14 residues, 8-13, residues, 8- 12 residues, 8-11 residues, or 8-10 residues. As a further example, a CDR comprising a rigid structure can have a length of 9-18 residues, 9-17 residues, 9-16 residues, 9-15 residues, 9-14 residues, 9-13, residues, 9-12 residues, or 9-11 residues. As yet a further example, a CDR comprising a rigid structure can have a length of 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 residues. Other lengths may be determined by the number of residues that are both sufficient to design binding to a target and that adopts a secondary structure (e.g., alpha helical) with high predicted accuracy and confidence. Below such a length, a CDR comprising a rigid structure can become unstructured and / or may not bind to a target. Other lengths may be determined by the number of residues that can be accommodated by an antibody scaffold and that adopts secondary structure (e.g., alpha helical) with high predicted accuracy and confidence. Above such a length, the CDR comprising a rigid structure can introduce too much strain into the structure and / or will not stably fold. Preferred ranges, in some embodiments, include lengths where CDRs comprising a rigid structure can be predicted with high accuracy and confidence and can be designed effectively to bind to a target. In some embodiments, the lengths include those where CDRs comprising a rigid structure that are typically predicted with a lower accuracy and confidence but may be able to be designed to bind to a target. The antibody structures provided herein can include linkers. The linkers can join the CDRs comprising a rigid structure to an antibody scaffold with unstructured segments that, preferably, do not adopt a secondary structure (e.g., an alpha helix or beta sheet) and / or are distinct from the CDRs comprising a rigid structure and the beta sheets of the antibody scaffold they join. These segments or “linkers” can be before and / or after a CDR comprising a rigid structure in the peptide chain (from N-terminus to C-terminus). However, these linkers may not be necessary in some cases (equivalent to being 0 residues in length). In some embodiments, at least one linker for a CDR comprising a rigid structure at the N- terminus and / or C-terminus must be longer than 0 residues to avoid strain in the structure and / or to ensure stable folding. The linkers, for examples, are of 1-8 residues, 1-7 residues, 1-6 residues, 1-5 residues, 1-4 residues, or 1-3 residues. In some embodiments of any one of the compositions or methods provided herein, the foregoing linkers are at the N-terminus and / or C-terminus of a CDR comprising a rigid structure, such as a CDR1 comprising a rigid structure or CDR3 comprising a rigid structure. As another example, the linkers are of 1-10 residues, 1-9, residues, 1-8 residues, 1-7 residues, 1-6 residues, 1-5 residues, 1-4 residues, 1-3 residues, 2- 10 residues, 2-9, residues, 2-8 residues, 2-7 residues, 2-6 residues, 2-5 residues, or 2-4 residues. In some embodiments of any one of the compositions or methods provided herein, the foregoing linkers are at the N-terminus and / or C-terminus of a CDR comprising a rigid structure, such as a CDR3 comprising a rigid structure. In some embodiments of any one of the compositions or methods provided herein, the foregoing linkers are at the C-terminus of a CDR comprising a rigid structure, such as a CDR3 comprising a rigid structure. As yet a further example, a linker can have a length of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 residues. Other lengths may be determined by the number of residues that are both sufficient to design binding to a target and that adopts a secondary structure (e.g., alpha helical) with high predicted accuracy and confidence. Above a certain residue length, such as above the maximum lengths of the ranges provided herein, the linkers may result in instability of the structure and / or result in aggregation. Other lengths of a linker, in some embodiments, can be those that result in antibody structures that can be predicted with high accuracy and confidence and / or that specifically binds to a target. Still other lengths of a linker, in other embodiments, can be those that result in antibody structures that are less likely to be stable but may still function as desired. Amino acids for the linkers may be, but are not limited to, glycine, proline, and serine. Compositions comprising the CDRs comprising a rigid structure alone or in combination with the antibody scaffolds as provided herein are provided. Thus, compositions comprising the antibody structures provided herein are provided. For example, the antibody structures may comprise any portion of an antibody, full-length or an antigen-binding fragment thereof, with one or more CDRs comprising a rigid structure as provided herein. In some embodiments, the antibody structure comprises a VHH scaffold with a CDR comprising a rigid structure, such as a CDR1 comprising a rigid structure and / CDR3 comprising a rigid structure; a mAb, Fab, or scFv scaffold with a VH CDR comprising a rigid structure, such as a CDR1 comprising a rigid structure and / or CDR3 comprising a rigid structure, and a VL CDR comprising a rigid structure, such as a CDR1 and / or CDR3 comprising a rigid structure; a mAb, Fab, or scFv scaffold with a VH CDR comprising a rigid structure, such as a CDR1 and / or CDR3 comprising a rigid structure, and a VL CDR comprising a rigid structure, such as a CDR3 comprising a rigid structure; or a mAb, Fab, or scFv scaffold with a VH CDR comprising a rigid structure, such as a CDR3 comprising a rigid structure, and a VL CDR comprising a rigid structure, such as a CDR1 and CDR3 comprising a rigid structure. Specific examples of antibody structures as provided herein are depicted in the Figures and Examples. For example, Figure 1 depicts an example nanobody (VHH) fold with helical CDR1 and helical CDR3. Figure 2 depicts an example nanobody (VHH) fold with helical CDR1 and helical CDR3 (alternate view). Figures 3 and 4 illustrate an exemplary nanobody with helical CDR1 and CDR3 designed to bind to PD-L1. Figures 5, 6, 9 and 10 illustrate exemplary single domain antibodies designed to bind human insulin receptor, while Figures 12 and 13 illustrate an exemplary single domain antibody designed to bind tropomyosin receptor kinase A. CDRs comprising rigid structures as provided herein can have highly predictable and controllable structure and can allow for precise sequence and structural manipulation. As a result, the antibody structures provided herein can be designed with a wide variety of beneficial properties. These properties include, but are not limited to, target epitope binding, reduced off-target binding, binding affinity, aggregation, and pharmacokinetic properties. Successful binding of exemplary antibody structures of the Examples is demonstrated in Figures 7 and 11. Still other properties include, but are not limited to, features such as pH responsiveness. In one embodiment, an antibody structure may bind with high affinity at a neutral or slightly basic pH (such as physiologic pH of 7.4) while binding with much lower affinity in an acidic environment (such as pH of 4.5 to 6.5 such as of the endosome). In such an embodiment, pH responsiveness can be used to increase internalization of an antibody structure by promoting its dissociation in the endosome. Other environments can also feature an acidic pH, like the tumor microenvironment (TME). A pH responsive antibody structure may bind with high affinity in the acidic TME, while featuring a much lower affinity in neutral physiologic pH. In such an embodiment, pH responsiveness can be used to limit an antibody structure to only bind its target in the TME, increasing its specificity. In one embodiment of any one of the compositions or methods provided herein, the antibody structures provided herein can be pH responsive. In one embodiment of any one of the compositions or methods provided herein, the antibody structures provided herein can be pH responsive and have any one of the foregoing pH responsive features. Histidine residues have a pKa of around 6, so they become protonated in acidic environments and may alter binding affinity if they are present at a binding interface. In one embodiment of any one of the compositions or methods provided herein, a pH responsive antibody structure can feature histidine residues at the binding interface. These histidine residues may be on the paratope of the antibody structure and / or on the epitope of the target of the antibody structure. Further, antibody structures can be designed that avoid undesirable features, such as lack of stability or degradation in an intestinal environment and / or lack of stability or degradation by one or more proteases and / or lack of stability or degradation at higher temperatures, such as at 37ºC. Thus, antibody structures can be thermostable, in some embodiments of any one of the compositions or methods provided herein. Generally, a pH resistant antibody structure can avoid or have reduced unfolding in specific pH conditions and / or in the presence of protease and / or at higher temperatures. Unfolding can result in reduced efficacy of an antibody. Thus, in some embodiments, the antibody structures provided herein can be resistant to unfolding in any one or more of the foregoing conditions. “Stability” as used herein refers to at least some level of antibody structures in a sample that are still intact and / or have reduced or no unfolding under a set of conditions. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation at an intestinal pH, such as a pH of 6.5. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation in simulated intestinal fluid, such as the simulated intestinal fluid of Table 2. In one embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation in simulated intestinal fluid for at least 1 hour. In another embodiment of any one of the compositions or methods provided herein, the antibody structure can be stable or resistant to degradation by proteolytic enzymes, including luminal enzymes from gastrointestinal and pancreatic secretions, bacterial enzymes in the colon and mucosal enzymes. Table 1 provided below lists digestive enzymes, and the antibody structures provided herein can be stable or resistant to degradation by one or more or all (or any combination) of these enzymes. For example, pepsin in the stomach is able to degrade proteins into smaller fragments of peptides by hydrolyzing the peptide bonds. As another example, proteolytic enzymes in the upper part of the small intestine which are secreted by pancreas, such as trypsin, chymotrypsin, carboxypeptidase and elastase, can result in degradation or further degradation of proteins. Moreover, remaining parts of proteins can be finally digested by various peptidases (e.g., aminopeptidase and dipeptidase). Resistance to such degradation can be a benefit. The antibody structures herein can have such resistance in some embodiments. Table 1. Main digestive enzymes and their sites of action Secretion Enzyme Specificity site Stomach Pepsin Asp, hydrophobic amino acids Secretion Enzyme Specificity site Pancreas Trypsin Arg, Lys Chymotrypsin Aliphatic amino acids (Phe, Tyr) Carboxypeptidase A Aromatic amino acids in C-terminal (Tyr, Phe, Ile, Thr, Glu, His, Ala) Carboxypeptidase B Arg, Lys in C-terminal Elastase Ala, Gly, Ser Small Aminopeptidase A Asp, Glu in N-terminal intestine Aminopeptidase N Ala, Leu in N-terminal Aminopeptidase P Pro in N-terminal Aminopeptidase W Typ, Tyr, Phe in N-terminal γ-Glutamyl γ-Glutamic acid in N-terminal transpeptidase Dipeptidyl peptidase IV Pro, Ala Peptidylpeptidase A His–Leu Carboxypeptidase M Lys, Arg in C-terminal Carboxypeptidase P Pro, Gly, Ala in C-terminal γ-Glutamyl γ-Glutamic acid carboxypeptidase Endopeptidase-24.11 Hydrophobic amino acids Endopeptidase-24.18 Aromatic amino acids Enteropeptidase (Asp)4-Lys As another example, the antibody structures provided herein can be thermostable or have resistance to degradation at higher temperatures, such as 37ºC. Generally, thermostability is the ability of a protein to remain properly folded and maintain its structure when exposed to higher temperatures. For thermostability, the antibody structures with CDRs comprising rigid structures can generally have thermostability relative to (increased stability relative to) conventional antibodies as a property intrinsic to the structures. De novo designed proteins have been found to be exceptionally thermostable relative to natural proteins. This is due to their rigid, idealized structures and sequences that are a result of how they are designed. Thermostability can be measured by the melting temperature, at which point the protein denatures. Thermostability can correlate with resistance to proteolysis as well as other metrics of stability, such as resistance to guanidinium denaturation. Thermostability can also be measured by any other method as provided herein or as otherwise known in the art. Thermostability is a highly desirable characteristic, in some embodiments, as it can enable manufacturing, storage, and longer serum half-life. In one embodiment of any one of the compositions or methods provided herein, the antibody structures provided herein can be thermostable and have any one of the foregoing thermostable features. Stability or resistance to degradation of antibody structures as provided herein can generally be measured by a variety of methods known in the art. For example, Differential Scanning Calorimetry (DSC), Nano-Differential Scanning Calorimetry (nano-DSC), Western Blot, Immunohistochemistry (IHC) and Immunofluorescence (IF), Enzyme-linked immunosorbent assay (ELISA), Dynamic Light Scattering (DLS), Differential Scanning Fluorimetry (DSF), Thermofluor assay, Size-exclusion chromatography (SEC), or Capillary electrophoresis (CE). In one embodiment of any one of the compositions or methods provided herein, the stability or resistance to degradation of an antibody structure is performed by any one of the methods provided herein, such as in the Examples. Stability or resistance to degradation can also be assessed with SDS-PAGE, such as described below. Thus, in one embodiment, the stability or resistance to degradation of an antibody structure of any one of the compositions or methods provided herein can be assessed as follows. 1. Aliquot 7.5 uL of His-tag purified protein sample in elution buffer (25 mM NaPhosphate pH 7.4, 275 mM NaCl, 250 mM Imidazole). 2. Add 7.5 uL of 2x freshly prepared solution (e.g., at a desired pH (depending on whether or not pH degradation is to be assessed)) with or without added proteases at 60 μg / mL, if protease degradation is to be assessed. 3. Incubate at a desired temperature (if degradation at a desired temperature, such as at 37ºC) for 1 hour and 4 hour timepoints. For 0 hour timepoint, add elution buffer to match the volume of the digestion timepoints. 4. Add 5.5uL of 4x Tris / Glycine / SDS running buffer (BioRad) and 1uL 1M DTT to each sample and heat 5 minutes at 95C to end incubation. 5. Run samples immediately on 4-20% TGX gel (BioRad) to perform SDS- PAGE analysis using Precision Plus Protein Dual Xtra Prestained Protein Standards (BioRad) as ladder. Exemplary antibody structures of the Examples are demonstrated in Figures 8 and 14 to have been successfully produced with stability and degradation resistant features. The compositions provided herein can further comprise a pharmaceutically acceptable carrier. As used herein, “pharmaceutically acceptable carrier” includes any and all salts, buffering agents, preservatives, compatible carriers, solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like that are physiologically compatible. A pharmaceutically acceptable carrier also includes one or more compatible solid or liquid fillers, diluents or encapsulating substances that are suitable for administration into a human. The term “carrier” denotes an organic or inorganic ingredient, natural or synthetic, with which the active ingredient is combined to facilitate the application. A carrier may be suitable for oral, intravenous, intramuscular, subcutaneous, or parenteral (e.g., by injection or infusion) administration. In some embodiments, a composition may conveniently be presented in unit dosage form and may be prepared by any of the methods well-known in the art of pharmacy. In some embodiments, compositions are prepared by uniformly and intimately bringing the active compound into association with a liquid carrier, a finely divided solid carrier, or both, and then, if necessary, shaping the product. Compositions suitable for administration may comprise a sterile aqueous or non- aqueous preparation. This preparation may be formulated according to known methods using suitable dispersing or wetting agents and suspending agents. The sterile injectable preparation also may be a sterile injectable solution or suspension in a non-toxic parenterally- acceptable diluent or solvent. Among the acceptable vehicles and solvents that may be employed are water, Ringer's solution, and isotonic sodium chloride solution. In addition, sterile, fixed oils are conventionally employed as a solvent or suspending medium. For this purpose any bland fixed oil may be employed including synthetic mono- or di-glycerides. In addition, fatty acids such as oleic acid may be used in the preparation of injectables. Carrier formulations suitable for administration can be found in Remington's Pharmaceutical Sciences, Mack Publishing Co., Easton, Pa. Any of the compositions provided herein may be sterile. Compositions as provided herein, in some embodiments, may be administered in effective amounts to a subject. "Administering" or "administration" or “administer” means providing a material to a subject in a manner that is pharmacologically useful. The term is intended to include “causing to be administered”. “Causing to be administered” means causing, urging, encouraging, aiding, inducing or directing, directly or indirectly, another party to administer or ingest the material. An “effective amount” is that amount of an active compound that alone, or together with further doses, produces a desired response. Such effective amounts will depend, of course, on the particular condition being treated, the severity of the condition, the individual patient parameters including age, physical condition, size and weight, the duration of the treatment, the nature of concurrent therapy (if any), the specific route of administration and like factors within the knowledge and expertise of the health practitioner. These factors are well known to those of ordinary skill in the art and can be addressed with no more than routine experimentation. It is generally preferred that a maximum dose of the individual components or combinations thereof be used, that is, the highest safe dose according to sound medical judgment. It will be understood by those of ordinary skill in the art, however, that a patient / subject may insist upon a lower dose or tolerable dose for medical reasons, psychological reasons or for virtually any other reason. The doses of compositions administered to a subject can be chosen in accordance with different parameters, in particular in accordance with the mode of administration used and the state of the subject. Other factors include the desired period of treatment. As used herein, the term “subject” is intended to include humans and non-human animals, including warm blooded mammals, such as humans and primates; avians; domestic household or farm animals such as cats, dogs, sheep, goats, cattle, horses and pigs; laboratory animals such as mice, rats and guinea pigs; fish; reptiles; zoo and wild animals; and the like. In one aspect, a method of administering any one of the antibody structures or any one of the compositions provided herein to a subject is provided. In one embodiment, the administering is done by oral delivery. Methods of Producing Antibody Structures with CDRs Comprising a Rigid Structure The methods provided herein allows the antibody structures comprising at least one CDR comprising a rigid structure on a desired antibody scaffold to be designed by, for example, inputting structural requirements and / or a target sequence. The target input structure can, for example, a crystal structure or a predicted structure. The resulting antibody can take a variety of formats, including nanobody and scFv. Antibody structures with CDRs comprising a rigid structure can be designed by first generating a protein backbone and then generating an amino acid sequence for that backbone. The resulting designs can be, optionally, evaluated with computational metrics. The backbones can be generated in a variety of ways. For example, backbones for antibody structures with at least one CDR comprising a rigid structure can be generated computationally using diffusion model, such as a denoising diffusion probabilistic model. Such a model, generally, is a generative model that outputs backbone atom coordinates for a protein. Such models can be used with fold conditioning, which in some embodiments allows for the specification of a protein fold. In some embodiments, the fold can be specified by providing secondary structural elements, such as each secondary structural element that is desired of the desired antibody structure (e.g., alpha helix, beta sheet, or loop), total length, or length of specific elements, number of residues, and / or contacts with other secondary structural elements. As another example, backbones can be designed to bind to a target by providing a model with a target structure and desired residues on that structure (e.g., the epitope). Backbones for antibody structures with CDRs comprising a rigid structure can be generated in reference to binding to a target by, for example, a grafting approach. In one example of such an approach, first, a backbone for an antibody structure comprising a rigid structure is generated without providing a target, using a diffusion model with fold conditioning to specify the fold. A backbone, such as with two or three rigid structures (e.g., helices in a helical bundle fold), can then be generated that binds a target using a diffusion model with fold conditioning as well as a target structure and target residues on that structure. In such an example, the at least two rigid structures (e.g., helices) can then be grafted onto the backbone. In one example, a method can be performed comprising, A) 1) selecting a target structure and, optionally, epitope residues (e.g., an epitope) on the structure, 2) using a diffusion model (e.g., RoseTTAFold diffusion model) with fold conditioning to generate an antibody structure to the target and, optionally, the epitope residues (e.g., epitope), 3) providing a backbone comprising one, two or three rigid structures (e.g., helices) to specify a fold, and 4) using a model (e.g., ProteinMPNN model) to determine a sequence for the antibody structure, and 5) optionally, using a model (e.g., AlphaFold2) to predict and / or evaluate the binder and / or binding interface; B) 1) using a diffusion model with fold conditioning to generate a backbone with CDRs comprising a rigid structure, such as by providing a blueprint specifying a fold, 2) using a model (e.g., ProteinMPNN model) to determine a sequence for the backbone with CDRs comprising a rigid structure; and 3) optionally, using a model (e.g., AlphaFold2) to predict and / or evaluate the structure; and C) 1) grafting the backbone with CDRs comprising a rigid structure onto the antibody structure (e.g., by using structural alignment). The foregoing may also comprise redesigning one or more of the residues using a model (e.g., ProteinMPNN) to accommodate the grafting and / or using a model (e.g., AlphaFold2) to predict and / or evaluate the antibody structure with CDRs comprising a rigid structure binding to the target. As a further example, a whole-antibody approach can be taken. An example of such approach comprises generating a backbone for an antibody structure with CDRs comprising a rigid structure using a target structure and target residues on that structure and using a diffusion model with fold conditioning. In one embodiment, a method can be performed comprising 1) selecting a target structure and, optionally, epitope residues (e.g., an epitope) on the structure; 2) using a diffusion model (e.g., RoseTTAFold diffusion model) with fold conditioning to generate an antibody structure with one, two, or three CDRs comprising a rigid structure (e.g., helix) that binds to the target and, optionally, the epitope residues; 3) using a model (e.g., ProteinMPNN model) to determine a sequence for the antibody with CDRs comprising a rigid structure (e.g., helix); and 4) optionally, using a model (e.g., AlphaFold2) to predict and / or evaluate the structure and / or binding interface. The foregoing method may also comprise using a diffusion model with fold conditioning to generate a backbone with CDRs comprising a rigid structure (e.g., helix), such as by providing a blueprint specifying a fold. The result of the foregoing approaches can be a designed backbone for an antibody structure with CDRs comprising a rigid structure (e.g., helix) in complex with a target structure, docked at specified target residues on that structure. The methods provided herein can also include a step of generating amino acid sequences, which step can occur before or after the generation of the backbone. Amino acid sequences can be generated, for example, using a message-passing neural network model. For example, the sequences for a target and an antibody scaffold can be provided to the model along with the backbone structure of the complex (consisting of target and antibody structure with CDRs comprising a rigid structure (e.g., helix)), and a sequence is generated for the CDRs comprising a rigid structure (e.g., helix) in this context. When a grafting approach is employed, the sequences can be designed either before or after the rigid structures (e.g., helices) are grafted onto the antibody structure with CDRs comprising a rigid structure (e.g., helix). If necessary for improving predicted accuracy and confidence, some of the amino acids of the antibody scaffold sequence may be redesigned to better support the CDRs comprising a rigid structure (e.g., helix). In particular, the amino acids neighboring the CDRs comprising a rigid structure (e.g., helix) may be redesigned. In some embodiments, optional partial diffusion can be used to refine and generate more designs. The diffusion model may be used in a ‘partial diffusion’ mode to redesign a designed antibody structure with CDRs comprising a rigid structure (e.g., helix). This method can involve adding some noise to the backbone coordinates, then using the diffusion model to generate a new backbone from the ‘noisy’ backbone. A new sequence is then generated for this new backbone. This method can provide additional structural variation and yield improved designs. Designs generated as provided herein can be evaluated in some embodiments. Protein structure prediction models may be used. Such models can provide a predicted structure given the sequence of the design, which can be aligned to the design structure model to assess accuracy. These models also can provide a measure of confidence in the prediction. The methods provided herein can include steps to design antibody structures with the specific feature(s) provided herein. Any one of the methods provided herein, can include one or more steps to design an antibody structure to have one or more features as provided herein. As an example, a pH responsive antibody structure can be designed to target an epitope featuring histidine residues. One or multiple histidine residues can be provided on the target as target residues. The histidine residues can be modeled in either their protonated or deprotonated state. Generated antibody structures can be selected that make interactions with either the protonated or deprotonated histidine residue(s), depending on the desired pH- dependent binding behavior. As another example, a pH responsive antibody structure can be designed to incorporate histidine residues when generating the sequences of the CDRs comprising a rigid structure. These histidine residues can be preferentially used in the sequence design, such as by providing amino acid composition bias weights. These weights bias the sequence design process to use histidine residues with a higher probability when designing the interface. The histidine residues can be modeled in either their protonated or deprotonated state. Generated antibody structures with CDRs comprising a rigid structure can be selected that feature one or more histidine residues in their CDRs comprising a rigid structure. These antibody structures may make interactions with the target using either the protonated or deprotonated histidine residue(s), depending on the desired pH-dependent binding behavior. Any one of the methods provided herein, can include any one or more of the foregoing steps to design an antibody structure to be pH responsive. Any one of the methods provided herein, can include one or more steps to select or test for pH responsiveness. Any one of the methods provided herein, can include one or more steps to design an antibody structure to be stable or resistant to degradation at a specific pH, such as a pH of 6.5. Any one of the methods provided herein, can include one or more steps to select or test for pH resistance, such as at a pH of 6.5. Any one of the methods provided herein, can include one or more steps to design an antibody structure to be thermostable or be resistant to degradation at higher temperatures, such as 37ºC. Any one of the methods provided herein, can include one or more steps to select or test for thermostability or resistance to degradation at higher temperatures, such as 37ºC. Any one of the methods provided herein, can include one or more steps to design an antibody structure to be stable or resistant to degradation by one or more proteases. Any one of the methods provided herein, can include one or more steps to select or test for proteolytic stability or resistance or resistance to degradation by one or more proteases. Any one of the methods provided herein, can include one or more steps to design an antibody structure to be stable or resistant to degradation in an intestinal environment. Any one of the methods provided herein, can include one or more steps to design an antibody structure to be stable or resistant to degradation in simulated intestinal fluid, such as that of Table 2. Any one of the methods provided herein, can include one or more steps to select or test for stability or resistance to degradation in an intestinal environment. Any one of the methods provided herein, can include one or more steps to select or test for stability or resistance to degradation in a simulated intestinal fluid, such that of Table 2. The present invention is further illustrated by the following Examples, which in no way should be construed as further limiting. The entire contents of all of the references (including literature references, issued patents, published patent applications, and copending patent applications) cited throughout this application are hereby expressly incorporated by reference. However, the citation of any reference is not intended to be admission that said reference is prior art. EXAMPLES Example 1 - Nanobody with Helical CDR1 and CDR3 Designed to Bind to PD-L1 An exemplary nanobody backbone with helical CDR1 and CDR3 was generated with PD-L1 as the target structure and with target residues on PD-L1 inputted into a diffusion model with fold conditioning. The PD-L1 target sequence was as follows: NAFTVTVPKDLYVVEYGSNMTIECKFPVEKQLDLAALIVYWEMEDKNIIQFVHGEED LKVQHSSYRQRARLLKDQLSLGNAALQITDVKLQDAGVYRCMISYGGADYKRITVKV NAPY (SEQ ID NO:1) The designed nanobody sequence with helical CDR1 and CDR3 sequence (helical CDR1 and CDR3 in bold) was as follows: MITIETTVTAKGVNGKLVATVTLTAKGTKNKSDLARAGFLVASSVVTVTVYDKNGNV LSTATYSLGGATTTTTGAETVTLTLVSYSGTTATVQATSSAAASDVKSVTAAASPGS PVALKAFEELTGKPVTFTSATADVTNAD (SEQ ID NO:2) Figure 3 shows the resulting designed nanobody. Figure 4 shows the designed nanobody with helical CDR1 and CDR3 designed to bind PD-L1 with interface detail of the predicted structure complex. An evaluation of the designed nanobody was performed. The computational metrics were as follows: i. AlphaFold2 predicted local distance difference test (pLDDT): 88.1 ii. AlphaFold2 interaction predicted aligned error (pAE): 9.572 iii. AlphaFold2 monomer root mean-squared deviation (RMSD): 0.884Å With these metrics, this design can be considered an in silico success, for example, according to References 5 and 7: AlphaFold2 monomer pLDDT > 80, AlphaFold2 interaction pAE < 10, AphaFold2 monomer RMSD < 1Å. Example 2 – Single Domain Antibodies with Helical CDRs Designed Materials and Methods Generation of Backbones for Antibodies with Helical CDRs Backbones were computationally generated using a denoising diffusion probabilistic model (hereafter ‘diffusion model’), which is a generative model that outputs backbone atom coordinates for a protein. This model was used with fold conditioning, a method which allows for the specification of a protein fold. The fold was specified by providing each secondary structural element (alpha helix, beta sheet, or loop), its length in number of residues, and its contacts with other secondary structural elements. For this example, a single domain antibody fold was specified with CDR1 and CDR3 replaced by alpha helices. Backbones were designed to bind to a target by providing the model with a target structure and desired residues on that structure (i.e., the epitope). Backbones for these examples were designed using the docking approach. First, a backbone for an antibody with helical CDRs was generated without providing a target, using the diffusion model with fold conditioning to specify the fold. Then, a backbone consisting of two or three helices in a helical bundle fold were generated to bind to a target, using the diffusion model with fold conditioning as well as a target structure and target residues on that structure. Two of these helices were then used to dock the antibody with helical CDRs backbone. The result was a designed backbone for an antibody with helical CDRs in complex with a target structure, docked at specified target residues on that structure. Generation of Sequences Amino acid sequences were generated for the backbones using a message-passing neural network model. The sequences for the target and the antibody scaffold were provided to the model along with the backbone structure of the complex (consisting of target and antibody with helical CDRs), and the sequence was generated for the helical CDRs in this context. If necessary for improving predicted accuracy and confidence, some of the amino acids of the antibody scaffold sequence were redesigned to better support the helical CDRs. In particular, the amino acids neighboring the helical CDRs were redesigned. Evaluation of Computational Designs Designs were evaluated using protein structure prediction models. These models provide a predicted structure given the sequence of the design, which can be aligned to the design structure model to assess accuracy. These models also provide a measure of confidence in the prediction. Designs that are predicted with higher accuracy and higher confidence are more likely to function experimentally as designed. In Vitro Production of Designed Single Domain Antibodies with Helical CDRs Exemplary single domain antibodies with helical CDRs were produced using transient Chinese hamster ovary (CHO) cell expression and His-tag purification. Plasmid production: a. Synthesized gene fragments were ordered (eBlock gene fragments, IDT) consisting of codon-optimized sequences for designed single domain antibodies with helical CDRs, including 6xHis tag and secretion signal. b. The pcDNA3.4 vector was modified to remove BsaI cut sites and linearized using PCR. Gene fragments were cloned into the vector using Golden Gate assembly. c. Golden Gate assembly product was transformed into competent TOP10 E. coli (Thermo Fisher) and grown overnight in 1mL TB. Then plasmids were purified (ZymoPURE 96 Plasmid Miniprep Kit) from overnight culture. CHO cell transfection and expression: Purified plasmid was used to transfect CHO cells using the ExpiCHO Expression System Kit (Thermo Fisher) in 96 well (1mL) format. The single domain antibodies with helical CDRs were expressed in CHO cells. His-tag purification: CHO supernatant containing single domain antibodies with helical CDRs was harvested following expression. Single domain antibodies with helical CDRs were purified from CHO expression supernatant using His-tag immobilized metal affinity chromatography (IMAC) in 96 well format using nickel- nitrilotriacetic acid resin columns (HisPur Ni-NTA Spin Plates, Thermo Fisher). Results Antibodies with helical CDRs targeting human insulin receptor (InsR) (Accession # P06213-2 and as set forth in SEQ ID NO: 3), were designed by first generating a protein backbone, then generating an amino acid sequence for that backbone. The resulting designs were evaluated with computational metrics. The subsequence used for computational design is shown below in bold. MATGGRRGAAAAPLLVAVAALLLGAAGHLYPGEVCPGMDIRNNLTRLHELENCSVIEGHLQILLMFKT RPEDFRDLSFPKLIMITDYLLLFRVYGLESLKDLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNL MNITRGSVRIEKNNELCYLATIDWSRILDSVEDNYIVLNKDDNEECGDICPGTAKGKTNCPATVINGQ FVERCWTHSHCQKVCPTICKSHGCTAEGLCCHSECLGNCSQPDDPTKCVACRNFYLDGRCVETCPPPY YHFQDWRCVNFSFCQDLHHKCKNSRRQGCHQYVIHNNKCIPECPSGYTMNSSNLLCTPCLGPCPKVCH LLEGEKTIDSVTSAQELRGCTVINGSLIINIRGGNNLAAELEANLGLIEEISGYLKIRRSYALVSLSF FRKLRLIRGETLEIGNYSFYALDNQNLRQLWDWSKHNLTITQGKLFFHYNPKLCLSEIHKMEEVSGTK GRQERNDIALKTNGDQASCENELLKFSYIRTSFDKILLRWEPYWPPDFRDLLGFMLFYKEAPYQNVTE FDGQDACGSNSWTVVDIDPPLRSNDPKSQNHPGWLMRGLKPWTQYAIFVKTLVTFSDERRTYGAKSDI IYVQTDATNPSVPLDPISVSNSSSQIILKWKPPSDPNGNITHYLVFWERQAEDSELFELDYCLKGLKL PSRTWSPPFESEDSQKHNQSEYEDSAGECCSCPKTDSQILKELEESSFRKTFEDYLHNVVFVPRKTSS GTGAEDPRPSRKRRSLGDVGNVTVAVPTVAAFPNTSSTSVPTSPEEHRPFEKVVNKESLVISGLRHFT GYRIELQACNQDTPEERCSVAAYVSARTMPEAKADDIVGPVTHEIFENNVVHLMWQEPKEPNGLIVLY EVSYRRYGDEELHLCVSRKHFALERGCRLRGLSPGNYSVRIRATSLAGNGSWTEPTYFYVTDYLDVPS NIAKIIIGPLIFVFLFSVVIGSIYLFLRKRQPDGPLGPLYASSNPEYLSASDVFPCSVYVPDEWEVSR EKITLLRELGQGSFGMVYEGNARDIIKGEAETRVAVKTVNESASLRERIEFLNEASVMKGFTCHHVVR LLGVVSKGQPTLVVMELMAHGDLKSYLRSLRPEAENNPGRPPPTLQEMIQMAAEIADGMAYLNAKKFV HRDLAARNCMVAHDFTVKIGDFGMTRDIYETDYYRKGGKGLLPVRWMAPESLKDGVFTTSSDMWSFGV VLWEITSLAEQPYQGLSNEQVLKFVMDGGYLDQPDNCPERVTDLMRMCWQFNPKMRPTFLEIVNLLKD DLHPSFPEVSFFHSEENKAPESEELEMEFEDMENVPLDRSSHCQREEAGGRDGGSSLGFKRSYEEHIP YTHMNGGKKNGRILTLPRSNPS (SEQ ID NO:3) The first exemplary single domain antibody (nanobody / VHH) featuring helical CDRs (helical CDR1 and helical CDR3) targeting human insulin receptor was designed and had the sequence as set forth as SEQ ID NO: 4. The CDR1 alpha helix had the sequence EDRDLFLGALIF (SEQ ID NO: 5), and the CDR3 alpha helix had the sequence EDVKELFEKA (SEQ ID NO: 6). hCDR_InsR_1 sequence with helical CDR1 and CDR3 in bold: EIQMLASPAVANQKTGSVRSSCAFSPEDRDLFLGALIFGGTISCYVQAKSGGLELAAAYDGKTGQTYN ADSFKGRATISVDNSKGTVTCQVNVPDAEDVKAVICKLEMPDSEDVKELFEKAGIKSPVTQTAQVTLS S (SEQ ID NO:4) Another exemplary single domain antibody (nanobody / VHH) featuring helical CDRs (helical CDR1 and helical CDR3) targeting human insulin receptor was designed and had the sequence as set forth as SEQ ID NO: 7. The CDR1 alpha helix had the sequence EVAELIKQCLDL (SEQ ID NO: 8), and the CDR3 alpha helix had the sequence EAYSALCTSELERY (SEQ ID NO: 9). hCDR_InsR_2 sequence with helical CDR1 and CDR3 in bold: EAQVLASAGPANQATGSARFSCAFSPEVAELIKQCLDLGNSISCVVQAKGGGTLGVVAIDSSGNATVY AASGGVRVTGSWDESKGTLTCQVTSPRAEDTVVVYCARASGDEAYSALCTSELERYGLVGQSAQATLS S (SEQ ID NO:7) Antibodies with helical CDRs targeting human tropomyosin receptor kinase A (TrkA) (Accession # P04629.4 and as set forth in SEQ ID NO: 6), were also designed by first generating a protein backbone, then generating an amino acid sequence for that backbone. The resulting designs were evaluated with computational metrics. The subsequence used for computational design is shown below in bold. MLRGGRRGQLGWHSWAAGPGSLLAWLILASAGAAPCPDACCPHGSSGLRCTRDGALDSLHHLPGAENL TELYIENQQHLQHLELRDLRGLGELRNLTIVKSGLRFVAPDAFHFTPRLSRLNLSFNALESLSWKTVQ GLSLQELVLSGNPLHCSCALRWLQRWEEEGLGGVPEQKLQCHGQGPLAHMPNASCGVPTLKVQVPNAS VDVGDDVLLRCQVEGRGLEQAGWILTELEQSATVMKSGGLPSLGLTLANVTSDLNRKNVTCWAENDVG RAEVSVQVNVSFPASVQLHTAVEMHHWCIPFSVDGQPAPSLRWLFNGSVLNETSFIFTEFLEPAANET VRHGCLRLNQPTHVNNGNYTLLAANPFGQASASIMAAFMDNPFEFNPEDPIPVSFSPVDTNSTSGDPV EKKDETPFGVSVAVGLAVFACLFLSTLLLVLNKCGRRNKFGINRPAVLAPEDGLAMSLHFMTLGGSSL SPTEGKGSGLQGHIIENPQYFSDACVHHIKRRDIVLKWELGEGAFGKVFLAECHNLLPEQDKMLVAVK ALKEASESARQDFQREAELLTMLQHQHIVRFFGVCTEGRPLLMVFEYMRHGDLNRFLRSHGPDAKLLA GGEDVAPGPLGLGQLLAVASQVAAGMVYLAGLHFVHRDLATRNCLVGQGLVVKIGDFGMSRDIYSTDY YRVGGRTMLPIRWMPPESILYRKFTTESDVWSFGVVLWEIFTYGKQPWYQLSNTEAIDCITQGRELER PRACPPEVYAIMRGCWQREPQQRHSIKDVHARLQALAQAPPVYLDVLG (SEQ ID NO:10) An exemplary single domain antibody (nanobody / VHH) featuring helical CDRs (helical CDR1 and helical CDR3) targeting tropomyosin receptor kinase A was designed and had the sequence as set forth in SEQ ID NO:11. The CDR1 alpha helix had the sequence EDMANLLALMKA (SEQ ID NO: 12), and the CDR3 alpha helix had the sequence EVALMARLV (SEQ ID NO: 13). hCDR_ TrkA_1 sequence with helical CDR1 and CDR3 in bold: EIQMLASGAVANQKTGSVRSSCAFSPEDMANLLALMKAGATISCYVQAKSGGLELAAAYDGKTGQTYN ADSFKGRGTISVDNSKGTVTCQVNVPDAEDVKAVICKLELPGTPEVALMARLVGVREPVTQTAQVTLS S (SEQ ID NO:11) Example 3 – Binding and Stability of Exemplary Designed Antibodies with Helical CDRs Materials and Methods Binding Affinity Binding was assessed by loading biotinylated human InsR (ACROBiosystems) onto streptavidin coated biosensor. Association and dissociation were measured using His-tag purified sample, with background subtracted from both a blank sample to remove buffer effects as well as an off-target biosensor to remove nonspecific binding from purification off- products. Fitting curves were used as well as a conservative value for typical single domain antibody association rates (105M-1s-1). Simulated Intestinal Fluid (SIF) Stability Assay Protocol Stability was assessed using SDS-PAGE according to the below protocol. 1. Aliquot 7.5 uL of His-tag purified protein sample in elution buffer (25 mM NaPhosphate pH 7.4, 275 mM NaCl, 250 mM Imidazole). 2. Add 7.5 uL of 2x freshly prepared SIF solution (see Table 2 for recipe; buffer mixes sourced from BioRelevant) with added proteases trypsin at 60 μg / mL and chymotrypsin at 60 μg / mL (yielding 30 μg / mL each at 1x). 3. Incubate at 37ºC for 1 hour and 4 hour timepoints. For 0 hour timepoint, add elution buffer to match the volume of the digestion timepoints. 4. Add 5.5uL of 4x Tris / Glycine / SDS running buffer (BioRad) and 1uL 1M DTT to each sample and heat 5 minutes at 95C to end SIF incubation. 5. Run samples immediately on 4-20% TGX gel (BioRad) to perform SDS-PAGE analysis using Precision Plus Protein Dual Xtra Prestained Protein Standards (BioRad) as ladder. Results Binding was assessed according to the above. Association and dissociation were measured (separated by dashed vertical line, signal depicted in gray in the Figures). It was estimated that the binding affinity of the exemplary designed single domain antibodies with helical CDRs for InsR (Figure 7) and TrkA (Figure 11) was at least 100 nM and likely under 10 nM. A higher binding affinity corresponds to a lower dissociation constant. Stability in simulated intestinal fluid was also assessed (according to the above) by incubating His-tag purified sample at 37ºC in simulated intestinal buffer with proteases trypsin and chymotrypsin each added at 30 μg / mL. Samples were then analyzed using SDS- PAGE. Samples were expected to run at around 15 kDa given their molecular weight. Samples were seen between the 10 kDa and 15 kDa ladder markers at the 0 hour time point, with flanking trypsin and chymotrypsin protease bands visible at 15 kDa and just over 10 kDa (in addition to bands around 25 kDa) in the 1 hour and 4 hour time points. Reference His-tag purified sample is visible at 0h (arrow), and background protease bands are visible at 1h and 4h. For the exemplary designed single domain antibodies with helical CDRs, intact sample is visible on the gel in a band between 10 kDa and 15 kDa at the 1 hour timepoint but is not apparent at the 4 hour timepoint. The results indicate that the exemplary designed single domain antibodies with helical CDRs survived for at least 1 hour of incubation in SIF (InsR (Figure 8) and TrkA (Figure 14)). References: 1. Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021). https: / / doi.org / 10.1038 / s41586-021- 2. Minkyung Baek et al., Accurate prediction of protein structures and interactions using a three-track neural network. Science 373, 871-876(2021). DOI:10.1126 / science.abj8754 3. Ruffolo, J.A., Chu, LS., Mahajan, S.P. et al. Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies. Nat Commun 14, 2389 (2023). https: / / doi.org / 10.1038 / s41467-023-38063-x 4. Cao, L., Coventry, B., Goreshnik, I. et al. Design of protein-binding proteins from the target structure alone. Nature 605, 551–560 (2022). https: / / doi.org / 10.1038 / s41586- 5. Watson, J.L., Juergens, D., Bennett, N.R. et al. De novo design of protein structure and function with RFdiffusion. Nature 620, 1089–1100 (2023). 6. Vázquez Torres, S., Leung, P.J.Y., Venkatesh, P. et al. De novo design of high- affinity binders of bioactive helical peptides. Nature 626, 435–442 (2024). 7. Bennett, N.R., Coventry, B., Goreshnik, I. et al. Improving de novo protein binder design with deep learning. Nat Commun 14, 2625 (2023). https: / / doi.org / 10.1038 / s41467-023-38328-5 8. Svilenov, H.L., Sacherl, J., Protzer, U. et al. Mechanistic principles of an ultra-long bovine CDR reveal strategies for antibody design. Nat Commun 12, 6737 (2021). https: / / doi.org / 10.1038 / s41467-021-27103-z 9. Kadonosono, T., Yimchuen, W., Ota, Y. et al. Design Strategy to Create Antibody Mimetics Harbouring Immobilised Complementarity Determining Region Peptides for Practical Use.Sci Rep 10, 891 (2020). https: / / doi.org / 10.1038 / s41598-020-57713-4 10. Abskharon R, Pan H, Sawaya MR, et al. Structure-based design of nanobodies that inhibit seeding of Alzheimer's patient-extracted tau fibrils. Proc Natl Acad Sci U S A. 2023;120(41):e2300258120. doi:10.1073 / pnas.2300258120

Claims

CLAIMS What is claimed is:

1. An antibody structure comprising an antibody scaffold and at least one CDR comprising a helical structure, wherein the antibody structure binds a target, and wherein the helical structure is an alpha helix.

2. The antibody structure of claim 1, wherein the antibody structure comprises at least two CDRs each comprising a helical structure, wherein each of the helical structures is an alpha helix.

3. The antibody structiure of claim 1 or 2, wherein the antibody scaffold is that of a single-domain antibody (sdAb), single-chain variable fragment (scFv), Fab’, fragment antigen binding (Fab), F(ab’)2 or a full-length antibody.

4. The antibody structure of any of claims 1-3, wherein the at least one CDR comprising a helical structure replaces a CDR1 or CDR3.

5. The antibody structure of claim 2 or 3, wherein the at least two CDRs comprising a helical structure replaces a CDR1 and CDR3.

6. The antibody structure of any one of claims 1-5, wherein the antibody structure has a binding affinity of at least 10-7M.

7. The antibody structure of any one of claims 1-6, wherein the antibody structure has a binding affinity of no more than 10-9M.

8. The antibody structure of any one of claims 1-7, wherein the antibody structure is resistant to degradation at an intestinal pH.

9. The antibody structure of claim 8, wherein the intestinal pH is 6.5.

10. The antibody structure of any one of claims 1-9, wherein the antibody structure is resistant to degradation at 37ºC.

11. The antibody structure of any one of claims 1-10, wherein the antibody structure is resistant to degradation by one or more proteases.

12. The antibody structure of claim 11, wherein the one or more proteases is trypsin and / or chymotrypsin.

13. The antibody structure of any one of claims 1-12, wherein the antibody structure is resistant to degradation in simulated intestinal fluid.

14. The antibody structure of claim 13, wherein the antibody structure is resistant to degradation in simulated intestinal fluid for at least 1 hour.

15. The antibody structure of any one of claims 1-14, wherein each CDR comprising a helical structure is 5-18 residues in length.

16. The antibody structure of claim 15, wherein each CDR comprising a helical structure is 6-14 residues in length.

17. The antibody structure of any one of claims 1-16, wherein the antibody structure further comprises a linker at the N-terminus and / or C-terminus of each CDR comprising a helical structure.

18. The antibody structure of claim 17, wherein the linker does not form an alpha helix or beta sheet secondary structure.

19. The antibody structure of claim 17 or 18, wherein the linker at the N-terminus is 1-8 residues in length.

20. The antibody structure of claim 19, wherein the linker at the N-terminus is 1-5 residues in length.

21. The antibody structure of any one of claims 17-20, wherein the linker at the C- terminus of a CDR comprising a helical structure replacing a CDR1 is 1-8 residues in length.

22. The antibody structure of claim 21, wherein the linker at the C-terminus of a CDR comprising a helical structure replacing a CDR1 loop is 1-5 residues in length.

23. The antibody structure of any one of claims 17-20, wherein the linker at the C- terminus of a CDR comprising a helical structure replacing a CDR3 loop is 1-10 residues in length.

24. The antibody structure of claim 23, wherein the linker at the C-terminus of a CDR comprising a helical structure replacing a CDR3 loop is 2-7 residues in length.

25. A composition comprising the antibody structure of any one of claims 1-24, and further comprising a pharmaceutically acceptable carrier.

26. A method, comprising administering an antibody structure of any one of claims 1-24 or the composition of claim 25 to a subject.

27. A method for producing an antibody structure comprising at least one CDR comprising a helical structure, wherein the antibody structure binds a target, comprising: a) computationally generating a backbone comprising at least one alpha helix and an antibody scaffold, b) generating an amino acid sequence such that the at least one CDR comprising a helical structure binds to the target, and c) optionally, evaluating the produced antibody structure using a protein structure prediction model.

28. The method of claim 27, wherein a) comprises using a diffusion model with fold conditioning, wherein the fold is specified with secondary structural elements, which secondary structural elements comprise the at least one alpha helix and one or more structural elements of the antibody scaffold.

29. The method of claim 27, wherein a) comprises i) generating a backbone comprising an antibody scaffold using a diffusion model with fold conditioning, wherein the fold is specified with secondary structural elements, without providing a target, ii) generating a backbone comprising at least two alpha helices that bind to a target using a diffusion model with fold conditioning as well as a target structure and target residues on the target structure, and iii) grafting two of the helices of ii) onto the backbone of i).

30. The method of claim 29, wherein b) occurs before or after iii).

31. The method of claim 27, wherein a) comprises providing a target structure and target residues on the target structure using a diffusion model with fold conditioning, wherein the fold is specified with secondary structural elements, which secondary structural elements comprise the at least one alpha helix and one or more structural elements of the antibody scaffold.

32. The method of any one of claims 27-31, wherein b) comprises using a message- passing neural network model.

33. The method of any one of claims 27-32, further comprising assessing, modeling or selecting for resistance to degradation at an intestinal pH.

34. The method of claim 33, wherein the intestinal pH is 6.

5.

35. The method of any one of claims 27-34, further comprising assessing, modeling or selecting for resistance to degradation at 37ºC.

36. The method of any one of claims 27-35, further comprising assessing, modeling or selecting for resistance to degradation by one or more proteases.

37. The method of claim 36, wherein the one or more proteases is trypsin and / or chymotrypsin.

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