WO2019074940A1

WO2019074940A1 - Integrated platform for target and specificity information-derived binding partner selection

Info

Publication number: WO2019074940A1
Application number: PCT/US2018/055036
Authority: WO
Inventors: Mohan Srinivasan; Matthew Greving
Original assignee: Healthtell Inc.
Priority date: 2017-10-09
Filing date: 2018-10-09
Publication date: 2019-04-18
Also published as: TW201922771A

Abstract

The present disclosure relates to peptide libraries with sequences derived from specific proteomes, or select target proteins, and methods of using such libraries for the characterization of binding partners of target proteins. The disclosed peptide libraries provide a useful platform for the identification of binding partner interactions with a large library of peptide sequences. The present disclosure further provides methods of using libraries comprising related peptides to identify binding partners capable of pan-species reactivity or possessing other desirable properties such as the ability to bind multiple distinct epitopes by an antibody, for example, a monoclonal antibody, of a same target molecule.

Description

INTEGRATED PLATFORM FOR TARGET AND SPECIFICITY INFORMATION- DERIVED BINDING PARTNER SELECTION

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 62/569,926, filed October 9, 2017, the disclosure of which is incorporated herein by reference in its entirety.

BACKGROUND

[0002] Biological-based therapies which bind to known target proteins, such as antibody -based therapies (for example immunotherapies), can provide relief from various disease states.

However the administration of such therapies, can have unwanted effects on a subject. Many of these effects are owed to non-specific binding of the biological-based therapy. The proper characterization of the binding properties of a binding partner, in both the pre-clinical and clinical stages, remains a critical challenge to the development of efficacious therapies.

SUMMARY

[0003] The present disclosure provides a method of selecting a binding partner that binds to a target protein, the method comprising a round of selection comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; (c) contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein; and (d) selecting and isolating the binding domains that bind to one or more peptides from the target protein.

[0004] Also provided herein is a method of eliminating dead-end binding partners from a library of binding domains comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; (c) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; and (d) eliminating the binding domains selected and isolated in step (c). The method may further comprise contacting the isolated binding domains of steps (b) and (c) above to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein. The library of binding domains can comprise a B cell library, a phage library, or combination thereof.

[0005] Also provided herein is a method of selecting a binding partner that binds to two or more peptides of an epitope in a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; (c) selecting and isolating the binding domains that bind to the two or more peptides. In some instances, the methods disclosed herein may further comprise contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0006] Also provided herein is a method of selecting a binding partner that binds to at least two homologs of a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides from at least two homologs of the target protein. In some instances, the method may further comprise (c) contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering multiple homologs of the target protein.

[0007] Also disclosed herein is a method of selecting a binding partner that binds to a functional domain of a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides from the functional domain. In yet other instances, the method may further comprise, contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein; [0008] Also disclosed herein is a method of selecting a binding partner that binds to a target epitope of a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides comprising the target epitope. In still other instances, the method may further comprise contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0009] Also disclosed herein is a method of selecting a multi-specific binding partner comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides comprising the target epitope. In some embodiments, the multispecific binding partner is an antibody. In other instances, the antibody is a multispecific monoclonal antibody. In some instances, the multispecific monoclonal antibody can comprise a bispecific monoclonal antibody or a trispecific monoclonal antibody. In still other instances, the method may further comprise contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0010] Also disclosed herein is a method of developing a polypeptide therapeutic comprising a binding domain, the method comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides comprising the target epitope. In some instances, the method may further comprise (c) contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0011] The aforementioned library of binding domains can be encoded by a polynucleotide. In some instances, the isolated binding domains may be sequenced. The binding domains to one or more peptides can be detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance. The aforementioned isolated binding domains may bind specifically to one peptide from the target protein or to multiple peptides from the target protein. In some instances the methods described above further comprise subjecting the isolated binding domains to at least one additional round of selection. In some instances, the polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection. The isolated binding domains can be binned according to the peptide bound by the isolated binding domain. The library of binding domains can comprise a B cell library from an immunized subject or a B cell library from a naive subject. The first and second peptide arrays can be bound to a microtiter plate, printed or spotted on a substrate, or synthesized in situ on the substrate. The substrate can comprises glass, composite, resin, silicon or combination thereof. One or more of the aforementioned methods can select a desired binding partner, for example, a monoclonal antibody that binds to multiple epitopes of the target protein, a monoclonal antibody that binds to at least two homologs of the target protein, a monoclonal antibody that binds to an active domain of the target protein, or a monoclonal antibody that binds to a target epitope of the target protein.

[0012] In other aspects, provided herein is a method of selecting a binding partner that binds to a target protein, the method comprising: (a) contacting a library of binding domains to a diverse peptide library, wherein the diverse peptide library comprises peptides covering at least a subset of a proteome of an organism, wherein the subset of the proteome comprises one or more peptides of the target protein; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; (c) contacting the selected binding domains from step (b) to a focused peptide library, wherein the focused peptide library comprises peptides covering the target protein; (d) selecting and isolating binding domains that binds to one or more peptides from the target protein in the focused peptide library; and (e) selecting the binding partner from the isolated binding domains of (d). In some embodiments, the diverse peptide library comprises at least 10% of the proteome of an organism. In certain embodiments, at least one isolated binding domain exhibits one or more characteristics selected from the group consisting of specificity to a target, little or no off-target binding, low promiscuity, and pan-species binding. In still further embodiments, the library of binding domains comprises a B cell library, a phage library, or combination thereof. In some embodiments, the binding domains of the library are encoded by polynucleotides. In certain embodiments, the isolated binding domains are sequenced. In some embodiments, the isolated binding domains bind specifically to one peptide from the target protein. In other embodiments, the isolated binding domains bind specifically to multiple peptides from the target protein. In certain embodiments, the method further comprises subjecting the isolated binding domains to at least one additional round of selection comprising steps (a) and (b) or steps (c) and (d). In some embodiments, the isolated binding domains are encoded by polynucleotides, and the polynucleotides are mutated prior the additional round of selection. In other embodiments, the library of binding domains comprises a B cell library from an immunized subject. In other embodiments, the library of binding domains comprises a B cell library from a naive subject. In certain embodiments, the diverse and focused peptide libraries are bound to a microtiter plate. In some embodiments, the diverse and focused peptide libraries are printed on a substrate. In other embodiments, the diverse and focused peptide libraries are spotted on a substrate. In certain embodiments, the substrate comprises glass, composite, resin, silicon or combination thereof. In other embodiments, the method further comprises selecting, isolating, and eliminating the binding domains that bind non-specifically to one or more peptides from the target protein in step (b) or step (d), wherein eliminating the binding domains that bind non-specifically eliminates dead-end binding partners from the library of binding domains. In other embodiments, the binding partner is a monoclonal antibody or an antibody analog scaffold. In certain embodiments, the binding partner comprises a monoclonal antibody that binds to multiple epitopes of the target protein. In some embodiments, the binding partner is a monoclonal antibody that binds to at least two homologs of the target protein. In other embodiments, the binding partner is a monoclonal antibody that binds to an active domain of the target protein. In certain embodiments, the binding partner is a monoclonal antibody that binds to a target epitope of the target protein. In certain embodiments, the method further comprises evaluating one or more of the isolated binding domains with a functional assay. In certain embodiments of the method, the binding partner binds to two or more peptides of an epitope in a target protein, wherein the subset of the proteome of the organism comprises the two or more peptides of the epitope in the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to the two or more peptides of the epitope in the target protein. In some embodiments, the binding partner binds to two or more peptides of an epitope in a target protein, wherein the focused peptide library comprises peptides that cover the two or more peptides of the epitope in the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to the two or more peptides of the epitope in the target protein. In some embodiments, the binding partner binds to at least two homologs of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the at least two homologs of the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to one or more peptides from the at least two homologs of the target protein. In other embodiments, the binding partner binds to at least two homologs of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the at least two homologs of the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to one or more peptides from the at least two homologs of the target protein. In certain embodiments, the binding partner binds to a functional domain of the target protein, wherein the subset of the proteome of the organism comprises the functional domain of the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to one or more peptides from the functional domain of the target protein. In some embodiments, the binding partner binds to a functional domain of the target protein, wherein the focused peptide library comprises one or more peptides from the functional domain of the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to one or more peptides from the functional domain of the target protein. In still further embodiments, the binding partner binds to a target epitope of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the target epitope, and wherein step (b) comprises selecting and isolating the binding domains that bind to the one or more peptides of the target epitope. In some embodiments, the binding partner binds to a target epitope of a target protein, wherein the focused peptide library comprises one or more peptides of the target epitope, and wherein step (d) comprises selecting and isolating the binding domains that bind to the one or more peptides of the target epitope. In certain embodiments, the binding partner is a multispecific monoclonal binding partner. In some embodiments, the multispecific monoclonal binding partner comprises a bispecific monoclonal antibody. In other embodiments, the multispecific monoclonal binding partner comprises a trispecific monoclonal antibody.

[0013] Further provided herein is a system for selecting a binding partner that binds to a target protein, the system comprising: a diverse peptide library comprising peptides covering at least a subset of a proteome of an organism, wherein the subset of the proteome comprises one or more peptides of the target protein; and a focused peptide library, wherein the focused peptide library comprises peptides covering the target protein. In some embodiments, the system further comprises a library of binding domains. In certain embodiments, the diverse peptide library comprises at least 10% of the proteome of an organism. In some embodiments, the library of binding domains comprises a B cell library, a phage library, or combination thereof. In other embodiments, the binding domains of the library are encoded by polynucleotides. In still further embodiments, the library of binding domains comprises a B cell library from an immunized subject. In some embodiments, the library of binding domains comprises a B cell library from a naive subject. In other embodiments, the diverse and focused peptide libraries are bound to a microtiter plate. In some embodiments, the diverse and focused peptide libraries are printed on a substrate. In further embodiments, the diverse and focused peptide libraries are spotted on a substrate. In some embodiments, the substrate comprises glass, composite, resin, silicon or combination thereof.

INCORPORATION BY REFERENCE

[0014] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

[0016] FIG. 1 is a schematic representation of a target epitope space and binding of various epitopes by antibodies in distinct antibody bins.

[0017] FIG. 2 is a schematic representation of a use of the focused library platform or a diverse library platform for selection steering at the eluted clone step. [0018] FIG. 3 is a schematic representation of a use of the focused library platform or a diverse library platform for selection steering at the antigen binding step.

[0019] FIG. 4 is a schematic representation illustrating for example, a use of a focused library platform to select a binding partner that binds to a target protein, or to eliminate off-target recognition while retaining pan-species reactivity.

[0020] FIG. 5 is a schematic representation of putative Her2 epitope maps, key binding residues and rank-ordered affinity as compared to the cognate target. Panel A illustrates the putative epitopes of the anti-Her2 antibody secreting clone 44E7 as detected by the VI 5 array (diverse peptide array). Panel B illustrates the putative epitopes of the anti-Her2 antibody secreting clone D8F12 as detected by the VI 5 array.

[0021] FIG. 6 is a schematic representation of putative Her2 epitope maps, key binding residues and rank-ordered affinity as compared to the cognate target. Panel A illustrates the putative epitopes of the anti-Her2 antibody secreting clone RM228 as detected by the VI 5 array. Panel B illustrates the putative epitopes of the anti-Her2 antibody secreting clone EP105Y as detected by the VI 5 array.

[0022] FIG. 7 illustrates a comparison of putative epitope analysis of a same antibody (3B5 clone) from two distinct vendors. Panel A illustrates the putative epitopes of the anti-Her2 antibody secreting clone TF-3B5 as detected by the VI 5 array. Panel B illustrates the putative epitopes of the anti-Her2 antibody secreting clone SC-3B5 as detected by the VI 5 array.

[0023] FIG. 8 is a schematic representation of putative Her2 epitope maps, key binding residues and rank-ordered affinity as compared to the cognate target. Panel A illustrates the putative epitopes of the anti-Her2 antibody secreting clone C-3 identified by the VI 3 array. Panel B illustrates the putative epitopes of the anti-Her2 antibody secreting clone 29D8 as detected by the VI 3 array.

[0024] FIG. 9 is a schematic representation of putative Her2 epitope maps, key binding residues and rank-ordered affinity as compared to the cognate target. Panel A illustrates the putative epitopes of the anti-Her2 antibody secreting clone Q03B as detected by the VI 3 array. Panel B illustrates the putative epitopes of the anti-Her2 antibody secreting clone SC-3B5 as detected by the VI 3 array.

[0025] FIG. 10 illustrates a comparison of putative Her2 epitope maps potentially bound by the anti-Her2 antibody secreting 44E7 clone. Panel A illustrates the putative epitopes as detected by the VI 3 array. Panel B illustrates the putative epitopes as detected by the VI 5 array. The lower quality alignment suggests that the anti-Her2 antibody secreting 44E7 clone may produce a more promiscuous antibody.

[0026] FIG. 11 illustrates a comparison of putative Her2 epitope maps potentially bound by the anti-Her2 antibody secreting TF-3B5 clone. Panel A illustrates the putative epitopes as detected by the VI 3 array. Panel B illustrates the putative epitopes as detected by the VI 5 array. The higher quality alignment suggests that the anti-Her2 antibody secreting TF-3B5 clone may produce a more specific antibody.

[0027] FIG. 12 depicts a correlation between an increased specificity in a western blot and an increased target coverage quality for the D8F12, 44E7, 29D8, and SC-3B5 anti-Her2 antibody secreting clones.

[0028] FIG. 13 depicts potential off-target proteins for different anti-Her2 antibody secreting clones. Panel A depicts the identification of SIRT1 and ATF6-Beta as potential off-target hit proteins for the anti-Her2 antibody secreting clone Q03B. Panel B depicts the identification of SIRT1 and ATF6-Beta as potential off-target hit proteins for the anti-Her2 antibody secreting clone TF-3B5.

[0029] FIG. 14 depicts potential off-target proteins for different anti-Her2 antibody secreting clones. Panel A depicts the identification of Her4 as a potential off-target protein for the anti- Her2 antibody secreting clone C-3. Panel B depicts the identification of CYP2J2 as a potential off-target hit protein for the anti-Her2 antibody secreting clone 29D8.

[0030] FIG. 15 depicts the high resolution of the Her2 epitope obtained using a focused peptide array. Panels A and B depict the moderate resolution of the Her2 array obtained from screening VI 3 and VI 5 diverse peptide array libraries, and panel C depicts the high resolution of the Her2 epitope obtained from screening a focused peptide array library (V14) created from input sequences identified in the diverse libraries.

[0031] FIG. 16 depicts a summary potential off-target proteins for different anti-Her2 antibody secreting clones. No potential off-target proteins were predicted for clone C-3; ATF-6 Beta was predicted as a potential off-target protein for anti-Her2 antibody secreting clones SC-3B5, TF- 3B5, and Q03B, and Her4 were predicted as a potential off-target protein for anti-Her2 antibody secreting clone TF-3B5.

[0032] FIG. 17 is a dot-blot binding assay evaluating the binding of array-predicted off targets Her4 and ATF-6 Beta compared to binding of Her2 with the anti-Her2 antibody secreting clones C-3, SC-3B5, TF-3B5, and Q03B.

[0033] FIG. 18 is a summary of the dot-blot binding assay intensity for binding of array- predicted off targets Her4 and ATF-6 Beta, compared to binding of Her2, with the anti-Her2 antibody secreting clones C-3, SC-3B5, TF-3B5, and Q03B.

[0034] FIG. 19 depicts on the left side the co-crystal structure of the three antibodies,

Trastuzumab, Ipilimumab, and Nivolumab (dark structure) with their respective targets Her2, CTLA-4, and PD-1 (lighter structure) as obtained by X-ray crystallography. On the right are putative epitope maps of the targets Her2, CTLA-4, and PD-1, with the true positive epitope residues are outlined in white.

[0035] FIG. 20 presents the epitope prediction scoring data used to map the epitopes onto the targets Her2, CTLA-4, and PD-1.

[0036] FIG. 21 is a summary of epitope mapping evaluation of ten therapeutic antibody-target structure complexes, including Trastuzumab, Ipilimumab, and Nivolumab with their respective targets Her2, CTLA-4, and PD-1.

[0037] FIG. 22 depicts putative epitope maps of Her2 as determined using Trastuzumab and a 3.3M peptide library (top image) or 17K≤ 35mer peptide library (bottom image). The epitope confidence indicates (true peptide array binding hit alignments)/(random alignments), with red=1, gray=0, and blue mid-way. [0038] FIG. 23 depicts putative epitope maps of PD-1 as determined with Nivolumab and a 3.3M peptide library (top image) or 17K≤ 35mer peptide library (bottom image). The epitope confidence indicates (true peptide array binding hit alignments)/(random alignments), with red=l, gray=0, and blue mid-way.

[0039] FIG. 24 depicts putative epitope maps of PD-1 as determined with Pembrolizumab and a 3.3M peptide library (top image) or 17K≤ 35mer peptide library (bottom image). The epitope confidence indicates (true peptide array binding hit alignments)/(random alignments), with red=l, gray=0, and blue mid-way.

[0040] FIG. 25 depicts putative epitope maps of CTLA-4 as determined with Ipilimumab and a 3.3M peptide library (top image) or 17K≤ 35mer peptide library (bottom image). The epitope confidence indicates (true peptide array binding hit alignments)/(random alignments), with red=l, gray=0, and blue mid-way.

DETAILED DESCRIPTION

[0041] While various embodiments of the invention are shown and described herein, such embodiments are provided by way of example only. Numerous variations, changes, and substitutions may occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed.

[0042] The term "binding specificity" or "specificity" when referring to a binding event, as used herein, generally refers to the degree to which a binding element or domain binds to a target protein or portion thereof, such as, for example, one or more peptides. For example, binding specificity may refer to the degree to which an antibody differentiates between two different antigens. See, e.g., Immunology and Infectious Disease, S.A. Frank, 2002, Princeton Univ.

Press). For instance, peptide binding specificity can be determined by the difference in the apparent Kd value for each array peptide in the absence of competitor and in the presence of each of serum and non-cognate peptide competitor.

[0043] The term "cognate binding," as used herein, generally refers to non-covalent binding interactions between a binding partner and polypeptide sequence. For example, cognate binding of an antibody and a polypeptide sequence can bind with an apparent affinity ranging from the nanomolar (10^-9 M) range to the picomolar (10^-12 M) range or lower.

[0044] The term "off-target" or "off-target sequence variation" as used herein, generally refers to binding interactions wherein the binding interaction between the array peptide and target varies at one or more positions as compared to the actual target. Both off-target and on-target binding interactions will bind at affinities of at least 10^-8 M, preferably between 10^-8 to 10^-12 or lower.

[0045] The term "promiscuous" or "promiscuous antibody" as used herein, generally refers to an antibody that has indiscriminatory or unselective binding. For example, a promiscuous antibody is an antibody that binds to any molecule that is not the primary antibody target. In another example, a promiscuous antibody is an antibody that binds to one or more molecules other than the primary target of the antibody.

[0046] The term "binding signature," as used herein, generally refers to an antibody's ability to recognize a target and/or off-target peptides on a peptide array.

[0047] The term "peptide", "peptides" or "polypeptides," as used herein, generally refers to polymer chains comprised of amino acid residue monomers which are joined together through amide bonds (peptide bonds). A peptide can be a chain of at least three amino acids, a protein, a recombinant protein, an antigen, an epitope, an enzyme, a receptor, or a structure analogue or combinations thereof. As used herein, the abbreviations for the L-enantiomeric amino acids that form a polypeptide are as follows: alanine (A, Ala); arginine (R, Arg); asparagine (N, Asn); aspartic acid (D, Asp); cysteine (C, Cys); glutamic acid (E, Glu); glutamine (Q, Gin); glycine (G, Gly); histidine (H, His); isoleucine (I, IIe); leucine (L, Leu); lysine (K, Lys); methionine (M, Met); phenylalanine (F, Phe); proline (P, Pro); serine (S, Ser); threonine (T, Thr); tryptophan (W, Trp); tyrosine (Y, Tyr); valine (V, Val).

[0048] The term "binding partner," as used herein, generally refers to a molecule that binds to a target protein, or portion thereof. In some instances, the binding partner comprises an antibody or any portion thereof (for example, an antigen binding portion thereof, such as a fragment containing the antigen-binding region of an antibody). In some instances, the antibody may be a monoclonal antibody. In yet other instances, the binding partner may be an antibody analog scaffold. In still other instances, a binding partner can be a non-antibody (i.e., non- immunoglobulin) protein, including but not limited to, the target-binding region of a receptor, an adhesion molecule, a ligand, an enzyme, a cytokine, a chemokine, or some other protein or protein domain can be selected according to the methods described. Chimeric proteins comprising antibody and non-antibody scaffolds, or portions thereof, and small molecule mimetics of a protein such as cyclic, bicyclic or knotted scaffolds including natural and non- natural amino acids may also be included.

[0049] The term "target protein," as used herein, generally refers to a protein that is selected as a binding "target" for a binding partner, for example, an antibody.

[0050] The term "library of binding domains," as used herein, generally refers to a collection of molecules that recognize an antigen, a portion, or a fragment of any antigen. A library of binding domains can include a monoclonal antibody, a polyclonal antibody, an antibody fragment, a single-chain variable fragment (scFv), a Fab fragment, a single domain antibody, (sdAb), chimeric antibodies, humanized antibodies, antibody drug conjugates or any combination thereof that binds to one or more peptide sequences.

[0051] The term "functional domain," as used herein, generally refers to domains or regions associated with activity of a protein or target molecule, which may be as a result of indirect or direct interactions within the protein or target molecule.

[0052] The term "multispecific monoclonal binding partner," as used herein, generally refers to a binding partner, such as a monoclonal antibody, or scaffold thereof that binds to two or more desired targets.

[0053] The term "panspecies," as used herein, generally refers to the recognition of the binding domain (for example, an antibody) for the same protein or target molecule across at least two species. This includes, for example, binding of an antibody to a human and monkey protein or target molecule.

[0054] The term "polynucleotide" or "nucleic acid" as used herein refers to a polymeric form of nucleotides of any length, either ribonucleotides or deoxyribonucleotides, that comprise purine and pyrimidine bases, purine and pyrimidine analogues, chemically or biochemically modified, natural or non-natural, or derivatized nucleotide bases. Polynucleotides include sequences of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), or DNA copies of ribonucleic acid (cDNA), all of which can be recombinantly produced, artificially synthesized, or isolated and purified from natural sources. The polynucleotides and nucleic acids may exist as single-stranded or double-stranded. The backbone of the polynucleotide can comprise sugars and phosphate groups, as may typically be found in RNA or DNA, or analogues or substituted sugar or phosphate groups. A polynucleotide may comprise naturally occurring or non-naturally occurring nucleotides, such as methylated nucleotides and nucleotide analogues (or analogs).

[0055] The term "subject," as used herein generally refers to mammals. In some instances, a subject can be a human, a monkey, a mouse, a rat, a guinea pig, a dog, a cat, a horse, a rabbit, and various other mammals. Monkeys include monkeys from the Catarrhine family

(Cercopithecoidea superfamily) such as cynomolgus monkey, macaque monkey, and rhesus macaque monkey; monkeys from the Callitrichidae family; the Cebidae family; the Aotidae family; the Pitheciidae family; or the Atelidae family. A subject can be of any age, for example, a human subject can be an infant, a toddler, a child, a pre-adolescent, an adolescent, an adult, or an elderly individual.

[0056] Ranges can be expressed herein as from "about" one particular value, and/or to "about" another particular value. When such a range is expressed, another embodiment includes from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent "about," it will be understood that the particular value forms another embodiment. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. The term "about" as used herein refers to a range that is 15% plus or minus from a stated numerical value within the context of the particular usage. For example, about 10 would include a range from 8.5 to 11.5.

[0057] A significant challenge in the process of therapeutic discovery using binding partners of target proteins, for example, to identify potential therapeutic antibodies, is to determine, for example, if a therapeutic antibody has any off-target protein binding ability. Off-target interactions are often the source of toxicity or lowered efficacy that therapeutic antibodies exhibits in the clinic, resulting in costly failures in drug development. The identification of these off-target interactions at early stages of drug development can be a key step in developing successful new treatments, but the sheer size of the potential number of off-target interactions poses a significant challenge in the identification of these interactions. The human proteome, for example, is estimated to produce more than 90 thousand proteins, of which more than 70 thousand are estimated to be distinct splicing variants from a same gene sequence. When one considers the scope of many proteomes, especially eukaryotic proteomes, it appears to be virtually unmanageable to investigate all potential adverse binding events of a lead antibody. The clinical development of antibody candidates that are capable of significant off-target binding poses unique challenges: very often these off-target binding events are only identified in later stages of clinical trials, when one or more antibody lead(s) fail to produce a desired result (i.e., fails to show efficacy) or the antibody lead shows one or more adverse effects (i.e., fails to show safety). In some instances, the present disclosure aims to improve, for example, antibody discovery and clinical development by providing methods and platforms that accurately and effectively permit the characterization of binding specificity (and non-specificity) and affinity in a reproducible platform.

[0058] In some aspects, provided herein are methods of characterizing and/or selecting a binding partner using two peptide libraries: a first peptide library covering at least a subset of a proteome of an organism (referred to herein as a "diverse array" or diverse library or diverse peptide library), and a second peptide library comprising peptides covering at least one target protein (referred to herein as a "focused array"). By combining these two libraries, a binding partner may be characterized and/or selected. For example, in some embodiments, a binding partner may be characterized and/or selected based on information about binding across different proteins of an organism, and information about binding to variations of a specific target protein (for example, cross-species binding to a target protein, or identification of off-target binding). Use of the first diverse peptide library may, in some embodiments, identify binding partners that have poor specificity for the target protein, compared to other proteins in the proteome of the organism. Thus, binding partners that have high promiscuity (e.g., poor selectivity) can be avoided in favor of binding partners that have high specificity (e.g. the higher the degree to which a binding partner differentiates between different antigens, the better; in some

embodiments the antigens are immunogens). Use of the second focused peptide library, comprising peptides covering at least one target protein, may, in some embodiments, identify off-target interactions, low-affinity interactions, and/or cross-species reactivity. For example, including polypeptides with sequences derived from a target protein and sequences with a very high similarity to the target protein, potential off-target interactions may be identified in some embodiments, and binding partners with such potential off-target interactions can be avoided. Including variations of the target protein across species may, in some embodiments, help identify binding partners with cross-species reactivity, which may be a useful characteristic. In certain embodiments, binding partners that have high specificity for a binding target compared to other proteins in the proteome of the organism, and that have few or no off-target interactions, and that maintain binding to the target across species, may be more useful in certain applications, for example antibodies used as drugs. Using these two libraries (which may be, for example, peptide arrays), the characteristics of a binding partner (such as an antibody) can be evaluated on both the level of an organism and the level of the binding target protein of interest. The use of two peptide libraries assessing different aspects of binding may, in some embodiments, provide information that can be combined to produce a more comprehensive picture of the characteristics of a binding partner of interest, and may lead to better selection of binding partners from a library of binding partner candidates, such as a library of antibody candidates. Thus, in certain embodiments, combining the use of a diverse library covering at least a subset of a proteome of an organism, with a more focused library comprising peptides covering at least one target protein, provides for the identification of binding partners that may have greater success as drug candidates. In some embodiments, the diverse library covering at least a subset of a proteome of an organism also comprises one or more peptides associated with at least one target protein.

[0059] The present disclosure provides a powerful method of selecting a binding partner, for example, an antibody, that binds to a target protein while identifying binding domains of the binding partner, for example, an antibody. In some cases, the disclosure provides a first peptide library (such as a peptide array) comprising peptides covering at least a subset of a proteome of an organism, such as a human proteome. In some instances, a subset of a proteome comprises at least 10% of a proteome of an organism, at least 15% of a proteome of an organism, at least 20% of a proteome of an organism, at least 25% of a proteome of an organism, at least 30% of a proteome of an organism, at least 35% of a proteome of an organism, at least 40% of a proteome of an organism, at least 45% of a proteome of an organism, at least 50% of a proteome of an organism, at least 55% of a proteome of an organism, at least 60% of a proteome of an organism, at least 65% of a proteome of an organism, at least 70% of a proteome of an organism, at least 75%) of a proteome of an organism, at least 80% of a proteome of an organism, at least 85% of a proteome of an organism, at least 90% of a proteome of an organism, at least 95% of a proteome of an organism, at least 99% of a proteome of an organism, or at least 100% of a proteome of an organism. In some instances, specific desired and undesired target(s) would be represented by the peptide library (such as a peptide array) comprising the at least a subset of a proteome of an organism to steer, for example, antibody selection towards desired target(s) and away from undesired target(s).

[0060] A library of binding domains, such as a library of antibodies produced by one or more hybridomas, can be contacted with the first peptide library (for example, a peptide array). The binding domains that specifically bind to one or more peptides associated with a target protein can be selected. Antibodies capable of only binding to cognate epitopes of the target protein, and not highly similar peptides, can be inferred to have high specificity. Such screening can optionally be conducted at increasingly higher titrates (i.e., very low antibody concentrations). The disclosure also provides a second peptide library (such as a second peptide array) comprising peptides covering at least one target protein (e.g., Her3) or two or more related family members (e.g., Her3 and Her2). For example, antibody candidates can be contacted with the second peptide library (which may be, for example, an array). Characterization of these antibody-epitope interactions allows many off-target and/or low-affinity interactions to be identified at earlier stages of drug development. This allows for a more effective screening of dead-end monoclonal antibodies and it can significantly decrease the failure rate of "lead" candidates late in the development pipeline. The aforementioned methods can also be used to eliminate "dead-end" monoclonal antibodies, antibodies with significant off-target binding, from a library of binding domains.

[0061] Also recognized herein, is a method of selecting a binding partner, for example a monoclonal antibody, that binds to multiple epitopes in a target protein. In some instances, the disclosure provides a method of screening a binding partner, for example an antibody, against a peptide library that comprises polypeptides with sequences derived from a target protein, and sequences with a very high similarity to the target protein. By repeated panning and screening of the binding partner against such library platforms (including, for example, array platforms), the disclosure provides a method of identifying binding partners (for example, antibod(ies)) that bind with high specificity to a cognate sequence, but fail to bind sequences that are nearly identical.

[0062] In some instances, the disclosure provides methods of selecting a binding partner, for example a monoclonal antibody, that binds to at least two homologs of a target protein. In yet other instances, the disclosure provides a method of screening a binding partner, for example an antibody, against a peptide library to identify antibodies capable of binding to a target protein across different species (i.e., pan-species binding). In such instances, an antibody candidate can be screened against a peptide library comprising peptide sequences of a target protein from various species, such as human, cynomolgus monkey, rat, mouse, hamster, and others. Such peptide libraries could be used to screen for antibody clones at early stages of drug development and clones that exhibit binding to target peptides sequences across the various species can be selected for further development. Such a method can be used to apply positive pressure selection for antibodies to acquire pan-species reactivity.

[0063] In some instances, the disclosure provides methods to select for a binding partner, for example an antibody, with higher specificity towards a given target protein, for example, an active domain of a target protein, a functional domain of a target protein, or a target epitope of a target protein, by screening one or more antibodies against diverse and/or focused peptide libraries (such as arrays, i.e., arrays designed to display epitopes derived from a proteome or from a target protein). For example, the process of antibody optimization often involves humanization of an antibody sequence and other biophysical changes designed to improve properties of the lead antibody. These biophysical changes may change the binding properties of an antibody. The methods and library platforms (such as array platforms) of the disclosure allow for the monitoring of potential binding properties that may be acquired by an antibody during routine antibody optimization. FIG. 4, for example, is a general schematic representation illustrating for example, a use of a focused library platform to select a binding partner that binds to a target protein, or to eliminate off-target recognition while retaining pan-species reactivity.

[0064] In some embodiments, the binding partner selected from the methods or with the systems described herein has one or more characteristics selected from the group consisting of specificity for the target protein, little or no off-target binding, low promiscuity, and pan-species reactivity. In some embodiments, the target protein has at least two of these characteristics, or at least three of these characteristics, or all of these characteristics. In certain embodiments, the binding partner has specificity for the target protein. In some embodiments, the binding partner has little off-target binding, or no off-target binding. In some embodiments, the binding partner has low promiscuity. In some embodiments, the binding partner has pan-species reactivity. For example, in some embodiments, the binding partner has reactivity with the target protein in at least two species, at least three species, or at least four species. In some embodiments, the binding partner has reactivity with the target protein in humans, the target protein in cynomolgus monkeys, and the target protein in mice. In some embodiments, the binding partner has reactivity with the target protein in humans and the target protein in cynomolgus monkeys.

[0065] In other embodiments, provided herein are methods of "selection steering" of a library of binding domains, using a peptide library platform as described herein, such as a diverse peptide library platform (e.g., diverse peptide array) or a focused peptide library platform (e.g., focused peptide array). Using the libraries and methods provided herein, desired characteristics can be introduced into the selection process, which can result, in some embodiments, in identifying or producing groups of binding domains that are enriched in the desired characteristics. In some embodiments, a diverse peptide array and a focused peptide array are used in selection steering, for example at different points in the process. For example, in some embodiments, the library of binding domains is a phage library. FIG. 2 and FIG. 3 are schematic representations of the use of a focused library platform or a diverse library platform for selection steering with phage libraries. In FIG. 2, the focused or diverse peptide array library is used at the eluted clone step. For example, once clones have been eluted and isolated, individual clones can be separately evaluated with a library platform (e.g., diverse or focused) to identify a clone that has desired binding properties. In FIG. 3, the focused or diverse peptide library is used at the antigen binding step. This may include, in some embodiments, exposing the phage library to a peptide array, washing the bound library to remove unbound phage, eluting the bound phase, and amplifying the eluted phage to produce an enriched library comprising a higher proportion of phage that exhibit binding to the peptide array than in the initial phage library. This cycle can be repeated to produce an increasingly enriched phage library, in some embodiments. For both types of selection steering, presenting a peptide array containing the properties of interest can, in some embodiments, steer selection of the binding domain library (e.g., phage library) towards members that have the desired properties. For example, if cross-species reactivity is desired, binding domains could be evaluated, in some embodiments, using a focused library comprising peptide sequences of a target protein from various species. If a binding domain capable of binding a target protein that may have variability is desired (e.g., a cancer marker that may have sequence variability due to mutation), using a library comprising peptide sequences that cover the desired variabilities in the target protein could be used in some embodiments. In some embodiments, both a diverse and a focused peptide library is used in selection steering - for example, in some embodiments a diverse library is used in one or more cycles first, and then a focused library is used in one or more subsequent cycles.

Improving Specificity of a Therapeutic Antibody Towards a Target Protein

[0066] The methods and library platforms of the disclosure detect, characterize and improve specificity of an antibody towards a given target. In some cases, the disclosure provides methods of screening one or more antibody(ies) against a peptide array, such as the VI 5 or the VI 6 peptide arrays described herein. In such methods, clones that produce antibodies that identify only the cognate peptides of the target protein, i.e., clones that do not recognize peptides, that differ from the cognate sequence even by one residue, can be selected for further therapeutic development. In some of the methods described herein, such clones are screened at increasingly higher titrates {i.e., very low antibody concentrations). Clones that are not promiscuous, and that identify only the cognate peptide sequence in such screenings can be inferred to have high specificity.

[0067] The V16 array is a 3.3M feature array of 3.2M unique peptides. The V16 array comprises a library of peptides synthesized from 18 of the 20 naturally occurring amino acids by excluding cysteine (C) and methionine (M). Peptides range from 5 to 16 amino acids in length, having a median length of 8 amino acids. The array comprises a low-bias library of peptides, which is a high sequence-diversity library of unique peptides designed to cover sequence space evenly based on the 18 amino acids; and a library of peptides designed to map particular sequences including epitope sequences. The VI 5 array is described in Example 1 below. Eliminating Promiscuous Off-Therapeutic-Target Binding

[0068] The methods and array platforms of the disclosure detect, characterize, and potentially eliminate from the drug development pipeline antibodies that are promiscuous and bind off- target. In some cases, the disclosure provides methods of screening one or more antibody(ies) against a peptide array, such as the VI 5 or the VI 6 peptide arrays described herein. In such methods, clones that produce antibodies that identify sequences other than the cognate sequence of the target protein, but representing the cognate sequences of proteins other than the target protein, can be inferred to have off-target interactions. In such cases, the disclosure provides for methods of eliminating clones with off-target or promiscuous interactions from further therapeutic development. These methods provide lead antibody molecules that are highly specific and negatively selected for off-target recognition.

Monitoring Specificity and Promiscuity of a Therapeutic Antibody During Antibody Optimization Process

[0069] The methods and array platforms of the disclosure allow for the monitoring of specific, off-target, or promiscuous binding at the early stages of drug discovery. Thus, the methods described herein can be used to prevent expensive late-stage failures. If such screening of clones for off-target binding is carried out at the early stages when alternate clones could be selected, it eliminates the risk of realizing at a very late stage that a potential lead molecule could have off- target recognition, which can be a big set back to the program, as off-target interactions are often the source of toxicity and rapid clearance from the system and failure of the drug candidate in the clinic.

Positive Pressure Selection for Antibodies to Acquire Pan-Species Reactivity

[0070] In some cases, the disclosure provides peptide libraries comprising the cognate sequences of a target from a species such as human, cynomologous monkey, rat, mouse, hamster, or another species. The methods and array platforms of the disclosure, can be used to screen an antibody clone at the early stages of discovery. In these cases, only clones that exhibit binding to peptides representing the target across the various species may be selected for further development. Monitoring for Retention of High Target Specificity During Antibody Optimization

Process

[0071] The antibody optimization process often involves making physical changes to an antibody that improve one or more properties of a lead antibody. Examples of these properties include: developability (aggregation, solubility, viscosity, stability etc., such as to improve handling or storage), immunogenicity, antigen-binding affinity, effector functions, and pharmacokinetics. Immunogenicity typically involves minimizing non-human sequences in the lead antibody by creating chimeric, humanized, or human versions of the antibodies with as few T-lymphocyte epitopes as possible. Effector functions can be improved by genetically engineering, for example, the Fc region to contain point mutations or glycan modifications. Pharmacokinetic characteristics, such as plasma half-life can also be increased by developing antibodies with increased affinity for particular receptors. Antibody fragments treated with polyethylene gycol (PEGylation) have also been shown to have an increased plasma half-life. Lastly antigen-binding affinity can be improved by using the methods and arrays described herein to isolate antibodies with strong affinities for the antigen. Monitoring that all of these properties, including specificity, remains unchanged during the antibody optimization process is an important aspect of antibody development. The methods and arrays of the instant disclosure, such as the VI 5, VI 6, or another array described herein can be used to monitor the specificity of an antibody throughout the antibody optimization process.

Monitoring for the Acquisition of Off-Target Specificity During Antibody Optimization Process

[0072] In general, specific and off-target (also known as cross-reactive and polyreactive) interactions differ thermodynamically. Antibody specificity can be dominated by enthalpic contributions whereas antibody cross-reactivity can be mediated by configurational entropy." See, e.g., Mohan S, et al. Association energetics of cross-reactive and specific antibodies.

Biochemistry. 2009;48: 1390-8; incorporated herein by reference in its entirety. Off-target binding behavior can result from multiple mechanisms. For instance, hydrophobic interactions, derived either from the paratope itself or the adoption of a non-native conformation, can be reported to contribute to non-specific binding. In general, antibodies that recognize many different antigens (polyreactivity) have a lower affinity for each of the antigens than antibodies that recognize only one (monoreactive) or a limited number of antigens. It is assumed that flexibility in the antigen binding pocket contributes to polyreactivity. The methods and libraries of the instant disclosure, such as the V15, V16, or another array described herein can be used to monitor the acquisition of off-target or promiscuous specificity of an antibody throughout the antibody optimization process.

Optimizing for Target Specificity by creating Antibody Libraries

[0073] Currently, very few methods and technologies exist that allow one to improve the ability of a lead antibody to recognize only the peptides that represent the cognate sequences of target and not those that are even very similar to the cognate sequence. The instant disclosure provides a combinatorial library for a lead antibody comprising target cognate sequences and sequences very similar to target cognate sequences. By repeated panning and screening against such library(ies) one could select antibody(ies) that have been optimized for specificity, and screening against peptide libraries (such as V15/V16/etc).

Continuously Monitoring the Specificity Profile of a Lead Antibody as it Undergoes Process Optimization, Development and Manufacturing steps.

[0074] During process optimization, development, and manufacturing efforts devoted to scaling- up production of a lead antibody, one has to ensure that a 'binding signature' of a monoclonal does not change. Typically, several physico-chemical properties of the antibody (molecular weight, peptide map, SDS page, cIEF, glycan profiles etc.) are monitored during this process using several analytical and biophysical techniques. One can similarly, monitor if an antibody's ability to recognize the target, or off-target interactions, is intact and unchanged through the entire process. By monitoring this binding signature the binding of an antibody to a focused and diverse array, could be continuously determined throughout development.

Binding to Peptide Arrays

[0075] The methods of the disclosure can use data obtained from the binding domains that specifically bind to one or more peptides to characterize a binding interaction. A dynamic range of binding of a binding partner, for examples, a monoclonal antibody, a polyclonal antibody, an antibody fragment, a Fab fragment, a single-chain variable fragment (scFv), a single domain antibody, (sdAb), chimeric antibodies, humanized antibodies, antibody drug conjugates, and the like can be detected on a focused or a targeted peptide library. The specificity of binding to an library can be determined based on an apparent binding affinity.

[0076] In some cases, the methods disclosed herein comprise contacting a library of binding domains to a first peptide or a second peptide array. The library of binding domains can comprise a B cell library, a phage library, or combination thereof. The library of binding domains may be encoded by polypeptides. A B cell library can comprise a library of binding domains from an immunized subject or from a naive subject.

[0077] Binding interactions between components of a sample and a peptide array can be detected in a variety of formats. In some formats, components of the samples are labeled. The label can be a radioisotype or dye among others. The label can be supplied either by administering the label to a patient before obtaining a sample or by linking the label to the sample or selective component(s) thereof. Binding interactions can also be detected using a secondary detection reagent, such as an antibody. For example, binding of antibodies in a sample to an array can be detected using a secondary antibody specific for the isotype of an antibody (e.g., IgG (including any of the subtypes, such as IgGl, IgG2, IgG3 and IgG4), IgA, IgM). The secondary antibody is usually labeled and can bind to all antibodies in the sample being analyzed of a particular isotype. Different secondary antibodies (for example, from different hosts) can be used having different isotype specificities. Binding interactions can also be detected using label-free methods, such as surface plasmon resonance (SPR) and mass spectrometry. SPR can provide a measure of dissociation constants, and dissociation rates, for example, using the A- 100 Biocore/GE instrument for this type of analysis. An isolated binding domain described herein can bind specifically to one peptide from the target protein or it can bind specifically to multiple peptides from the target protein.

[0078] A binding event can be quantitatively described as the ratio between the largest and smallest value of a detected signal of binding. A signal of binding can be, for example, a fluorescent signal detected with a secondary antibody. The methods and arrays of the invention can detected a broad dynamic range of antibody binding to the peptides in the array of the invention. In some embodiments, a broad dynamic range of antibody binding can be detected on a logarithmic scale. In some embodiments, the methods and arrays of the invention allow the detection of a pattern of binding of a plurality of antibodies to an array using up to 2 logs of dynamic range, up to 3 logs of dynamic range, up to 4 logs of dynamic range or up to 5 logs of dynamic range.

[0079] In some embodiments, at least 1 μg of total antibody, purified or 1 μg/mL concentration in unpurified matrix is used in the assays and methods disclosed herein.

[0080] Detection of binding events can also occur in the presence of competitor peptides. In some embodiments, the competitive inhibitor is a peptide identical to, similar to or derived from a determined epitope, motif or input sequence as disclosed herein. In some embodiments, the competitive inhibitor peptides comprises a mixture of at least 2, at least 3, at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45 or at least 50 different peptides. In some embodiments, the competitor peptides comprise natural and/or non- natural amino acids. In some embodiments, the competitive inhibitor peptide is at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%), at least 96%, at least 97%, at least 98% or is at least 99% identical to a determined epitope, motif or input sequence. In other embodiments, the competitive inhibitor peptide comprises at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98% and/or at least 99% similarity to a determined epitope, motif or input sequence. In some embodiments, the similarity can be determined by sequence or by structure. In other embodiments, the competitive inhibitor peptide may comprise a mixture of random or semi-random peptides. In yet other embodiments, the competitive peptide mixture can include a biological source, for example, serum, plasma or blood, added to or in place of the competitive inhibitor peptides disclosed herein. By adding competitive inhibitor peptides to the binding reaction, and measuring a change in binding signal in the absence and presence of the competitive inhibitor peptides, a measurement of specificity may be obtained that conveys information regarding the stringency of the interaction between peptides on the array and the biological sample. Specificity can be measured in terms of the affinity (Kd) measured in the presence of competitor and/or the number of identified peptides with a determined motif or sequence that bind to the biological sample or antibody and identified as a putative binding site.

[0081] In some instances, the methods disclosed herein require one round of selection comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a proteome of an organism; (b) selecting and isolating the binding domains that specifically bind to one or more peptides from the target protein; (c) contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein; and (d) selecting and isolating the binding domains that bind to one or more peptides of interest. In other cases, the methods disclosed herein further comprise subjecting the isolated binding domains to at least one, to at least two, to at least, three, to at least four, or to at least five additional round of selection.

[0082] A library of binding domains may be encoded by one or more polynucleotides. In some instances the polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection.

[0083] Methods and systems described herein may be used with other methods and/or systems. For example, in some embodiments, the binding domains used in the methods provided herein are produced using one or more immunogens, which may, for example, be selected through one or more methods. This application cross-references the following patent application: Attorney Docket No. 43638-729.101, filed on October 9, 2017, with U.S. Provisional Application No. 62/569,945; U.S. Provisional Application No. 62/587,368, filed November 16, 2017; and the international application entitled "IMMUNOGENS FOR DIRECTED IMMUNE RESPONSE AND ANTIBODIES THEREFROM", which has Attorney Docket No. RBYC-018/02WO 334002/2069, filed concurrently herewith, the disclosures of which are incorporated herein by reference in their entireties. Array Platforms

[0084] The present disclosure relates to methods of characterizing the binding of a binding partner, for example an antibody, to one or more peptide arrays. Such peptide arrays can comprise polypeptide sequences derived from specific proteomes, select target proteins, or both. The array platforms comprise a plurality of individual features on the surface of the array. Each feature typically comprises a plurality of individual molecules synthesized in situ on the surface of the array, wherein the molecules are identical within a feature, but the sequence or identity of the molecules differ between features. The array molecules include, but are not limited to nucleic acids (including DNA, RNA, nucleosides, nucleotides, structure analogs or combinations thereof), peptides, peptide-mimetics, and combinations thereof and the like, wherein the array molecules may comprise natural or non-natural monomers within the molecules. Such array molecules include the synthesis of large synthetic peptide arrays. In some embodiments, a molecule in an array is a mimotope, a molecule that mimics the structure of an epitope and is able to bind an epitope-elicited antibody. In some embodiments, a molecule in the array is a paratope or a paratope mimetic, comprising a site in the variable region of an antibody (or T cell receptor) that binds to an epitope of an antigen. In some embodiments, an array of the invention is a peptide array comprising random, semi-random or diverse peptide sequences. In some embodiments, the diverse peptide sequences may be derived from a target library. Target libraries can be a proteome library, for example, from a human (see, e.g., protein libraries from the human genome project), a mammal, or another suitable creature. Target libraries can be a proteome library, for example, from a specific organism, (see, e.g., Mycobacterium tuberculosis (Mtb) proteome library (Schubert et al., Cell Host Microbe (2013) 13(5):602-12), or organelle {see, e.g., Mitochondrial (Mtd) proteome library (Calvo and Mootha, Annu. Rev. Genomics (2010) 11 :25-44), or the like.

[0085] In yet other embodiments, the diverse peptide sequences may be derived from a set of all known combinations of amino acids, for example at least 100% of all possible tetramers, at least 90%) of all possible tetramers, at least 85% of all possible tetramers, at least 80% of all possible tetramers, at least 75% of all possible tetramers, at least 70% of all possible tetramers, at least 65%o of all possible tetramers, at least 60% of all possible tetramers, at least 55% of all possible tetramers, at least 50% of all possible tetramers, at least 45% of all possible tetramers, at least 40% of all possible tetramers, at least 35% of all possible tetramers, at least 30% of all possible tetramers, or at least 25% of all possible tetramers. In still other embodiments, the diverse peptide sequences may be derived from a set of all possible pentamers, for example, at least 100%) of all possible pentamers, at least 95% of all possible pentamers, at least 90% of all possible pentamers, at least 85% of all possible pentamers, at least 80% of all possible pentamers, at least 75% of all possible pentamers, at least 70% of all possible pentamers, at least 65%o of all possible pentamers, at least 60% of all possible pentamers, at least 55% of all possible pentamers, at least 50% of all possible pentamers, at least 45% of all possible pentamers, at least 40%) of all possible pentamers, at least 35% of all possible pentamers, at least 30% of all possible pentamers or at least 25% of all possible pentamers. In yet other embodiments, the diverse peptide sequences of an array may be derived from a set of amino acid combinations, for example from 25%- 100% of all possible hexamers, from 25%- 100% of all possible septamers, from 25%)- 100%) of all possible octamers, from 25%- 100% of all possible nonamers or from 25%)- 100%) of all possible decamers, or combinations thereof. Representation of the diverse peptide sequences is only limited by the size of the array. Accordingly, large arrays, for example, at least 1 million, at least 2 million, at least 3 million, at least 4 million, at least 5 million, at least 6 million, at least 7 million, at least 8 million, at least 9 million, at least 10 million or more peptides can be used with the methods, systems and assays disclosed herein. Alternatively or additionally, multiple substantially non-overlapping peptide libraries/arrays may be synthesized to cover the sequence space needed for resolution of the peptide sequences or motif(s) recognized by the biological sample or binding partner, for example, an antibody.

[0086] In other embodiments, the individual sequences can share a % homology to an amino acid sequence of a polypeptide from a related species. A polypeptide sequence can share at most 10%) homology, at most 20% homology, at most 30% homology, at most 40% homology, at most 50%) homology, at most 60% homology, at most 70% homology, at most 80% homology, at most 90%) homology, or at most 99% homology with an amino acid sequence of a related peptide. Various methods and software programs can be used to determine the homology between two or more peptides, such as NCBI BLAST, Clustal W, MAFFT, Clustal Omega, AlignMe, Praline, or another suitable method or algorithm. [0087] The peptides of the libraries provided herein, such as the diverse peptide library and the focused peptide library, may be any suitable length. In some embodiments, the individual peptides on the array are of variable and/or different lengths. In some embodiments, the peptides are between about 6-20 amino acids in length, or between about 7-18 amino acids in length, or between about 8-15 amino acids in length, or between about 9-14 amino acids in length. In other embodiments, the peptides are at least 6 amino acids, at least 7 amino acids, at least 8 amino acids, at least 9 amino acids, at least 10 amino acids, at least 11 amino acids, at least 12 amino acids, at least 13 amino acids, at least 14 amino acids, at least 15 amino acids in length. In still other embodiments, the peptides are not more than 15 amino acids, not more than 14 amino acids, not more than 13 amino acids, not more than 12 amino acids, not more than 11 amino acids, not more than 10 amino acids, not more than 9 amino acids or not more than 8 amino acids in length. In still other embodiments, the peptides on the array have an average length of about 6 amino acids, about 7 amino acids, about 8 amino acids, about 9 amino acids, about 10 amino acids, about 11 amino acids, about 12 amino acids, about 13 amino acids, about 14 amino acids, or about 15 amino acids.

[0088] The peptides of the libraries provided herein, such as the diverse peptide library and the focused peptide library, may comprise any suitable amino acids. In yet other embodiments, the amino acid building blocks for the peptides on the array comprises all natural amino acids. In other embodiments, the amino acid building blocks for the peptides on the array are comprised of non-natural or synthetic amino acids. In yet other embodiments, only 19 amino acids are used as the building blocks for synthesizing the peptides on the array. In still other embodiments, only 18 amino acids, only 17 amino acids, only 16 amino acids, only 15 amino acids or only 14 amino acids are used as the building blocks for synthesizing the peptides on the array. In some embodiments, cysteine is omitted during peptide synthesis. In other embodiments, methionine is omitted during peptide synthesis. In still other embodiments, isoleucine is omitted during peptide synthesis. In yet other embodiments, threonine is omitted during peptide synthesis. In still other embodiments, cysteine, methionine, isoleucine and/or threonine, including all combinations thereof, are omitted during peptide synthesis.

[0089] In some embodiments, the diverse peptide libraries provided herein sample the highly diverse sequence space represented in a combinatorial peptide library, and provide individual peptides, including significant peptides, comprising enriched in motifs that predict biding epitopes. The enriched motifs may serve, for example, as basis for identifying input sequences that are used to design focused libraries. Examples of diverse libraries include the VI 3 library, a highly diverse combinatorial library of 126,009 peptides comprising peptides with a median length of 9 residues, ranging from 5 to 13 amino acids, and designed to include 99.9% of all possible 4-mers and 48.3% of all possible 5-mers of 16 amino acids (methionine, M; cysteine, C; isoleucine, I; and threonine, T were excluded); and also include the VI 5 library, a highly diverse combinatorial library comprising peptides designed to include 100% of all possible 4-mers to 6- mers.

[0090] In certain embodiments, the focused libraries provided herein vary a number of positions around the input sequence comprising enriched motifs of individual peptides, including significant peptides, identified in a diverse library. An example of a focused library includes the V14 library, which comprises 16,920 peptides with a median length of 0 to 17 amino acid residues. The peptides of the V14 focused library were designed each to provide variant sequences of one input sequence of an individual peptide, in this case a significant peptide, of a diverse library.

[0091] In some embodiments, an array of the invention is a peptide array comprising a focused or limited set of peptide sequences, all derived from an input amino acid or peptide sequence, or an input amino acid or peptide motif. One or more peptide arrays may be used with the methods, systems and assays disclosed herein, including a diverse or semi-random peptide array and/or a focused or limited set of peptide sequences. For example, the methods and arrays disclosed herein may utilize both a diverse set of peptides and a focused or limited set of peptides are chosen. One or more peptide arrays may be used either in parallel or sequentially with a method disclosed herein. For example, a first peptide array (such as a diverse peptide array) may be used initially, and a second peptide array (such as a targeted peptide array) may be used thereafter. Using the methods, systems and arrays described herein, multiple focused or limited set of peptide arrays may be used to characterize binding partner binding, such as antibody binding.

[0092] As described herein, in some embodiments the focused peptide library (such as a focused peptide array), comprises peptides that cover a target protein. For example, in some embodiments, the focused peptide library comprises at least 100% of all possible tetramers, at least 90%) of all possible tetramers, at least 85% of all possible tetramers, at least 80% of all possible tetramers, at least 75% of all possible tetramers, at least 70% of all possible tetramers, at least 65%) of all possible tetramers, at least 60% of all possible tetramers, at least 55% of all possible tetramers, at least 50% of all possible tetramers, at least 45% of all possible tetramers, at least 40%) of all possible tetramers, at least 35% of all possible tetramers, at least 30% of all possible tetramers, or at least 25% of all possible tetramers that cover the target protein. In still other embodiments, the focused peptide sequences may be derived from a set of all possible pentamers, for example, at least 100% of all possible pentamers, at least 95% of all possible pentamers, at least 90% of all possible pentamers, at least 85% of all possible pentamers, at least 80%) of all possible pentamers, at least 75% of all possible pentamers, at least 70% of all possible pentamers, at least 65% of all possible pentamers, at least 60% of all possible pentamers, at least 55%) of all possible pentamers, at least 50% of all possible pentamers, at least 45% of all possible pentamers, at least 40% of all possible pentamers, at least 35% of all possible pentamers, at least 30%) of all possible pentamers or at least 25% of all possible pentamers that cover the target protein. In yet other embodiments, the focused peptide sequences of an array may be derived from a set of amino acid combinations, for example from 25%- 100% of all possible hexamers, from 25%)- 100%) of all possible septamers, from 25%- 100% of all possible octamers, from 25%- 100%) of all possible nonamers or from 25%- 100% of all possible decamers, or combinations thereof that cover the target protein. In some embodiments, multiple substantially non- overlapping peptide libraries/arrays may be synthesized to cover the sequence space needed for resolution of the peptide sequences or motif(s) recognized by the biological sample or binding partner, for example, an antibody.

[0093] In other embodiments, the individual sequences of the focused peptide library can share a % homology to an amino acid sequence of a polypeptide from a related species. A polypeptide sequence can share at most 10% homology, at most 20% homology, at most 30% homology, at most 40%) homology, at most 50% homology, at most 60% homology, at most 70% homology, at most 80%) homology, at most 90% homology, or at most 99% homology with an amino acid sequence of a related peptide. Various methods and software programs can be used to determine the homology between two or more peptides, such as NCBI BLAST, Clustal W, MAFFT, Clustal Omega, AlignMe, Praline, or another suitable method or algorithm. Thus, for example, in some embodiments the focused peptide library (such as a focused peptide array) comprises peptides that cover the target protein of a particular species and that cover the corresponding target protein in one or more additional species. Such focused peptide libraries may be useful, for example, in evaluating cross-species binding of a binding domain.

[0094] Nearly all therapeutic binding partner screens, such as antibody screens, incorporate some level of epitope mapping and epitope binning on a select number of leads and these data drive decisions on which leads move forward into the development pipeline. Epitope mapping studies commonly utilize systematic overlapping sequences of peptides to determine the amino acids responsible for the antibody -target interaction. Epitope binning studies map the epitopes of several lead antibodies and then bin the antibodies by their binding affinity /kinetics towards identified epitopes. Epitope binning studies are a key decision dataset to identify lead antibodies with different epitope reactivity and potentially different modes-of-action and off-target effects. Typically epitope binning and mapping characterizations are done using synthesized libraries of targeted peptide sequences related to known epitope(s), which limits analyses to a few thousand targeted interactions (e.g. 10 lead antibodies vs. 100 peptides) due to limited analysis throughput and the high cost of purified synthetic peptide libraries. Characterization of such a small number of antibody-target interactions allows many off-target and/or low-affinity interactions to go undetected which increases failure rates of candidates late in the development pipeline.

[0095] A limitation of current epitope mapping/binning platforms is limited antibody-epitope interaction analysis throughput relative to the total number of possible interactions. This analytical throughput limitation forces antibody discovery scientists to reduce the number of leads selected for further development. As a result, the reduced number of leads increases the risk of late-stage antibody therapeutic candidate failure. This ultimately increases the cost of those candidates that do succeed and in turn subsidize the R&D costs of failed candidates. Risks associated with limited analytical throughput are increasing with the advent of multi-specific antibody screens that require selection of more numerous lead antibodies to identify candidates with particular multi-specificity relevant to the target disease and minimal off-target effects.

[0096] The methods and arrays described herein may, in some embodiments, be used to bin binding domains (such as antibodies) based on criteria other than interactions with known epitopes that is typically used. For example, in some embodiments, binding domains are binned using two or more desired properties as described herein - for example, pan-species reactivity and binding specificity. In certain embodiments, the peptide arrays and methods as described herein can be used to bin binding domains with greater resolution (e.g., greater functional similarity between binding domains in the same bin) than standard methods based on interactions with known epitopes. For example, binning antibodies based on the standard methods described above may result in a group of antibodies that have similar binding affinity /kinetics toward one identified epitope, but otherwise differ in their off-target and/or low-affinity interactions. In contrast, in some embodiments, binning binding domains using peptide arrays described herein (e.g., diverse and focused arrays) leads to groups of binding domains that have more functional characteristics in common, or that have greater similarity in one or more functional

characteristics (e.g., pan-species reactivity, specificity, etc.).

[0097] The technologies disclosed herein include a photolithographic array synthesis platform that merges semiconductor manufacturing processes and combinatorial chemical synthesis to produce array -based libraries on silicon wafers. Further, by sequentially applying another mask with UV light exposure, various array features can be established. By utilizing the tremendous advancements in photolithographic feature patterning, the array synthesis platform is highly- scalable and capable of producing combinatorial chemical libraries with 40 million features on an 8-inch wafer. Photolithographic array synthesis is performed using semiconductor wafer production equipment in a class 10,000 cleanroom to achieve high reproducibility. When the wafer is diced into standard microscope slide dimensions, each slide contains more than 3 million distinct chemical entities. Exemplary embodiments of focused and targeted arrays are described in detail in PCT/US2017/025546, entitled "Array-Based Peptide Libraries for

Therapeutic Antibody Characterization", which is incorporated by reference herein for such disclosure.

[0098] In some embodiments, arrays with chemical libraries produced by the technologies disclosed herein are used for immune-based diagnostic assays, for example called

immunosignature assays. Using a patient's antibody repertoire from a drop of blood bound to the arrays, a fluorescence binding profile image of the bound array provides sufficient information to classify disease vs. healthy. [0099] In some embodiments, immunosignature assays are being developed for clinical application to diagnose/monitor autoimmune diseases and to assess response to autoimmune treatments. Exemplary embodiments of immunosignature assays is described in detail in US Pre- Grant Publication No. 2012/0190574, entitled "Compound Arrays for Sample Profiling" and US Pre-Grant Publication No. 2014/0087963, entitled "Immunosignaturing: A Path to Early

Diagnosis and Health Monitoring", both of which are incorporated by reference herein for such disclosure. The arrays developed herein incorporate analytical measurement capability within each synthesized array using orthogonal analytical methods including ellipsometry, mass spectrometry and fluorescence. These measurements enable longitudinal qualitative and quantitative assessment of array synthesis performance.

[0100] In some embodiments, the peptide arrays are high density peptide arrays. In some embodiments, the arrays comprise individual peptides within a feature on the array spaced less than 0.5 nm, less than 1 nm, less than 2 nm, less than 3 nm, less than 4 nm, less than 5 nm, less than 6 nm, less than 7 nm, less than 8 nm, less than 9 nm, less than 10 nm apart, less than 11 nm apart, less than 12 nm apart, less than 13 nm apart, less than 14 nm part or less than 15 nm apart.

[0101] Focused and diverse peptide arrays can comprise a number of different peptides. In some instances, the size of the peptide array is dependent on the desired coverage of a proteome or of a target protein. In some cases, the methods of the invention can effectively provide for: the selection of a monoclonal antibody with specific binding; the elimination of dead-end monoclonal antibodies from a library of binding domains; the selection of a monoclonal antibody that binds to multiple epitopes in a target protein; the selection of a monoclonal antibody that binds to at least two homologs of a target protein; the selection of a monoclonal antibody that binds to an active domain, a functional domain, or to a target epitope of a target protein; or the selection of a multi-specific monoclonal antibody by screening the antibody against a peptide array that comprises no more than 2,000 peptides; no more than 5,000 peptides; no more than 10,000 peptides; no more than 20,000 peptides; no more than 30,000 peptides; no more than 40,000 peptides; no more than 50,000 peptides; no more than 60,000 peptides; no more than 70,000 peptides; no more than 80,000 peptides; no more than 90,000 peptides; no more than 100,000 peptides; no more than 200,000 peptides; no more than 300,000 peptides; no more than 400,000 peptides; no more than 500,000 peptides; no more than 600,000 peptides; no more than 700,000 peptides; no more than 800,000 peptides; no more than 900,000 peptides; no more than 1,000,000 peptides; no more than 2,000,000 peptides; no more than 3,000,000 peptides; no more than 4,000,000 peptides; or no more than 5,000,000 peptides.

[0102] In some embodiments, a peptide array comprises at least 2,000 peptides; at least 3,000 peptides; at least 4,000 peptides; at least 5,000 peptides; at least 6,000 peptides; at least 7,000 peptides; at least 8,000 peptides; at least 9,000 peptides; at least 10,000 peptides; at least 11,000 peptides; at least 12,000 peptides; at least 13,000 peptides; at least 14,000 peptides; at least 15,000 peptides; at least 16,000 peptides; at least 17,000 peptides; at least 18,000 peptides; at least 19,000 peptides; at least 20,000 peptides; at least 21,000 peptides; at least 22,000 peptides; at least 23,000 peptides; at least 24,000 peptides; at least 25,000 peptides; at least 30,000 peptides; at least 40,000 peptides; at least 50,000 peptides; at least 60,000 peptides; at least 70,000 peptides; at least 80,000 peptides; at least 90,000 peptides; at least 100,000 peptides; at least 110,000 peptides; at least 120,000 peptides; at least 130,000 peptides; at least 140,000 peptides; at least 150,000 peptides; at least 160,000 peptides; at least about 170,000 at least 180,000 peptides; at least 190,000 peptides; at least 200,000 peptides; at least 210,000 peptides; at least 220,000 peptides; at least 230,000 peptides; at least 240,000 peptides; at least 250,000 peptides; at least 260,000 peptides; at least 270,000 peptides; at least 280,000 peptides; at least 290,000 peptides; at least 300,000 peptides; at least 310,000 peptides; at least 320,000 peptides; at least 330,000 peptides; at least 340,000 peptides; at least 350,000 peptides.

[0103] A peptide can be physically tethered to a peptide array by a linker molecule. The N- or the C-terminus of the peptide can be attached to a linker molecule. A linker molecule can be, for example, a functional plurality or molecule present on the surface of an array, such as an imide functional group, an amine functional group, a hydroxyl functional group, a carboxyl functional group, an aldehyde functional group, and/or a sulfhydryl functional group. A linker molecule can be, for example, a polymer. In some embodiments the linker is maleimide. In some embodiments the linker is a glycine-serine-cysteine (GSC) or glycine-glycine-cysteine (GGC) linker. In some embodiments, the linker consists of a polypeptide of various lengths or compositions. In some cases the linker is polyethylene glycol of different lengths. In yet other cases, the linker is hydroxymethyl benzoic acid, 4-hydroxy-2-methoxy benzaldehyde, 4- sulfamoyl benzoic acid, or other suitable for attaching a peptide to the solid substrate. [0104] A surface of a peptide array can comprise a plurality of different materials. A surface of a peptide array can be, for example, glass. Non-limiting examples of materials that can comprise a surface of a peptide array include glass, functionalized glass, silicon, germanium, gallium arsenide, gallium phosphide, silicon dioxide, sodium oxide, silicon nitride, nitrocellulose, nylon, polytetraflouroethylene, polyvinylidendiflouride, polystyrene, polycarbonate, methacrylates, or combinations thereof. A surface of a peptide array can also comprise semi-conductor wafers, for example, silicon wafers, derivatized with, for example, aminosilane molecules, which allows spotting or in situ synthesis on the surface of the array.

[0105] A surface of a peptide array can be flat, concave, or convex. A surface of a peptide array can be homogeneous and a surface of an array can be heterogeneous. In some embodiments, the surface of a peptide array is flat. In some embodiments, the surface of a peptide array is round, such as the surface of a bead. A surface of a peptide array can be coated with a coating. A coating can, for example, improve the adhesion capacity of an array of the invention. A coating can, for example, reduce background adhesion of a biological sample to an array of the invention. In some embodiments, a peptide array of the invention comprises a glass slide or silicon wafer with an aminosilane-coating.

Functional Assays

[0106] Understanding the comprehensive off-target effects of an immunotherapy and

investigating the effects of the immunotherapy in a live being can require extensive evaluation of pharmacokinetic and ADMET (absorption, distribution, metabolism, discretion, and toxicity) parameters. Thus, the comprehensive characterization of efficacious monoclonal antibodies on a disclosed peptide library can also lead to their selection as a lead therapeutic target at early discovery.

[0107] In some cases, the disclosed methods further comprise conducting a functional assay in conjunction with the methods and devices disclosed herein. Further functional assays can establish or reject known-or-perceived relationships among components of the peptide array and monoclonal antibodies. The effectiveness of a plurality of monoclonal antibodies, at a plurality of concentrations, for inhibiting biological or biochemical pathways can be evaluated further in functional assays. Functional assays can be used, for example, to simulate the half maximal inhibitory concentration (IC₅₀) of a monoclonal antibody.

Sequencing of the Isolated Binding Domains

[0108] In some instances, the isolated binding domains are sequenced. Sequencing can include sequencing-by-synthesis (SBS) methods utilizing reversible terminator chemistry. Sequencing can also involve the use of Single Molecule Sequencing by Synthesis (SMSS) method and nanopore sequencing. In some instances, sequencing methods, such as Sanger sequencing, next- generation sequencing methods, ab-initio sequencing by LC-MS or Edman degradation sequencing can be employed with the assays and methods disclosed herein.

Digital processing device

[0109] In some embodiments methods described herein are used in conjunction with computer systems, platforms, software, and networks, that facilitate the detection of the binding domains to one or more peptides of a peptide array by the at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance. The aforementioned computer systems, platforms, software, and networks, may include a digital processing device, or use of the same. In further embodiments, the digital processing device includes one or more hardware central processing units (CPUs), i.e., processors that carry out the device's functions. In still further embodiments, the digital processing device further comprises an operating system configured to perform executable instructions. In some embodiments, the digital processing device is optionally connected a computer network. In further embodiments, the digital processing device is optionally connected to the Internet such that it accesses the World Wide Web. In still further embodiments, the digital processing device is optionally connected to a cloud computing infrastructure. In other embodiments, the digital processing device is optionally connected to an intranet. In other embodiments, the digital processing device is optionally connected to a data storage device.

[0110] In accordance with the description herein, suitable digital processing devices include, by way of non-limiting examples, server computers, desktop computers, laptop computers, notebook computers, sub-notebook computers, netbook computers, netpad computers, set-top computers, handheld computers, Internet appliances, mobile smartphones, tablet computers, personal digital assistants, video game consoles, and vehicles. Those of skill in the art will recognize that many smartphones are suitable for use in the system described herein. Those of skill in the art will also recognize that select televisions, video players, and digital music players with optional computer network connectivity are suitable for use in the system described herein. Suitable tablet computers include those with booklet, slate, and convertible configurations, known to those of skill in the art.

[0111] In some embodiments, a digital processing device includes an operating system configured to perform executable instructions. The operating system is, for example, software, including programs and data, which manages the device's hardware and provides services for execution of applications. Those of skill in the art will recognize that suitable server operating systems include, by way of non-limiting examples, FreeBSD, OpenBSD, NetBSD^®, Linux, Apple^® Mac OS X Server^®, Oracle^® Solaris^®, Windows Server^®, and Novell^® NetWare^®. Those of skill in the art will recognize that suitable personal computer operating systems include, by way of non-limiting examples, Microsoft^® Windows^®, Apple^® Mac OS X^®, UNIX^®, and UNIX- like operating systems such as GNU/Linux^®. In some embodiments, the operating system is provided by cloud computing. Those of skill in the art will also recognize that suitable mobile smart phone operating systems include, by way of non-limiting examples, Nokia^® Symbian^® OS, Apple^® iOS^®, Research In Motion^® BlackBerry OS^®, Google^® Android^®, Microsoft^® Windows Phone^® OS, Microsoft^® Windows Mobile^® OS, Linux^®, and Palm^® WebOS^®.

[0112] In some embodiments, a digital processing device includes a storage and/or memory device. The storage and/or memory device is one or more physical apparatuses used to store data or programs on a temporary or permanent basis. In some embodiments, the device is volatile memory and requires power to maintain stored information. In some embodiments, the device is non-volatile memory and retains stored information when the digital processing device is not powered. In further embodiments, the non-volatile memory comprises flash memory. In some embodiments, the non-volatile memory comprises dynamic random-access memory (DRAM). In some embodiments, the non-volatile memory comprises ferroelectric random access memory (FRAM). In some embodiments, the non-volatile memory comprises phase-change random access memory (PRAM). In other embodiments, the device is a storage device including, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, magnetic disk drives, magnetic tapes drives, optical disk drives, and cloud computing based storage. In further embodiments, the storage and/or memory device is a combination of devices such as those disclosed herein.

[0113] In some embodiments, a digital processing device includes a display to send visual information to a user. In some embodiments, the display is a cathode ray tube (CRT). In some embodiments, the display is a liquid crystal display (LCD). In further embodiments, the display is a thin film transistor liquid crystal display (TFT-LCD). In some embodiments, the display is an organic light emitting diode (OLED) display. In various further embodiments, on OLED display is a passive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED) display. In some embodiments, the display is a plasma display. In other embodiments, the display is a video projector. In still further embodiments, the display is a combination of devices such as those disclosed herein.

[0114] In some embodiments, a digital processing device includes an input device to receive information from a user. In some embodiments, the input device is a keyboard. In some embodiments, the input device is a pointing device including, by way of non-limiting examples, a mouse, trackball, track pad, joystick, game controller, or stylus. In some embodiments, the input device is a touch screen or a multi-touch screen. In other embodiments, the input device is a microphone to capture voice or other sound input. In other embodiments, the input device is a video camera to capture motion or visual input. In still further embodiments, the input device is a combination of devices such as those disclosed herein.

[0115] In some embodiments, a digital processing device includes a digital camera. In some embodiments, a digital camera captures digital images. In some embodiments, the digital camera is an autofocus camera. In some embodiments, a digital camera is a charge-coupled device (CCD) camera. In further embodiments, a digital camera is a CCD video camera. In other embodiments, a digital camera is a complementary metal-oxide-semiconductor (CMOS) camera. In some embodiments, a digital camera captures still images. In other embodiments, a digital camera captures video images. In various embodiments, suitable digital cameras include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, and higher megapixel cameras, including increments therein. In some embodiments, a digital camera is a standard definition camera. In other embodiments, a digital camera is an HD video camera. In further embodiments, an HD video camera captures images with at least about 1280 x about 720 pixels or at least about 1920 x about 1080 pixels. In some embodiments, a digital camera captures color digital images. In other embodiments, a digital camera captures grayscale digital images. In various embodiments, digital images are stored in any suitable digital image format. Suitable digital image formats include, by way of non-limiting examples, Joint

Photographic Experts Group (JPEG), JPEG 2000, Exchangeable image file format (Exif), Tagged Image File Format (TIFF), RAW, Portable Network Graphics (PNG), Graphics

Interchange Format (GIF), Windows^® bitmap (BMP), portable pixmap (PPM), portable graymap (PGM), portable bitmap file format (PBM), and WebP. In various embodiments, digital images are stored in any suitable digital video format. Suitable digital video formats include, by way of non-limiting examples, AVI, MPEG, Apple^® QuickTime^®, MP4, AVCHD^®, Windows Media^®, DivX™, Flash Video, Ogg Theora, WebM, and RealMedia.

Non-transitory computer readable storage medium

[0116] In some embodiments, methods described herein are used in conjunction with computer systems, platforms, software, and networks, that facilitate the detection of the binding domains to one or more peptides of a peptide array. The systems, platforms, software, networks, and methods include one or more non-transitory computer readable storage media encoded with a program including instructions executable by the operating system of an optionally networked digital processing device. In further embodiments, a computer readable storage medium is a tangible component of a digital processing device. In still further embodiments, a computer readable storage medium is optionally removable from a digital processing device. In some embodiments, a computer readable storage medium includes, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic disk drives, magnetic tape drives, optical disk drives, cloud computing systems and services, and the like. In some cases, the program and instructions are permanently, substantially permanently, semipermanently, or non-transitorily encoded on the media. Computer program

[0117] In some embodiments, the systems, platforms, software, networks, and methods disclosed herein include at least one computer program. A computer program includes a sequence of instructions, executable in the digital processing device's CPU, written to perform a specified task. In light of the disclosure provided herein, those of skill in the art will recognize that a computer program may be written in various versions of various languages. In some

embodiments, a computer program comprises one sequence of instructions. In some

embodiments, a computer program comprises a plurality of sequences of instructions. In some embodiments, a computer program is provided from one location. In other embodiments, a computer program is provided from a plurality of locations. In various embodiments, a computer program includes one or more software modules. In various embodiments, a computer program includes, in part or in whole, one or more web applications, one or more mobile applications, one or more standalone applications, one or more web browser plug-ins, extensions, add-ins, or addons, or combinations thereof. Non-limiting examples of computer programs that can be used with the present disclosure include databases that provide the identity of known linear epitopes for existing antibodies, including databases such as Bcipep, FIMM, and SVMTrip. In addition, machine learning algorithms such as Hidden Markov Model (HMM) , Artificial Neural Network (ANN) , and Support Vector Machine (SVM) can be used to characterize binding domains that bind to one or more peptides specifically or off-target.

Web application

[0118] In some embodiments, a computer program includes a web application. In light of the disclosure provided herein, those of skill in the art will recognize that a web application, in various embodiments, utilizes one or more software frameworks and one or more database systems. In some embodiments, a web application is created upon a software framework such as Microsoft^® .NET or Ruby on Rails (RoR). In some embodiments, a web application utilizes one or more database systems including, by way of non-limiting examples, relational, non-relational, object oriented, associative, and XML database systems. In further embodiments, suitable relational database systems include, by way of non-limiting examples, Microsoft^® SQL Server, mySQL™, and Oracle^®. Those of skill in the art will also recognize that a web application, in various embodiments, is written in one or more versions of one or more languages. A web application may be written in one or more markup languages, presentation definition languages, client-side scripting languages, server-side coding languages, database query languages, or combinations thereof. In some embodiments, a web application is written to some extent in a markup language such as Hypertext Markup Language (HTML), Extensible Hypertext Markup Language (XHTML), or extensible Markup Language (XML). In some embodiments, a web application is written to some extent in a presentation definition language such as Cascading Style Sheets (CSS). In some embodiments, a web application is written to some extent in a client-side scripting language such as Asynchronous Javascript and XML (AJAX), Flash^® Actionscript, Javascript, or Silverlight^®. In some embodiments, a web application is written to some extent in a server-side coding language such as Active Server Pages (ASP), ColdFusion^®, Perl, Java™, JavaServer Pages (JSP), Hypertext Preprocessor (PHP), Python™, Ruby, Tel, Smalltalk, WebDNA^®, or Groovy. In some embodiments, a web application is written to some extent in a database query language such as Structured Query Language (SQL). In some embodiments, a web application integrates enterprise server products such as IBM^® Lotus Domino^®. A web application for providing a career development network for artists that allows artists to upload information and media files, in some embodiments, includes a media player element. In various further embodiments, a media player element utilizes one or more of many suitable multimedia technologies including, by way of non-limiting examples, Adobe^® Flash^®, HTML 5, Apple^® QuickTime^®, Microsoft^® Silverlight^®, Java™, and Unity^®.

Mobile application

[0119] In some embodiments, a computer program includes a mobile application provided to a mobile digital processing device. In some embodiments, the mobile application is provided to a mobile digital processing device at the time it is manufactured. In other embodiments, the mobile application is provided to a mobile digital processing device via the computer network described herein.

[0120] In view of the disclosure provided herein, a mobile application is created by techniques known to those of skill in the art using hardware, languages, and development environments known to the art. Those of skill in the art will recognize that mobile applications are written in several languages. Suitable programming languages include, by way of non-limiting examples, C, C++, C#, Objective-C, Java™, Javascript, Pascal, Object Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML with or without CSS, or combinations thereof.

[0121] Suitable mobile application development environments are available from several sources. Commercially available development environments include, by way of non-limiting examples, AirplaySDK, alcheMo, Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework, Rhomobile, and WorkLight Mobile Platform. Other development environments are available without cost including, by way of non-limiting examples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile device manufacturers distribute software developer kits including, by way of non-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK, BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, and Windows® Mobile SDK.

[0122] Those of skill in the art will recognize that several commercial forums are available for distribution of mobile applications including, by way of non-limiting examples, Apple® App Store, Android™ Market, BlackBerry® App World, App Store for Palm devices, App Catalog for webOS, Windows® Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, and Nintendo® DSi Shop.

Standalone application

[0123] In some embodiments, a computer program includes a standalone application, which is a program that is run as an independent computer process, not an add-on to an existing process, e.g., not a plug-in. Those of skill in the art will recognize that standalone applications are often compiled. A compiler is a computer program(s) that transforms source code written in a programming language into binary object code such as assembly language or machine code. Suitable compiled programming languages include, by way of non-limiting examples, C, C++, Objective-C, COBOL, Delphi, Eiffel, Java™, Lisp, Python™, Visual Basic, and VB .NET, or combinations thereof. Compilation is often performed, at least in part, to create an executable program. In some embodiments, a computer program includes one or more executable complied applications. Software modules

[0124] The systems, platforms, software, networks, and methods disclosed herein include, in various embodiments, software, server, and database modules. In view of the disclosure provided herein, software modules are created by techniques known to those of skill in the art using machines, software, and languages known to the art. The software modules disclosed herein are implemented in a multitude of ways. In various embodiments, a software module comprises a file, a section of code, a programming object, a programming structure, or combinations thereof. In further various embodiments, a software module comprises a plurality of files, a plurality of sections of code, a plurality of programming objects, a plurality of programming structures, or combinations thereof. In various embodiments, the one or more software modules comprise, by way of non-limiting examples, a web application, a mobile application, and a standalone application. In some embodiments, software modules are in one computer program or application. In other embodiments, software modules are in more than one computer program or application. In some embodiments, software modules are hosted on one machine. In other embodiments, software modules are hosted on more than one machine. In further embodiments, software modules are hosted on cloud computing platforms. In some embodiments, software modules are hosted on one or more machines in one location. In other embodiments, software modules are hosted on one or more machines in more than one location.

ENUMERATED EMBODIMENTS

[0125] Embodiment I-1. A method of selecting a binding partner that binds to a target protein, the method comprising a round of selection comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides from the target protein.

[0126] Embodiment I-2. The method of Embodiment I-1, further comprising, contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein. [0127] Embodiment I-3. The method of Embodiment I-1, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0128] Embodiment I-4. The method of Embodiment I-1, wherein the library of binding domains are encoded by a polynucleotide.

[0129] Embodiment I-5. The method of Embodiment I-1, wherein the isolated binding domains are sequenced.

[0130] Embodiment I-6. The method of Embodiment I-1, wherein binding of the binding domains to one or more peptides is detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance.

[0131] Embodiment I-7. The method of Embodiment I-1, wherein the isolated binding domain binds specifically to one peptide from the target protein.

[0132] Embodiment I-8. The method of Embodiment I-1, wherein the isolated binding domain binds specifically to multiple peptides from the target protein.

[0133] Embodiment I-9. The method of Embodiment I-1, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection according to the method of Embodiment I-1.

[0134] Embodiment I- 10. The method of Embodiment I-9, wherein polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection.

[0135] Embodiment I-11. The method of Embodiment I-1, wherein the isolated binding domains are binned according to the peptide bound by the isolated binding domain.

[0136] Embodiment I-12. The method of Embodiment I-1, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0137] Embodiment I-13. The method of Embodiment I-1, wherein the library of binding domains comprises a B cell library from a naive subject. [0138] Embodiment I-14. The method of Embodiment I-1, wherein the first and second peptide arrays are bound to a microtiter plate.

[0139] Embodiment I-15. The method of Embodiment I-1, wherein the first and second peptide arrays are printed on a substrate.

[0140] Embodiment I-16. The method of Embodiment I-1, wherein the first and second peptide arrays are spotted on a substrate.

[0141] Embodiment I-17. The method of Embodiment I-15 or Embodiment I-16, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0142] Embodiment I-18. The method of Embodiment I-1, wherein the method eliminates deadend monoclonal antibodies from the library of binding domains.

[0143] Embodiment I-19. The method of Embodiment I-1, wherein the binding partner is a monoclonal antibody or an antibody analog scaffold.

[0144] Embodiment I-20. The method of Embodiment I-1, wherein the method selects a monoclonal antibody that binds to multiple epitopes of the target protein.

[0145] Embodiment I-21. The method of Embodiment I-1, wherein the method selects a monoclonal antibody that binds to at least two homologs of the target protein.

[0146] Embodiment I-22. The method of Embodiment I-1, wherein the method selects a monoclonal antibody that binds to an active domain of the target protein.

[0147] Embodiment I-23. The method of Embodiment I-1, wherein the method selects a monoclonal antibody that binds to a target epitope of the target protein.

[0148] Embodiment I-24. The method of Embodiment I-1, wherein the method further comprises a functional assay.

[0149] Embodiment I-25. A method of eliminating dead-end binding partners from a library of binding domains comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; (c) selecting and isolating the binding domains that bind non-specifically to one or more peptides from the target protein; and (d) eliminating the binding domains selected and isolated in step (c).

[0150] Embodiment I-26. The method of Embodiment I-25, further comprising contacting the isolate binding domains of (b) and (c) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0151] Embodiment I-27. The method of Embodiment I-25, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0152] Embodiment I-28. The method of Embodiment I-25, wherein the library of binding domains are encoded by a polynucleotide.

[0153] Embodiment I-29. The method of Embodiment I-25, wherein the isolated binding domains are sequenced.

[0154] Embodiment I-30. The method of Embodiment I-25, wherein binding of the binding domains to one or more peptides is detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance.

[0155] Embodiment I-31. The method of Embodiment I-25, wherein the isolated binding domain binds specifically to one peptide from the target protein.

[0156] Embodiment I-32. The method of Embodiment I-25, wherein the isolated binding domain binds specifically to multiple peptides from the target protein.

[0157] Embodiment I-33. The method of Embodiment I-25, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection according to the method of Embodiment I-1.

[0158] Embodiment I-34. The method of Embodiment I-33, wherein polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection. [0159] Embodiment I-35. The method of Embodiment I-25, wherein the isolated binding domains are binned according to the peptide bound by the isolated binding domain.

[0160] Embodiment I-36. The method of Embodiment I-25, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0161] Embodiment I-37. The method of Embodiment I-25, wherein the library of binding domains comprises a B cell library from a naive subject.

[0162] Embodiment I-38. The method of Embodiment I-25, wherein the first and second peptide arrays are printed on a substrate.

[0163] Embodiment I-39. The method of Embodiment I-25, wherein the first and second peptide arrays are spotted on a substrate.

[0164] Embodiment I-40. The method of Embodiment I-38 or Embodiment I-39, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0165] Embodiment I-41. The method of Embodiment I-25, wherein the method eliminates a monoclonal antibody that binds to multiple epitopes of the target protein.

[0166] Embodiment I-42. The method of Embodiment I-25, wherein the method eliminates a monoclonal antibody that binds to a functional domain of the target protein.

[0167] Embodiment I-43. The method of Embodiment I-25, wherein the method selects a monoclonal antibody that binds to a target epitope of the target protein.

[0168] Embodiment I-44. The method of Embodiment I-25, wherein the method eliminates a monoclonal antibody that binds to multiple peptides of an epitope of the target protein.

[0169] Embodiment I-45. A method of selecting a binding partner that binds to two or more peptides of an epitope in a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to the two or more peptides.

[0170] Embodiment I-46. The method of Embodiment I-45, further comprising contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0171] Embodiment I-47. The method of Embodiment I-45, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0172] Embodiment I-48. The method of Embodiment I-45, wherein the library of binding domains are encoded by a polynucleotide.

[0173] Embodiment I-49. The method of Embodiment I-45, wherein the isolated binding domains are sequenced.

[0174] Embodiment I-50. The method of Embodiment I-45, wherein binding of the binding domains to one or more peptides is detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance.

[0175] Embodiment I-51. The method of Embodiment I-45, wherein the isolated binding domain binds specifically to one peptide from the target protein.

[0176] Embodiment I-52. The method of Embodiment I-45, wherein the isolated binding domain binds specifically to two or more peptides from the target protein.

[0177] Embodiment I-53. The method of Embodiment I-45, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection according to the method of Embodiment I-1.

[0178] Embodiment I-54. The method of Embodiment I-53, wherein polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection. [0179] Embodiment I-55. The method of Embodiment I-45, wherein the isolated binding domains are binned according to the peptide bound by the isolated binding domain.

[0180] Embodiment I-56. The method of Embodiment I-45, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0181] Embodiment I-57. The method of Embodiment I-45, wherein the library of binding domains comprises a B cell library from a naive subject.

[0182] Embodiment I-58. The method of Embodiment I-45, wherein the first and second peptide arrays are bound to a microtiter plate.

[0183] Embodiment I-59. The method of Embodiment I-45, wherein the first and second peptide arrays are printed on a substrate.

[0184] Embodiment I-60. The method of Embodiment I-45, wherein the first and second peptide arrays are spotted on a substrate.

[0185] Embodiment I-61. The method of Embodiment I-59 or Embodiment I-60, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0186] Embodiment I-62. The method of Embodiment I-45, wherein the method eliminates dead-end monoclonal antibodies from the library of binding domains.

[0187] Embodiment I-63. The method of Embodiment I-45, wherein the method selects a monoclonal antibody that binds to at least two homologs of the target protein.

[0188] Embodiment I-64. The method of Embodiment I-45, wherein the method selects a monoclonal antibody that binds to an active domain of the target protein.

[0189] Embodiment I-65. The method of Embodiment I-45, wherein the method selects a monoclonal antibody that binds to a target epitope of the target protein.

[0190] Embodiment I-66. A method of selecting a binding partner that binds to at least two homologs of a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides from at least two homologs of the target protein.

[0191] Embodiment I-67. The method of Embodiment I-66, further comprising contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering multiple homologs of the target protein;

[0192] Embodiment I-68. The method of Embodiment I-66, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0193] Embodiment I-69. The method of Embodiment I-66, wherein the library of binding domains are encoded by a polynucleotide.

[0194] Embodiment I-70. The method of Embodiment I-66, wherein the isolated binding domains are sequenced.

[0195] Embodiment I-71. The method of Embodiment I-66, wherein binding of the binding domains to one or more peptides is detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance.

[0196] Embodiment I-72. The method of Embodiment I-66, wherein the isolated binding domain binds specifically to one peptide from the target protein.

[0197] Embodiment I-73. The method of Embodiment I-66, wherein the isolated binding domain binds specifically to multiple peptides from the target protein.

[0198] Embodiment I-74. The method of Embodiment I-66, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection according to the method of Embodiment I-1.

[0199] Embodiment I-75. The method of Embodiment I-74, wherein polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection. [0200] Embodiment I-76. The method of Embodiment I-66, wherein the isolated binding domains are binned according to the peptide bound by the isolated binding domain.

[0201] Embodiment I-77. The method of Embodiment I-66, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0202] Embodiment I-78. The method of Embodiment I-66, wherein the library of binding domains comprises a B cell library from a naive subject.

[0203] Embodiment I-79. The method of Embodiment I-66, wherein the first and second peptide arrays are bound to a microtiter plate.

[0204] Embodiment I-80. The method of Embodiment I-66, wherein the first and second peptide arrays are printed on a substrate.

[0205] Embodiment I-81. The method of Embodiment I-66, wherein the first and second peptide arrays are spotted on a substrate.

[0206] Embodiment I-82. The method of Embodiment I-80 or Embodiment I-81, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0207] Embodiment I-83. The method of Embodiment I-66, wherein the method eliminates dead-end monoclonal antibodies from the library of binding domains.

[0208] Embodiment I-84. The method of Embodiment I-66, wherein the method selects a monoclonal antibody that binds to multiple epitopes of the target protein.

[0209] Embodiment I-85. The method of Embodiment I-66, wherein the method selects a monoclonal antibody that binds to an active domain of the target protein.

[0210] Embodiment I-86. The method of Embodiment I-66, wherein the method selects a monoclonal antibody that binds to a target epitope of the target protein.

[0211] Embodiment I-87. A method of selecting a binding partner that binds to a functional domain of a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides from the functional domain.

[0212] Embodiment I-88. The method of Embodiment I-87, further comprising contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein;

[0213] Embodiment I-89. The method of Embodiment I-87, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0214] Embodiment I-90. The method of Embodiment I-87, wherein the library of binding domains are encoded by a polynucleotide.

[0215] Embodiment I-91. The method of Embodiment I-87, wherein the isolated binding domains are sequenced.

[0216] Embodiment I-92. The method of Embodiment I-87, wherein binding of the binding domains to one or more peptides is detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance.

[0217] Embodiment I-93. The method of Embodiment I-87, wherein the isolated binding domain binds specifically to one peptide from the target protein.

[0218] Embodiment I-94. The method of Embodiment I-87, wherein the isolated binding domain binds specifically to multiple peptides from the target protein.

[0219] Embodiment I-95. The method of Embodiment I-87, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection according to the method of Embodiment I-1.

[0220] Embodiment I-96. The method of Embodiment I-95, wherein polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection. [0221] Embodiment I-97. The method of Embodiment I-87, wherein the isolated binding domains are binned according to the peptide bound by the isolated binding domain.

[0222] Embodiment I-98. The method of Embodiment I-87, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0223] Embodiment I-99. The method of Embodiment I-87, wherein the library of binding domains comprises a B cell library from a naive subject.

[0224] Embodiment I- 100. The method of Embodiment I-87, wherein the first and second peptide arrays are bound to a microtiter plate.

[0225] Embodiment I- 101. The method of Embodiment I-87, wherein the first and second peptide arrays are printed on a substrate.

[0226] Embodiment I-102. The method of Embodiment I-87, wherein the first and second peptide arrays are spotted on a substrate.

[0227] Embodiment I-103. The method of Embodiment I-101 or Embodiment I-102, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0228] Embodiment I-104. The method of Embodiment I-87, wherein the method eliminates dead-end monoclonal antibodies from the library of binding domains.

[0229] Embodiment I-105. The method of Embodiment I-87, wherein the method selects a monoclonal antibody that binds to multiple epitopes of the target protein.

[0230] Embodiment I-106. The method of Embodiment I-87, wherein the method selects a monoclonal antibody that binds to at least two homologs of the target protein.

[0231] Embodiment I-107. The method of Embodiment I-87, wherein the method selects a monoclonal antibody that binds to a target epitope of the target protein.

[0232] Embodiment I-108. A method of selecting a binding partner that binds to a target epitope of a target protein comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (d) selecting and isolating the binding domains that bind to one or more peptides comprising the target epitope.

[0233] Embodiment I-109. The method of Embodiment I-108, further comprising contacting the isolated binding domains of (c) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein;

[0234] Embodiment I-110. The method of Embodiment I-108, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0235] Embodiment I-111. The method of Embodiment I-108, wherein the library of binding domains are encoded by a polynucleotide.

[0236] Embodiment I-112. The method of Embodiment I-108, wherein the isolated binding domains are sequenced.

[0237] Embodiment I-113. The method of Embodiment I-108, wherein binding of the binding domains to one or more peptides is detected by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance.

[0238] Embodiment I-114. The method of Embodiment I-108, wherein the isolated binding domain binds specifically to one peptide from the target protein.

[0239] Embodiment I-115. The method of Embodiment I-108, wherein the isolated binding domain binds specifically to multiple peptides from the target protein.

[0240] Embodiment I-116. The method of Embodiment I-108, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection according to the method of Embodiment I-1.

[0241] Embodiment I-117. The method of Embodiment I-116, wherein polynucleotides encoding the isolated binding domains are mutated prior the additional round of selection. [0242] Embodiment I-118. The method of Embodiment I-108, wherein the isolated binding domains are binned according to the peptide bound by the isolated binding domain.

[0243] Embodiment I-119. The method of Embodiment I-108, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0244] Embodiment I-120. The method of Embodiment I-108, wherein the library of binding domains comprises a B cell library from a naive subject.

[0245] Embodiment I-121. The method of Embodiment I-108, wherein the first and second peptide arrays are bound to a microtiter plate.

[0246] Embodiment I-122. The method of Embodiment I-108, wherein the first and second peptide arrays are printed on a substrate.

[0247] Embodiment I-123. The method of Embodiment I-108, wherein the first and second peptide arrays are spotted on a substrate.

[0248] Embodiment I-124. The method of Embodiment I-122 or Embodiment I-123, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0249] Embodiment I-125. The method of Embodiment I-108, wherein the method eliminates dead-end monoclonal antibodies from the library of binding domains.

[0250] Embodiment I-126. The method of Embodiment I-108, wherein the method selects a monoclonal antibody that binds to multiple epitopes of the target protein.

[0251] Embodiment I-127. The method of Embodiment I-108, wherein the method selects a monoclonal antibody that binds to at least two homologs of the target protein.

[0252] Embodiment I-128. The method of Embodiment I-108, wherein the method selects a monoclonal antibody that binds to an active domain of the target protein.

[0253] Embodiment I-129. A method of selecting a multi-specific binding partner comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a subset of a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides comprising the target epitope.

[0254] Embodiment I-130. The method of Embodiment I-129, further comprising contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein;

[0255] Embodiment I-131. The method of Embodiment I-129, wherein the multispecific monoclonal binding partner comprises a bispecific monoclonal antibody.

[0256] Embodiment I-132. The method of Embodiment I-129, wherein the multispecific monoclonal binding partner comprises a trispecific monoclonal antibody.

[0257] Embodiment I-133. A method of developing a polypeptide therapeutic comprising a binding domain, the method comprising: (a) contacting a library of binding domains to a first peptide array, wherein the first peptide array comprises peptides covering at least a proteome of an organism; (b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; and (c) selecting and isolating the binding domains that bind to one or more peptides comprising the target epitope.

[0258] Embodiment I-134. The method of Embodiment I-133, further comprising contacting the isolated binding domains of (b) to a second peptide array, wherein the second peptide array comprises polypeptides covering the target protein.

[0259] Embodiment II- 1. A method of selecting a binding partner that binds to a target protein, the method comprising:

(a) contacting a library of binding domains to a diverse peptide library, wherein the diverse peptide library comprises peptides covering at least a subset of a proteome of an organism, wherein the subset of the proteome comprises one or more peptides of the target protein;

(b) selecting and isolating the binding domains that bind to one or more peptides from the target protein; (c) contacting the selected binding domains from step (b) to a focused peptide library, wherein the focused peptide library comprises peptides covering the target protein;

(d) selecting and isolating binding domains that binds to one or more peptides from the target protein in the focused peptide library; and

(e) selecting the binding partner from the isolated binding domains of (d).

[0260] Embodiment II-2. The method of Embodiment II- 1, wherein the diverse peptide library comprises at least 10% of the proteome of an organism.

[0261] Embodiment II-3. The method of Embodiment II- 1 or II-2, wherein the at least one isolated binding domain exhibits one or more characteristics selected from the group consisting of specificity to a target, little or no off-target binding, low promiscuity, and pan-species binding.

[0262] Embodiment II-4. The method of any one of Embodiments II-1 to II-3, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0263] Embodiment II-5. The method of any one of Embodiments II-1 to II-4, wherein the binding domains of the library are encoded by polynucleotides.

[0264] Embodiment II-6. The method of any one of Embodiments II-1 to II-5, wherein the isolated binding domains are sequenced.

[0265] Embodiment II-7. The method of any one of Embodiments II-1 to II-6, wherein the isolated binding domains bind specifically to one peptide from the target protein.

[0266] Embodiment II-8. The method of any one of Embodiments II-1 to II-6, wherein the isolated binding domains bind specifically to multiple peptides from the target protein.

[0267] Embodiment II-9. The method of any one of Embodiments II-1 to II-8, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection comprising steps (a) and (b) or steps (c) and (d). [0268] Embodiment II-10. The method of Embodiment II-9, wherein the isolated binding domains are encoded by polynucleotides, and the polynucleotides are mutated prior the additional round of selection.

[0269] Embodiment II- 11. The method of any one of Embodiments II-1 to II-10, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0270] Embodiment II-12. The method of any one of Embodiments II-1 to II-10, wherein the library of binding domains comprises a B cell library from a naive subject.

[0271] Embodiment II-13. The method of any one of Embodiments II-1 to II-12, wherein the diverse and focused peptide libraries are bound to a microtiter plate.

[0272] Embodiment II-14. The method of any one of Embodiments II-1 to II-13, wherein the diverse and focused peptide libraries are printed on a substrate.

[0273] Embodiment II-15. The method of any one of Embodiments II-1 to II-13, wherein the diverse and focused peptide libraries are spotted on a substrate.

[0274] Embodiment II-16. The method of Embodiment II-14 or II-15, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

[0275] Embodiment II-17. The method of any one of Embodiments II-1 to II-16, further comprising selecting, isolating, and eliminating the binding domains that bind non-specifically to one or more peptides from the target protein in step (b) or step (d), wherein eliminating the binding domains that bind non-specifically eliminates dead-end binding partners from the library of binding domains.

[0276] Embodiment II-18. The method any one of Embodiments II-1 to II-17, wherein the binding partner is a monoclonal antibody or an antibody analog scaffold.

[0277] Embodiment II-19. The method of any one of Embodiments II-1 to II-7 or II-9 to II-18, wherein the binding partner comprises a monoclonal antibody that binds to multiple epitopes of the target protein. [0278] Embodiment II-20. The method any one of Embodiments II- 1 to II-19, wherein the binding partner is a monoclonal antibody that binds to at least two homologs of the target protein.

[0279] Embodiment II-21. The method of any one of Embodiments II-1 to II-20, wherein the binding partner is a monoclonal antibody that binds to an active domain of the target protein.

[0280] Embodiment II-22. The method of any one of Embodiments II-1 to II-21, wherein the binding partner is a monoclonal antibody that binds to a target epitope of the target protein.

[0281] Embodiment II-23. The method any one of Embodiments II-1 to II-22, further comprising evaluating one or more of the isolated binding domains with a functional assay.

[0282] Embodiment II-24. The method of any one of Embodiments II-1 to II-23, wherein the binding partner binds to two or more peptides of an epitope in a target protein, wherein the subset of the proteome of the organism comprises the two or more peptides of the epitope in the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to the two or more peptides of the epitope in the target protein.

[0283] Embodiment II-25. The method of any one of Embodiments II-1 to II-24, wherein the binding partner binds to two or more peptides of an epitope in a target protein, wherein the focused peptide library comprises peptides that cover the two or more peptides of the epitope in the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to the two or more peptides of the epitope in the target protein.

[0284] Embodiment II-26. The method of any one of Embodiments II-1 to II-23, wherein the binding partner binds to at least two homologs of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the at least two homologs of the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to one or more peptides from the at least two homologs of the target protein.

[0285] Embodiment II-27. The method of any one of Embodiments II-1 to II-23, or II-26, wherein the binding partner binds to at least two homologs of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the at least two homologs of the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to one or more peptides from the at least two homologs of the target protein.

[0286] Embodiment II-28. The method of any one of Embodiments II- 1 to II-23, wherein the binding partner binds to a functional domain of the target protein, wherein the subset of the proteome of the organism comprises the functional domain of the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to one or more peptides from the functional domain of the target protein.

[0287] Embodiment II-29. The method of any one of Embodiments II-1 to II-23 or II-28, wherein the binding partner binds to a functional domain of the target protein, wherein the focused peptide library comprises one or more peptides from the functional domain of the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to one or more peptides from the functional domain of the target protein.

[0288] Embodiment II-30. The method of any one of Embodiments II-1 to II-23, wherein the binding partner binds to a target epitope of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the target epitope, and wherein step (b) comprises selecting and isolating the binding domains that bind to the one or more peptides of the target epitope.

[0289] Embodiment II-31. The method of any one of Embodiments II-1 to II-23 or II-30, wherein the binding partner binds to a target epitope of a target protein, wherein the focused peptide library comprises one or more peptides of the target epitope, and wherein step (d) comprises selecting and isolating the binding domains that bind to the one or more peptides of the target epitope.

[0290] Embodiment II-32. The method of Embodiment II-30 or II-31, wherein the binding partner is a multispecific monoclonal binding partner.

[0291] Embodiment II-33. The method of Embodiment II-32, wherein the multispecific monoclonal binding partner comprises a bispecific monoclonal antibody. [0292] Embodiment II-34. The method of Embodiment II-32, wherein the multispecific monoclonal binding partner comprises a trispecific monoclonal antibody.

[0293] Embodiment II-35. A system for selecting a binding partner that binds to a target protein, the system comprising: a diverse peptide library comprising peptides covering at least a subset of a proteome of an organism, wherein the subset of the proteome comprises one or more peptides of the target protein; and a focused peptide library, wherein the focused peptide library comprises peptides covering the target protein.

[0294] Embodiment II-36. The system of Embodiment II-35, further comprising a library of binding domains.

[0295] Embodiment II-37. The system of Embodiment II-35 or II-36, wherein the diverse peptide library comprises at least 10% of the proteome of an organism.

[0296] Embodiment II-38. The system of Embodiment II-36 or II-37, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

[0297] Embodiment II-39. The system of any one of Embodiments II-36 to II-38, wherein the binding domains of the library are encoded by polynucleotides.

[0298] Embodiment II-40. The system of any one of Embodiments II-36 to II-39, wherein the library of binding domains comprises a B cell library from an immunized subject.

[0299] Embodiment II-41. The system of any one of Embodiments II-36 to II-39, wherein the library of binding domains comprises a B cell library from a naive subject.

[0300] Embodiment II-42. The system of any one of Embodiments II-35 to II-41, wherein the diverse and focused peptide libraries are bound to a microtiter plate.

[0301] Embodiment II-43. The system of any one of Embodiments II-35 to II-42, wherein the diverse and focused peptide libraries are printed on a substrate. [0302] Embodiment II-44. The system of any one of Embodiments II-35 to II-42, wherein the diverse and focused peptide libraries are spotted on a substrate.

[0303] Embodiment II-45. The system of Embodiment II-43 or II-44, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

EXAMPLES

[0304] The following non-limiting examples serves to further illustrate the present disclosure. [0305] Example 1: Diverse and Focused Peptide Arrays

[0306] Diverse libraries. Diverse peptide libraries were prepared to sample the highly diverse sequence space represented in a combinatorial peptide library, and provide individual peptides, including significant peptides, comprising enriched in motifs that predicted biding epitopes. The enriched motifs served as basis for identifying input sequences that were used to design focused libraries.

[0307] The diverse libraries used in the methods provided were prepared as primary highly diverse combinatorial libraries of 126,009 peptides (V13 library) and of 3.3M peptides (VI 5). The VI 3 library comprised peptides with a median length of 9 residues, ranging from 5 to 13 amino acids, and designed to include 99.9% of all possible 4-mers and 48.3% of all possible 5- mers of 16 amino acids (methionine, M; cysteine, C; isoleucine, I; and threonine, T were excluded). The VI 5 library comprised peptides designed to include 100% of all possible 4-mers to 6-mers. The peptides were synthesized on an 200mm silicon oxide wafer using standard semiconductor photolithography tools adapted for tert-butyloxycarbonyl (BOC) protecting group peptide chemistry (Legutki JB et al, Nature Communications. 2014;5:4785). Briefly, an aminosilane functionalized wafer was coated with BOC-glycine. Next, photoresist containing a photoacid generator, which is activated by UV light, was applied to the wafer by spin coating. Exposure of the wafer to UV light (365nm) through a photomask allows for the fixed selection of which features on the wafer will be exposed using a given mask. After exposure to UV light, the wafer was heated, allowing for BOC-deprotection of the exposed features. Subsequent washing, followed the by application of an activated amino acids completes the cycle. With each cycle, a specific amino acid was added to the N-terminus of peptides located at specific locations on the array. These cycles were repeated, varying the mask and amino acids coupled, to achieve the combinatorial peptide library. Thirteen rectangular regions with the dimensions of standard microscope slides, were diced from each wafer. Each completed wafer was diced into 13 rectangular regions with the dimensions of standard microscope slides (25mm X 75mm). Each of these slides contained 24 arrays in eight rows by three columns. Finally, protecting groups on the side chains of some amino acids were removed using a standard cocktail. The finished slides were stored in a dry nitrogen environment until needed. A number of quality tests are performed ensure arrays are manufactured within process specifications including the use of 3σ statistical limits for each step. Wafer batches were sampled intermittently by MALDI-MS to identify that each amino acid was coupled at the correct step, ensuring that the individual steps constituting the combinatorial synthesis were correct. Wafer manufacturing was tracked from beginning to end via an electronic custom Relational Database which is written in Visual Basic and has an access front end with an SQL back end. The front-end user interface allows operators to enter production info into the database with ease. The SQL back end provides a simple method for database backup and integration with other computer systems for data share as needed. Data typically tracked include chemicals, recipes, time and technician performing tasks. After a wafer is produced the data is reviewed and the records are locked and stored. Finally, each lot is evaluated in a binding assay to confirm performance, as described below.

[0308] Monoclonal binding to the array peptides of the diverse library identified individual peptides, including significant peptides, that comprised 3-5 mer motifs, which were used to identify input sequences for designing focused libraries.

[0309] Focused libraries. Focused libraries were prepared to vary a number of positions around the input sequence comprising enriched motifs of individual peptides, including significant peptides, identified in the diverse library. The focused library used in the methods provided was prepared as a library of 16,920 peptides using a series of 24 overlapping masks, which resulted in synthesized peptides with a median length of 0 to 17 amino acid residues. The focused library is identified herein as V14.

[0310] The peptides of the focused library were designed each to provide variant sequences of one input sequence of an individual peptide, in this case a significant peptide, of the diverse library. The dimensions of each feature were 44μm X 44μm, set at 50 μm X 50 μm pitch, having a 6 μm interstitial space between features. The peptides were synthesized on an 200mm silicon oxide wafer using standard semiconductor photolithography tools adapted for tert- butyloxycarbonyl (BOC) protecting group peptide chemistry (Legutki JB et al, Nature

Communications. 2014;5:4785), as described for the synthesis of the diverse peptide library. Wafer batches were sampled intermittently by MALDI-MS to identify that each amino acid was coupled at the correct step, ensuring that the individual steps constituting the focused synthesis were correct.

[0311] Example 2: Schematic Representation of a Target Epitope Space

[0312] Diverse and Focused peptide arrays can provide distinct metrics for the selection of monoclonal antibody candidates. Diverse libraries can provide moderate resolution of epitope sequences, and epitope motifs that can be used to create focused libraries, which in turn provide high-resolution i.e. complete epitope sequences. High resolution focused libraries can identify differences in critical amino acid residues of epitopes recognized by antibodies that are assigned to different bins.

[0313] FIG. 1 is a schematic representation of a target epitope space and binding of various epitopes by antibodies from distinct antibody bins to the target epitope space. FIG. 1 illustrates that the methods of the disclosure can be used to produce high-resolution epitope mapping {See FIG. 1 illustrating the mapping of the epitopes from 4 distinct bins to select peptides in a focused peptide array). FIG. 1 also illustrates that the methods of the disclosure can be used to identify unexplored putative epitopes form a target protein.

[0314] Example 3: Schematic Representation of a Use of a Peptide Array for "Selection Steering" at the Elution Step

[0315] FIG. 2 is a schematic representation of a technique that includes three main steps that begin with the construction of a library of binding domains and binding domain display onto a phage surface. As illustrated in FIG. 2, the library of binding domains can be derived from a B cell library. The second main step includes several rounds of selection against the target antigen {i.e., panning cycle). The panning cycle includes: a) antigen binding, b) wash, and c) elution steps. FIG. 2 is a schematic representation of a use of a disclosed peptide array for "selection steering" at the eluted clone portion of the panning cycle. Lastly, FIG. 2 illustrates the third main step: clone isolation and subsequent screening for fragments with desired specificity.

[0316] Example 4: Schematic Representation of a Use of a Peptide Array for "Selection Steering" at the Antigen Binding Step

[0317] FIG. 3 is a schematic representation of a technique that includes three main steps that begin with the construction of a library of binding domains and binding domain display onto a phage surface. As illustrated in FIG. 3, the library of binding domains can be derived from a B cell library. The second main step includes several rounds of selection against the target antigen (i.e., panning cycle). The panning cycle includes: a) antigen binding, b) wash, and c) elution steps. FIG. 3 is a schematic representation of a use of a disclosed peptide array for "selection steering" at the antigen binding step of the panning cycle. Lastly, FIG. 3 illustrates the third main step: clone isolation and subsequence screening for fragments with desired specificity.

[0318] Example 5: Identification of Putative Her2 Epitope Maps on Diverse 3.3M Peptide Arrays

[0319] Binding Assay. Microarrays comprising diverse peptide arrays comprising 3.3 million peptides (VI 5 array; generally described in Example 1) were obtained and rehydrated prior to use by soaking with gentle agitation in distilled water for 1 h, PBS for 30 min and primary incubation buffer (PBST, 1% mannitol) for 1 h. Slides comprising the microarrays were loaded into an Arraylt microarray cassette (Arraylt, Sunnyvale, CA) to adapt the individual microarrays to a microtiter plate footprint.

[0320] +/- Her2 cell lysates from HEK293 cells lacking or expressing Her2 were used in competition assays of antibody binding to the array peptides to identify key binding residues bound by commercially available monoclonal antibodies (Table 1) and rank the antibody affinity according to the respective binding to diverse peptide array libraries described herein.

[0321] TABLE 1

[0322] 4 distinct clones producing primary monoclonal antibodies, respectively 44E7 clone (FIG. 5, Panel A), D8F12 clone (FIG. 5, Panel B), RM228 clone (FIG. 6, Panel A), and EP105Y (FIG. 6, Panel B), were assayed as follows.

[0323] The primary monoclonal antibodies were diluted in 120μ1 of 1% Mannitol incubation buffer to a final concentration of InM (0.25nM for V15 peptide array library; 1 nM for V13 peptide array library) and arranged in a 96-well Axygen plate. A 1 :60 solution of Origene (Rockville, MD) FIER2 overexpressing whole cell lysate in RIPA buffer, or a lysate control was spiked in as a competitor between replicate arrays. After a 5min pre-incubation at room temperature, 90ul (96-well cassettes) or 6 x 100ul (16-well cassettes) of the primary antibody solution was transferred to hybridization cassettes using an Agilent Bravo liquid handling platform (Santa Clara, CA) with a 96-channel head. Cassettes were sealed and samples incubated for 30min at 37 °C on a Teleshake 95 from Inheko (Martinsried, Germany). Arrays were then washed with 1 x PBS pH 7.4, 0.05% Tween 20, 0.1% Proclin 950, followed by 18 ΜΩ water using a Biotek 405 Select Microplate Washer (Winooski, VT). A secondary incubation for lhr. at 37 °C was performed with fluorescent secondary antibodies in 1% mannitol incubation buffer against a species appropriate IgG, followed by a wash. The assays were performed in duplicate. [0324] Data Acquisition. An Innopsys 910 AL microarray scanner (Carbonne, France) was used to obtain fluorescence intensity at each peptide. Arrays were scanned with a 635nm laser at lum resolution for 17k and 125k arrays, or simultaneously scanned with 532/635nm lasers at 0.5um resolution for 3.3M arrays.

[0325] The Mapix software application (version 7.2.1) identified regions of the images associated with each peptide feature using an automated gridding algorithm. Median pixel intensities for each peptide feature were saved as a tab-delimitated text file and stored in a database for analysis. Quantitative signal measurements were obtained at a Ι μΜ resolution and 1% feature saturation by determining a relative fluorescent value for each addressable peptide feature. Thirty measurements of binding were obtained for each of the mAbs that were assayed.

[0326] Signal Analysis. The median feature intensities of the fluorescence signals were first background subtracted relative to the negative controls (secondary antibody only), then logio transformed, then normalized by dividing by the logio transformed median.

[0327] Specificity of Array Peptide Binding. Specificity herein refers to the degree to which an antibody differentiates two different antigens. (Ref: Immunology and Infectious Disease , S.A. Frank, 2002, Princeton Univ. Press). Binding specificity for each array peptide was

characterized by the difference in binding signal obtained in the absence and in the presence of Her2 lysate competitor, the degree to which binding was attenuated by Her2 lysate peptide relative to the binding obtained in the presence of non-cognate peptide competitor i.e. cell lysate not expressing Her2 (Her2 -). Peptides having specificity for the epitope were also assessed as having the greatest target coverage.

[0328] Primary monoclonal antibodies were diluted in 120 μΐ of 1% mannitol (Sigma-Aldrich 63560) incubation buffer (10 g/1 D-Mannitol, 1 x PBS, 0.05% Tween 20, 0.1% Proclin 950, pH 7.4), to a final concentration of 1 nM and 0.25 nM then arranged in a 96-well Axygen plate (Corning). A 1 :60 dilution of FIER2 expressing whole cell lysate in RTPA buffer (Origene LY417979), or a lysate control (Origene LY500001), was spiked in as a competitor between replicate arrays. After a 5 minute pre-incubation of lysate and antibody at room temperature, 90 μΐ (17K or 126K libraries) or 600 μΐ (3.3M library) of primary antibody with competitor solution was transferred to array hybridization cassettes using a Bravo automated liquid handling platform (Agilent) with a 96-channel head. Cassettes were sealed and samples incubated for 30 minutes at 37°C on a Teleshake 95 (Inheko). Arrays were then washed with PBST (1 x PBS, 0.05% Tween 20, 0.1% Proclin 950, pH 7.4). Labeling of primary antibodies was performed as an additional incubation for 1 hour at 37°C with a species-appropriate AF647-conjugated secondary antibody (Invitrogen A21235, A21245, A21445) in 1% mannitol incubation buffer. This was followed by a final wash series with PBST, then 18Ω ultrapure water. Arrays were then dried with 90% isopropyl alcohol (IP A).

[0329] Fluorescence intensity at each peptide was acquired using a 910 AL microarray scanner (Innopsys). Arrays were scanned with a 635 nm laser at 1 μm resolution for 17K and 126K arrays, or simultaneously scanned with 532 nm and 635 nm lasers at 0.5 μm resolution for 3.3M arrays.

[0330] Peptide binding specificity was determined by the difference in the median normalized binding signal for each array peptide in the presence and absence of Her2 lysate competitor.

[0331] Peptides bound by each of the antibodies tested were ranked according to their level of relative specificity. Individual peptides, specifically significant peptides, were selected for predicting HER2 epitope sequences for each of the mAbs that were tested. Significant peptides are defined as more than one exact match without gaps, although peptides with matches of varying degrees with gaps were also acceptable.

[0332] Significant peptides having a signal that was at least >2-fold above the median were aligned to the human proteome using a modified BLAST, and scoring matrix was used to reflect the composition of the array. Peptide coverage of each position across the proteome was calculated by summing each peptide contribution at each amino acid to each protein BLAST score. Target coverage and epitope prediction was determined from the alignment score for each protein epitope as the sum of the coverage score obtained by tiling 20-mers that overlapped by 10 amino acids across the proteome relative to the known epitope.

[0333] The alignment score was calculated as the sum of all scores at each position, and was combined with the binding signal of the corresponding significant peptide to provide a motif score for each of the antibodies produced by the 44E7 clone (FIG. 5, Panel A), D8F12 clone (FIG. 5, Panel B), RM228 clone (FIG. 6, Panel A), and EP105Y (FIG. 6, Panel B). The motif scores were sufficient to predict the target epitope.

[0334] Linear arrangement of submotifs was performed and compared using CLUSTALW (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC308517/) and MUSCLE

(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC390337/) software.

[0335] The motifs were also ranked according to their enrichment in the significant peptides. Fold-enrichment was calculated relative to the incidence of the motif in all array peptides i.e. significant and non-significant library array peptides by determining the probability of a particular motif/probability of finding that motif randomly in the Library or Array.

[0336] Finally, significant peptides were aligned (CLUSTALW

(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC308517/) and MUSCLE

(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC390337/)) to determine the identity and position of conserved amino acids.

[0337] Significant peptides were ranked according to their specificity as determined by the difference in normalized binding signal obtained in the absence and presence of Her2 competitor. Peptides for which the antibodies had the highest affinity showed the least decrease in binding when in the presence of Her2 competitor relative to the binding in the absence of competitor.

[0338] The details of the sequence alignment and scoring are provided below.

[0339] Multiple sequence alignments using the top 5 unique sequence hits were generated using ClustalW as provided by the R package msa. Alignments that display the target sequence ^ included either the full target, or the listed immunogen sequence in the final alignment. Manual corrections to obvious ClustalW mis-alignment cases were done. A BLOSUM similarity scoring matrix was used to score alignments. The positional conservation score (5 ) of an alignment used for putative epitope binning was defined as:

where a_n is the length of the amino acid alphabet used during library synthesis, a is a single amino acid within the set described by a_n, and p_a is the relative proportion of a at position x in the aligned set of peptide hits.

[0340] The positional coverage score (C_x), and global coverage score (C_glob) used as a specificity metric were defined as:

where h is a peptide within a set of aligned hits of length h_n, s_ij is the BLOSUM similarity score for an amino acid at position x with reference to the target HER2 immunogen sequence, s_ii is the corresponding BLOSUM similarity score of the exact match to the target sequence, and x_n is the total number of positions displayed within the alignment. The R package Logolas was used to display positional conservation and coverage scores as sequence logos above the original alignments for all clones across the peptide libraries.

[0341] Example 6: Comparison of Putative Epitope Maps from Different Vendors

[0342] FIG. 7 illustrates a comparison of putative epitope analysis of a same antibody (3B5 clone) obtained from two distinct vendors (Thermo Fisher: TF-3B5 and Santa Cruz: SC-3B5). Panel A illustrates the putative epitopes of the anti-Her2 antibody secreting clone TF-3B5 as detected by the VI 5 array. Panel B illustrates the putative epitopes of the anti-Her2 antibody secreting clone SC-3B5 as detected by the VI 5 array.

[0343] The binding assay, data acquisition, signal analysis and specificity of binding were calculated as described in Example 5. FIG. 7 illustrates that the same monoclonal antibody clone from two different vendors produced nearly identical top peptide hits and +/-Her2 competition results, with corresponding identical Her2 epitope mapping. The results corroborate the reproducibility of the method and array platforms. [0344] Example 7: Identification of Putative Her2 Epitope Maps on Diverse 126 Thousand Peptide Arrays (V13)

[0345] Binding Assay. Microarrays comprising diverse peptide arrays comprising 126 thousand peptides (V13 array; generally described in Example 1) were prepared as described in Example 5.

[0346] Antibodies from 4 distinct clones, respectively C-3 clone (FIG. 8, Panel A), 29D8 clone (FIG. 8, Panel B), Q03B clone (FIG. 9, Panel A), and SC-3B5 (FIG. 9, Panel B), were assayed in the presence and absence of competitor Her2, as described above.

[0347] Signal analysis, data acquisition, and specificity of array peptide binding were performed and determined as described in Example 5.

[0348] Binding assays were performed on a V13 peptide array/library using +/- Her2 cell lysates to identify individual peptides, including significant peptides, and predict epitope sequences as described in Example 5.

[0349] Target coverage and alignments to peptides bound by the antibodies are shown: C-3 clone (FIG. 8, Panel A), 29D8 clone (FIG. 8, Panel B), Q03B clone (FIG. 9, Panel A), and SC- 3B5 (FIG. 9, Panel B). The motif scores were sufficient to predict the target epitope.

[0350] These data show that the diverse VI 3 peptide array can be used to identify key binding residues of cognate targets. Additionally, the same key binding residues identified by the SC- 3B5 antibody using the diverse VI 5 array peptide library (see Example 6, panel B of Figure 7), were also identified using the diverse VI 3 array peptide library (see Figure 9, panel B).

[0351] Example 8: Identification of Promiscuous Clones with Diverse Peptide Arrays

[0352] The binding assay, data acquisition, signal analysis and specificity of binding were calculated as described in the aforementioned examples.

[0353] An alignment score was calculated as the sum of all scores at each position, and was combined with the binding signal of the corresponding significant peptide to provide a motif score for each of the antibodies 44E7 clone (FIG. 5, Panel A), D8F12 clone (FIG. 5, Panel B), RM228 clone (FIG. 6, Panel A), and EP105Y (FIG. 6, Panel B) in the presence or absence of Her2 lysate. The motif scores were sufficient to predict the target epitope.

[0354] FIG. 10 illustrates a comparison of putative Her2 epitope maps potentially bound by the anti-Her2 antibody secreting 44E7 clone. Panel A illustrates the putative epitopes as detected by the VI 3 array. Panel B illustrates the putative epitopes as detected by the VI 5 array. The lower quality alignment, as indicated by the target coverage score, suggests that the anti-Her2 antibody secreting 44E7 clone may produce a more promiscuous antibody. In contrast, FIG. 11 illustrates a comparison of putative Her2 epitope maps potentially bound by the anti-Her2 antibody secreting TF-3B5 clone. Panel A illustrates the putative epitopes as detected by the VI 3 array. Panel B illustrates the putative epitopes as detected by the VI 5 array. The higher quality alignment shown on FIG. 11 suggests that the anti-Her2 antibody secreting TF-3B5 clone may produce a more specific antibody.

[0355] Example 9: Target Alignment Quality of Top V15 3.3M Peptide Library Hits Parallels Monoclonal Antibody Clone Western Blot Broad Binding Specificity

[0356] Anti-Her2 monoclonal antibodies were used as primary antibodies in a series of western blots on wild-type HEK293T (non-expressing Her2) cells and HEK293T overexpressing Her2, both purchased as lysates (Origene). Lysates were directly loaded into each lane and b-actin was used as loading lane normalization. Anti-Her2 primaries were incubated with transfer blot membrane and labeled with HRP-secondary antibody and chromogenic HRP substrate.

[0357] FIG. 12 depicts a correlation between an increased specificity in a western blot and an increased target coverage quality for the D8F12, 44E7, 29D8, and SC-3B5 anti-Her2 antibody secreting clones.

[0358] These data show that the greater the quality of the peptide alignments of the top peptides bound by each of the antibodies tested confirms the corresponding binding specificity assayed by western blots. Notably, promiscuous antibodies recognize proteins other than Her2 (D8F12), or recognize Her2 to a lesser extent (44E7) than the more specific antibodies 29D8 and SC-3B5. Thus, mAb that result in lower quality target coverage correspond to promiscuous antibodies, and peptide array alignments that diverge from the cognate sequence may identify off-target protein interactions. Quality coverage reflects the degree of conservation of the amino acids across the top peptides, and it can be used to determine specificity of the antibodies.

[0359] Example 10: +/- Her2 Assay on V15 3.3M Peptide Library Identifies Putative Off- Target Proteins for Specific Clones

[0360] The methods for performing the binding assay, data acquisition, and signal analysis, the calculation of target coverage and determination of specificity of binding were performed as described in Example 5.

[0361] FIG. 13 panel A depicts the identification of SIRT1 and ATF6-Beta as potential off- target hit proteins for the anti-Her2 antibody secreting clone Q03B. FIG. 13 panel B depicts the identification of SIRT1 and ATF6-Beta as potential off-target hit proteins for the anti-Her2 antibody secreting clone TF-3B5. FIG. 14 panel A depicts the identification of Her4 as a potential off-target protein for the anti-Her2 antibody secreting clone C-3. FIG. 14 Panel B depicts the identification of CYP2J2 as a potential off-target hit protein for the anti-Her2 antibody secreting clone 29D8. FIG. 16 summarizes potential off-target hit proteins for the anti- Her2 antibody secreting clones C-3, SC-3B5, TF-3B5, and Q03B.

[0362] These data show that binding of antibodies to the peptide arrays can be used to identify antibodies that bind motifs that are closely related to each other and that are present in multiple different proteins. In the instant example, the commercially available anti-Her2 Q03B, TF-3B5 antibodies (FIG. 13, panels A and B), and the anti Her2 C-3 and 29D antibodies (FIG. 14, panels A and B) bind motifs in proteins that are not the target protein to which they were raised. Thus, the arrays provided can discern antibodies having high specificity, as assayed by the target coverage, and low affinity, as assayed by the difference in binding signal in the presence and absence of competitor.

[0363] Example 11: Input sequences identified by antibody binding to diverse libraries provide high resolution focused sequence space

[0364] For each of the mAbs that were tested, individual peptides, including significant peptides were identified in the diverse libraries, V15 and V13, as described in the aforementioned examples. The corresponding motifs that were enriched in the significant peptides, were determined to predict HER2 epitopes, and conserved amino acids and their positions identified. Competition binding assays and data analysis were performed as described in the aforementioned examples. The top dose-responsive peptide sequences identified from the diverse VI 5 (panel A) and VI 3 (panel B) libraries for the exemplary anti-HER2 antibody C-3 are shown in FIG. 15. Regions on the target protein comprising the enriched motifs that were shown to be highly conserved across individual peptides, specifically significant peptides, identified in the diverse library, were used as input sequences to derive variant sequences thereof for designing focused libraries.

[0365] Positional variants were generated through the process of developing the focused library algorithm as described in Example 2. These variants are derived from the input sequence, mask order and amino acid order defined during focused library design.

[0366] Individual peptides, in this case significant peptides, identified in the focused libraries were aligned to the HER2 target protein, scored according to their relative specificity, and aligned to identify the consensus sequences of the epitopes.

[0367] The alignments of the top significant peptides identified from the focused library are shown in FIG. 15, panel C. The positions of the conserved amino acids for mAb C-3 show that one iteration of the combination screening of a diverse and a focus library, identified the full sequence of the linear HER2 epitope.

[0368] Example 12: Dot blot confirmation of array-predicted off-target binding partners

[0369] A dot-blot binding assay was used to confirm the array-predicted off-target(s) for the anti-Her2 antibody secreting clones described in Example 10. A nitrocellulose membrane was blocked with 5% BSA (Sigma- Aldrich A7906) in 1 x TBST (Fisher AAJ77500K2) for 1 hour after the direct addition of 1.5 μΐ of either recombinant HER4 (Sino Biological 10363-H08H), or recombinant ATF-6 Beta (Abnova H00001388-Q01). Wild-type HEK293T lysate (Origene LY500001) or HEK293T overexpressing HER2 (Origene LY417979) lysates were used as controls. Each antibody was tested at 0.4 μg/ml and 0.04 μg/ml in blocking buffer. Membranes were washed 3 times with TBST and incubated for 1 hour with a 1 :2000 dilution of goat anti- mouse HRP (Thermo 62-6520) in blocking buffer for detection. Membranes were washed 3 times with TBST and visualized with chromogenic substrate. All steps were performed at room temperature. Quantitation of spot intensities was performed using ImageJ V2.0.0 software. FIG. 17 is an image of a dot-blot membrane. A summary of the spot intensities is provided in FIG. 18

[0370] Example 13: Conformational Epitope Mapping of Therapeutic mAb:Target Structures

[0371] Ten commercially-obtained monoclonal antibodies were obtained, and a procedure similar to that in Example 5 was used to map the conformational epitopes of their respective targets. FIG. 19 demonstrates on the left side the co-crystal structure of three of the antibodies, Trastuzumab, Ipilimumab, and Nivolumab (dark structure) with their respective targets Her2, CTLA-4, and PD-1 (lighter structure) as obtained by X-ray crystallography. On the right are epitope maps of the targets Her2, CTLA-4, and PD-1, with the true positive epitope residues outlined in white. FIG. 20 presents the epitope prediction scoring data used to map the epitopes onto the crystal structures of the targets, as shown in FIG. 19. FIG. 21 presents a summary of the performance metrics for the mapping of the targets for ten monoclonal antibodies, including for Trastuzumab, Ipilimumab, and Nivolumab.

[0372] Example 14: Conformational Epitope Mapping of Therapeutic mAb:Target Structures with V15 3.3M Peptide Library and V14 17k Peptide Library

[0373] The VI 5 and V14 peptide libraries (Example 1) were used with the commercially- obtained antibodies Trastuzumab, Nivolumab, Pembrolizumab, and Ipilimumab to map the epitopes of their respective targets Her2, PD-1, PD-1, and CTLA-4. The mapping obtained using the V15 3.3M peptide library for each target is shown as the top panels of FIGS. 22-25. The mapping obtained using the V14 17k peptide library is shown as the bottom panels of FIGS. 22- 25. For each image, the scaled confidence is illustrated with a heat map, with a confidence of 0 being grey, confidence of 1 being red, and the mid-way point being blue. The heat map colors are indicated in the figures with labels.

[0374] The method for mapping the experimental peptide sequence hits to the crystal structure is described below. [0375] First, the PDB structure of the target was converted into a network graph using software that calls methods from the python packages Biopython and Networkx. Graph nodes were amino acid sidechain centroids from the target structure. Graph edges represent any 2 nodes with a pairwise distance

All possible sequence paths on the network graph of length 6 were generated.

[0376] Path Scoring: For each array hit sequence, pairwise align to all linear sequences was obtained from the sequence path generation step. If a pairwise alignment contained more than 3 matches, the alignment was scored using the scoring matrix BLOSUM62, and the alignment score added to its corresponding residues on the structure. This pairwise alignment was repeated with a set of non-holdout randomly selected array sequences.

[0377] The ratio of hits/random alignment scores was calculated; this value is the score for a node on the graph.

[0378] Interface Bin Scoring: For each node on the target structure, the sum of the alignment scores for all nodes within radius 12A of a centroid node (this constitutes an interface bin) that have an alignment score 3 -fold or greater than the mean node score across the graph was obtained. This was repeated for all nodes in the graph, setting each node as a bin centroid.

[0379] Each interface (Ι_c,n,r) bin's summed alignment score (L_c,n,r) was scaled to random sampling (R_c,n,r) by the equation:

where:

This provided a table of position-level scores, which was then used to color each residue on the PDB structure to create the heat map structure.

[0380] While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.

Claims

CLAIMS WHAT IS CLAIMED IS:

1. A method of selecting a binding partner that binds to a target protein, the method comprising:

(b) selecting and isolating the binding domains that bind to one or more peptides from the target protein;

(c) contacting the selected binding domains from step (b) to a focused peptide library, wherein the focused peptide library comprises peptides covering the target protein;

(e) selecting the binding partner from the isolated binding domains of (d).

2. The method of claim 1, wherein the diverse peptide library comprises at least 10% of the proteome of an organism.

3. The method of claim 1 or 2, wherein the at least one isolated binding domain exhibits one or more characteristics selected from the group consisting of specificity to a target, little or no off-target binding, low promiscuity, and pan-species binding.

4. The method of any one of claims 1 to 3, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

5. The method of any one of claims 1 to 4, wherein the binding domains of the library are encoded by polynucleotides.

6. The method of any one of claims 1 to 5, wherein the isolated binding domains are sequenced.

7. The method of any one of claims 1 to 6, wherein the isolated binding domains bind specifically to one peptide from the target protein.

8. The method of any one of claims 1 to 6, wherein the isolated binding domains bind specifically to multiple peptides from the target protein.

9. The method of any one of claims 1 to 8, wherein the method further comprises subjecting the isolated binding domains to at least one additional round of selection comprising steps (a) and (b) or steps (c) and (d).

10. The method of claim 9, wherein the isolated binding domains are encoded by

polynucleotides, and the polynucleotides are mutated prior the additional round of selection.

11. The method of any one of claims 1 to 10, wherein the library of binding domains comprises a B cell library from an immunized subject.

12. The method of any one of claims 1 to 10, wherein the library of binding domains comprises a B cell library from a naive subject.

13. The method of any one of claims 1 to 12, wherein the diverse and focused peptide libraries are bound to a microtiter plate.

14. The method of any one of claims 1 to 13, wherein the diverse and focused peptide libraries are printed on a substrate.

15. The method of any one of claims 1 to 13, wherein the diverse and focused peptide libraries are spotted on a substrate.

16. The method of claim 14 or 15, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.

17. The method of any one of claims 1 to 16, further comprising selecting, isolating, and eliminating the binding domains that bind non-specifically to one or more peptides from the target protein in step (b) or step (d), wherein eliminating the binding domains that bind non- specifically eliminates dead-end binding partners from the library of binding domains.

18. The method any one of claims 1 to 17, wherein the binding partner is a monoclonal antibody or an antibody analog scaffold.

19. The method of any one of claims 1 to 7 or 9 to 18, wherein the binding partner comprises a monoclonal antibody that binds to multiple epitopes of the target protein.

20. The method any one of claims 1 to 19, wherein the binding partner is a monoclonal antibody that binds to at least two homologs of the target protein.

21. The method of any one of claims 1 to 20, wherein the binding partner is a monoclonal antibody that binds to an active domain of the target protein.

22. The method of any one of claims 1 to 21, wherein the binding partner is a monoclonal antibody that binds to a target epitope of the target protein.

23. The method any one of claims 1 to 22, further comprising evaluating one or more of the isolated binding domains with a functional assay.

24. The method of any one of claims 1 to 23, wherein the binding partner binds to two or more peptides of an epitope in a target protein, wherein the subset of the proteome of the organism comprises the two or more peptides of the epitope in the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to the two or more peptides of the epitope in the target protein.

25. The method of any one of claims 1 to 24, wherein the binding partner binds to two or more peptides of an epitope in a target protein, wherein the focused peptide library comprises peptides that cover the two or more peptides of the epitope in the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to the two or more peptides of the epitope in the target protein.

26. The method of any one of claims 1 to 23, wherein the binding partner binds to at least two homologs of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the at least two homologs of the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to one or more peptides from the at least two homologs of the target protein.

27. The method of any one of claims 1 to 23, or 26, wherein the binding partner binds to at least two homologs of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the at least two homologs of the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to one or more peptides from the at least two homologs of the target protein.

28. The method of any one of claims 1 to 23, wherein the binding partner binds to a functional domain of the target protein, wherein the subset of the proteome of the organism comprises the functional domain of the target protein, and wherein step (b) comprises selecting and isolating the binding domains that bind to one or more peptides from the functional domain of the target protein.

29. The method of any one of claims 1 to 23 or 28, wherein the binding partner binds to a functional domain of the target protein, wherein the focused peptide library comprises one or more peptides from the functional domain of the target protein, and wherein step (d) comprises selecting and isolating the binding domains that bind to one or more peptides from the functional domain of the target protein.

30. The method of any one of claims 1 to 23, wherein the binding partner binds to a target epitope of a target protein, wherein the subset of the proteome of the organism comprises one or more peptides of the target epitope, and wherein step (b) comprises selecting and isolating the binding domains that bind to the one or more peptides of the target epitope.

31. The method of any one of claims 1 to 23 or 30, wherein the binding partner binds to a target epitope of a target protein, wherein the focused peptide library comprises one or more peptides of the target epitope, and wherein step (d) comprises selecting and isolating the binding domains that bind to the one or more peptides of the target epitope.

32. The method of claim 30 or claim 31, wherein the binding partner is a multispecific monoclonal binding partner.

33. The method of claim 32, wherein the multispecific monoclonal binding partner comprises a bispecific monoclonal antibody.

34. The method of claim 32, wherein the multispecific monoclonal binding partner comprises a trispecific monoclonal antibody.

35. A system for selecting a binding partner that binds to a target protein, the system comprising: a diverse peptide library comprising peptides covering at least a subset of a proteome of an organism, wherein the subset of the proteome comprises one or more peptides of the target protein; and a focused peptide library, wherein the focused peptide library comprises peptides covering the target protein.

36. The system of claim 35, further comprising a library of binding domains.

37. The system of claim 35 or 36, wherein the diverse peptide library comprises at least 10% of the proteome of an organism.

38. The system of claim 36 or 37, wherein the library of binding domains comprises a B cell library, a phage library, or combination thereof.

39. The system of any one of claims 36 to 38, wherein the binding domains of the library are encoded by polynucleotides.

40. The system of any one of claims 36 to 39, wherein the library of binding domains comprises a B cell library from an immunized subject.

41. The system of any one of claims 36 to 39, wherein the library of binding domains comprises a B cell library from a naive subject.

42. The system of any one of claims 35 to 41, wherein the diverse and focused peptide libraries are bound to a microtiter plate.

43. The system of any one of claims 35 to 42, wherein the diverse and focused peptide libraries are printed on a substrate.

44. The system of any one of claims 35 to 42, wherein the diverse and focused peptide libraries are spotted on a substrate.

45. The system of claim 43 or 44, wherein the substrate comprises glass, composite, resin, silicon or combination thereof.