Mining for the antibody-antigen interacting associations that predict the B cell epitopes

Background

Predicting B-cell epitopes is very important for designing vaccines and drugs to fight against the infectious agents. However, due to the high complexity of this problem, previous prediction methods that focus on linear and conformational epitope prediction are both unsatisfactory. In addition, antigen interacting with antibody is context dependent and the coarse binary classification of antigen residues into epitope and non-epitope without the corresponding antibody may not reveal the biological reality. Therefore, we take a novel way to identify epitopes by using associations between antibodies and antigens.

Results

Given a pair of antibody-antigen sequences, the epitope residues can be identified by two types of associations: paratope-epitope interacting biclique and cooccurrent pattern of interacting residue pairs. As the association itself does not include the neighborhood information on the primary sequence, residues' cooperativity and relative composition are then used to enhance our method. Evaluation carried out on a benchmark data set shows that the proposed method produces very good performance in terms of accuracy. After compared with other two structure-based B-cell epitope prediction methods, results show that the proposed method is competitive to, sometimes even better than, the structure-based methods which have much smaller applicability scope.

Conclusions

The proposed method leads to a new way of identifying B-cell epitopes. Besides, this antibody-specified epitope prediction can provide more precise and helpful information for wet-lab experiments.

     

A combinatorial mutagenesis approach for functional epitope mapping on phage-displayed target antigen

Although multiple different procedures to characterize the epitopes recognized by antibodies have been developed, site-directed mutagenesis remains the method of choice to define the energetic contribution of antigen residues to binding. These studies are useful to identify critical residues and to delineate functional maps of the epitopes. However, they tend to underestimate the roles of residues that are not critical for binding on their own, but contribute to the formation of the target epitope in an additive, or even cooperative, way. Mapping antigenic determinants with a diffuse energetic landscape, which establish multiple individually weak interactions with the antibody paratope, resulting in high affinity and specificity recognition of the epitope as a whole, is thus technically challenging. The current work was aimed at developing a combinatorial strategy to overcome the limitations of site-directed mutagenesis, relying on comprehensive randomization of discrete antigenic regions within phage-displayed antigen libraries. Two model antibodies recognizing epidermal growth factor were used to validate the mapping platform. Abrogation of antibody recognition due to the introduction of simultaneous replacements was able to show the involvement of particular amino acid clusters in epitope formation. The abundance of some of the original residues (or functionally equivalent amino acids sharing their physicochemical properties) among the set of mutated antigen variants selected on a given antibody highlighted their contributions and allowed delineation of a detailed functional map of the corresponding epitope. The use of the combinatorial approach could be expanded to map the interactions between other antigens/antibodies.     

A combinatorial mutagenesis approach for functional epitope mapping on phage-displayed target antigen: Application to antibodies against epidermal growth factor

Although multiple different procedures to characterize the epitopes recognized by antibodies have been developed, site-directed mutagenesis remains the method of choice to define the energetic contribution of antigen residues to binding. These studies are useful to identify critical residues and to delineate functional maps of the epitopes. However, they tend to underestimate the roles of residues that are not critical for binding on their own, but contribute to the formation of the target epitope in an additive, or even cooperative, way. Mapping antigenic determinants with a diffuse energetic landscape, which establish multiple individually weak interactions with the antibody paratope, resulting in high affinity and specificity recognition of the epitope as a whole, is thus technically challenging. The current work was aimed at developing a combinatorial strategy to overcome the limitations of site-directed mutagenesis, relying on comprehensive randomization of discrete antigenic regions within phage-displayed antigen libraries. Two model antibodies recognizing epidermal growth factor were used to validate the mapping platform. Abrogation of antibody recognition due to the introduction of simultaneous replacements was able to show the involvement of particular amino acid clusters in epitope formation. The abundance of some of the original residues (or functionally equivalent amino acids sharing their physicochemical properties) among the set of mutated antigen variants selected on a given antibody highlighted their contributions and allowed delineation of a detailed functional map of the corresponding epitope. The use of the combinatorial approach could be expanded to map the interactions between other antigens/antibodies.     

Immunoinformatics analysis of H5N1 proteome for designing an epitope-derived vaccine and predicting the prevalence of pre-existing cellular-mediated immunity toward bird flu virus in Indonesian population

As an essential step of adaptive immune response, the recognition between antigen and antibody triggers a series of self-protection mechanisms. Therefore, the prediction of antibody-binding sites (B-cell epitope) for protein antigens is an important field in immunology research. The performance of current prediction methods is far from satisfying, especially for conformational epitope prediction. Here a multi-perspective analysis was carried on with a comprehensive B-cell conformational epitope dataset, which contains 161 immunoglobulin complex structures collected from PDB, corresponding to 166 unique computationally defined epitopes. These conformational epitopes were described with parameters from different perspectives, including characteristics of epitope itself, comparison to non-epitope surface areas, and interaction pattern with antibody. According to the analysis results, B-cell conformational epitopes were relatively constant both in the number of composing residues and the accessible surface area. Though composed of spatially clustering residues, there were sequentially linear segments exist in these epitopes. Besides, statistical differences were found between epitope and non-epitope surface residues with parameters in residual and structural levels. Compared to non-epitope surface residues, epitope ones were more accessible. Amino acid enrichment and preference for specific types of residue-pair set on epitope areas have also been observed. Several amino acid properties from AAindex have been proven to distinguish epitope residues from non-epitope surface ones. Additionally, epitope residues tended to be less conservative under the environmental pressure. Measured by topological parameters, epitope residues were surrounded with fewer residues but in a more compact way. The occurrences of residue-pair sets between epitope and paratope also showed some patterns. Results indicate that, certain rules do exist in conformational epitopes in terms of size and sequential continuity. Statistical differences have been found between epitope and non-epitope surface residues in residual and structural levels. Such differences indicate the existence of distinctiveness for conformation epitopes. On the other hand, there was no accordant estimation for higher or lower values derived from any parameter for epitope residues compared with non-epitope surface residues. This observation further confirms the complicacy of characteristics for conformational epitope. Under such circumstance, it will be a more effective and accurate approach to combine several parameters to predict the conformation epitope. Finding conformational epitopes and analysing their properties is an important step to identify internal formation mechanism of conformational epitopes and this study will help future development of new prediction tools.     

Epitope-Analyzer: A structure-based webtool to analyze broadly neutralizing epitopes

The antigenic epitope regions of pathogens (e.g., viruses) are recognized by antibodies (Abs) and subsequently cleared by the host immune system, thereby protecting us from disease. Some of these epitopes are conserved among different variants or subgroups of pathogens (e.g., Influenza (FLU) viruses, Coronaviruses), hence can be targeted for potential broad-neutralization. Here we report a web-based tool, Epitope Analyzer (EA), that rapidly identifies conformational epitope and paratope residues in an antigen–antibody complex structure. Furthermore, the tool provides the ways and means to analyze broadly neutralizing epitopes by comparing the equivalent epitope residues in similar antigen structures. The similarity in the epitope residues between (multiple) pairs of similar antigen molecules suggest the presence of conserved epitopes that can be targeted by broadly neutralizing antibodies. These details can be used as a guide in developing effective treatments, such as the design of novel vaccines and formulation of cocktail of broadly neutralizing antibodies, against multiple variants or subgroups of viruses. The web application can be freely accessed from the URL, http://viperdb.scripps.edu/ea.php.     

Human immunodeficiency virus type 1-neutralizing monoclonal antibody 2F5 is multispecific for sequences flanking the DKW core epitope

Human monoclonal antibody 2F5 is one of a few human antibodies that neutralize a broad range of HIV-1 primary isolates. The 2F5 epitope on gp41 includes the sequence ELDKWA, with the core residues, DKW, being critical for antibody binding. HIV-neutralizing antibodies have never been elicited by immunization with peptides bearing ELDKWA, suggesting that important part(s) of the 2F5 paratope remain unidentified. The use of longer peptides extending beyond ELDKWA has resulted in increased epitope antigenicity, but neutralizing antibodies have not been generated. We sought to develop peptides that bind to 2F5, and that function as specific probes of the 2F5 paratope. Thus, we used 2F5 to screen a set of phage-displayed, random peptide libraries. Tight-binding clones from the random peptide libraries displayed sequence variability in the regions flanking the DKW motif. To further reveal flanking regions involved in 2F5 binding, two semi-defined libraries were constructed having 12 variegated residues either N-terminal or C-terminal to the DKW core (X(12)-AADKW and AADKW-X(12), respectively). Three clones isolated from the AADKW-X(12) library had similar high affinities, despite a lack of sequence homology among them, or with gp41. The contribution of each residue of these clones to 2F5 binding was evaluated by Ala substitution and amino acid deletion studies, and revealed that each clone bound 2F5 by a different mechanism. These results suggest that the 2F5 paratope is formed by at least two functionally distinct regions: one that displays specificity for the DKW core epitope, and another that is multispecific for sequences C-terminal to the core epitope. The implications of this second, multispecific region of the 2F5 paratope for its unique biological function are discussed.     

Mapping of antibody epitopes based on docking and homology modeling

Antibodies are key proteins produced by the immune system to target pathogen proteins termed antigens via specific binding to surface regions called epitopes. Given an antigen and the sequence of an antibody the knowledge of the epitope is critical for the discovery and development of antibody based therapeutics. In this work, we present a computational protocol that uses template-based modeling and docking to predict epitope residues. This protocol is implemented in three major steps. First, a template-based modeling approach is used to build the antibody structures. We tested several options, including generation of models using AlphaFold2. Second, each antibody model is docked to the antigen using the fast Fourier transform (FFT) based docking program PIPER. Attention is given to optimally selecting the docking energy parameters depending on the input data. In particular, the van der Waals energy terms are reduced for modeled antibodies relative to x-ray structures. Finally, ranking of antigen surface residues is produced. The ranking relies on the docking results, that is, how often the residue appears in the docking poses' interface, and also on the energy favorability of the docking pose in question. The method, called PIPER-Map, has been tested on a widely used antibody–antigen docking benchmark. The results show that PIPER-Map improves upon the existing epitope prediction methods. An interesting observation is that epitope prediction accuracy starting from antibody sequence alone does not significantly differ from that of starting from unbound (i.e., separately crystallized) antibody structure.     

Paratope and epitope mapping of the antithrombotic antibody 6B4 in complex with platelet glycoprotein Ibalpha

The monoclonal antibody 6B4 has a potent antithrombotic effect in nonhuman primates by binding to the flexible loop, also known as the beta-switch region (amino acids 230-242), of glycoprotein Ibalpha (GPIbalpha). This interaction blocks, in high shear stress conditions, the specific interaction between GPIbalpha and von Willebrand factor suppressing platelet deposition to the damaged vessel wall, a key event in the pathogenesis of arterial thrombosis. To understand the interactions between this antibody and its antigen at the amino acid level, we here report the identification of the paratope and epitope in 6B4 and GPIbalpha, respectively, by using computer modeling and site-directed mutagenesis. The docking programs ZDOCK (rigid body docking) and HADDOCK (flexible docking) were used to model the interaction of 6B4 with GPIbalpha and to delineate the respective paratope and epitope. 6B4 and GPIbalpha mutants were constructed and assayed for their capacity to bind GPIbalpha and 6B4, respectively. From these data, it is found that the paratope of 6B4 is mainly formed by five residues: Tyr(27D), Lys(27E), Asp(28), and Glu(93) located in light chain CDR1 and -3, respectively, and Tyr(100C) of the heavy chain CDR3. These residues form a valley, where the GPIbalpha flexible loop can bind via residues Asp(235) and Lys(237). The experimental results were finally used to build a more accurate docking model. Taken together, this information provides guidelines for the design of new derivatized lead compounds with antithrombotic properties.     

Delineating the functional map of the interaction between nimotuzumab and the epidermal growth factor receptor

Molecular details of epidermal growth factor receptor (EGFR) targeting by nimotuzumab, a therapeutic anti-cancer antibody, have been largely unknown. The current study delineated a functional map of their interface, based on phage display and extensive mutagenesis of both the target antigen and the Fv antibody fragment. Five residues in EGFR domain III (R353, S356, F357, T358, and H359T) and the third hypervariable region of nimotuzumab heavy chain were shown to be major functional contributors to the interaction. Fine specificity differences between nimotuzumab and other anti-EGFR antibodies were revealed. Mapping information guided the generation of a plausible in silico binding model. Knowledge about the epitope/paratope interface opens new avenues for the study of tumor sensitivity/resistance to nimotuzumab and for further engineering of its binding site. The developed mapping platform, also validated with the well-known cetuximab epitope, allows a comprehensive exploration of antigenic regions and could be expanded to map other anti-EGFR antibodies.     

Delineating the functional map of the interaction between nimotuzumab and the epidermal growth factor receptor

Molecular details of epidermal growth factor receptor (EGFR) targeting by nimotuzumab, a therapeutic anti-cancer antibody, have been largely unknown. The current study delineated a functional map of their interface, based on phage display and extensive mutagenesis of both the target antigen and the Fv antibody fragment. Five residues in EGFR domain III (R353, S356, F357, T358, and H359T) and the third hypervariable region of nimotuzumab heavy chain were shown to be major functional contributors to the interaction. Fine specificity differences between nimotuzumab and other anti-EGFR antibodies were revealed. Mapping information guided the generation of a plausible in silico binding model. Knowledge about the epitope/paratope interface opens new avenues for the study of tumor sensitivity/resistance to nimotuzumab and for further engineering of its binding site. The developed mapping platform, also validated with the well-known cetuximab epitope, allows a comprehensive exploration of antigenic regions and could be expanded to map other anti-EGFR antibodies.     

A deeper analysis of the epitope/paratope of PLY-5, a mouse monoclonal antibody which recognises the conserved undecapeptide tryptophan-rich loop (ECTGLAWEWWR) of bacterial cholesterol-dependent cytolysins

A previous study showed that the minimal epitope recognised by the PLY-5 mAb in the conserved undecapeptide Trp-rich loop of bacterial CDCs should consist of WEWWRT (Jacobs et al., 1999) [5]. Now, through immunoscreening of amino acid substitution analogues, it is concluded that the second Trp and the Arg residues are essential in the PLY-5 epitope. The E residue is an auxiliary epitope contributor. Antibody modelling and docking simulations provided support for these findings. For recognition by the antibody, the Trp-rich loop flipped out, mimicking the mechanism of membrane insertion. The displaced second Trp was seen to establish aromatic stacking interactions with aromatic residues of the antibody paratope and the notably extruded guanidium tip of the arginine residue mediated electrostatic interactions with well-exposed carboxylic groups of glutamic residues on the surface of the paratope. Thus, the epitope/paratope interaction is mainly mediated by aromatic and by ionic interactions.     

Conformational B-Cell Epitope Prediction on Antigen Protein Structures: A Review of Current Algorithms and Comparison with Common Binding Site Prediction Methods

Accurate prediction of B-cell antigenic epitopes is important for immunologic research and medical applications, but compared with other bioinformatic problems, antigenic epitope prediction is more challenging because of the extreme variability of antigenic epitopes, where the paratope on the antibody binds specifically to a given epitope with high precision. In spite of the continuing efforts in the past decade, the problem remains unsolved and therefore still attracts a lot of attention from bioinformaticists. Recently, several discontinuous epitope prediction servers became available, and it is intriguing to review all existing methods and evaluate their performances on the same benchmark. In addition, these methods are also compared against common binding site prediction algorithms, since they have been frequently used as substitutes in the absence of good epitope prediction methods.     

Prediction of peptide reactivity with human IVIg through a knowledge-based approach

The prediction of antibody-protein (antigen) interactions is very difficult due to the huge variability that characterizes the structure of the antibodies. The region of the antigen bound to the antibodies is called epitope. Experimental data indicate that many antibodies react with a panel of distinct epitopes (positive reaction). The Challenge 1 of DREAM5 aims at understanding whether there exists rules for predicting the reactivity of a peptide/epitope, i.e., its capability to bind to human antibodies. DREAM 5 provided a training set of peptides with experimentally identified high and low reactivities to human antibodies. On the basis of this training set, the participants to the challenge were asked to develop a predictive model of reactivity. A test set was then provided to evaluate the performance of the model implemented so far.We developed a logistic regression model to predict the peptide reactivity, by facing the challenge as a machine learning problem. The initial features have been generated on the basis of the available knowledge and the information reported in the dataset. Our predictive model had the second best performance of the challenge. We also developed a method, based on a clustering approach, able to "in-silico" generate a list of positive and negative new peptide sequences, as requested by the DREAM5 "bonus round" additional challenge.The paper describes the developed model and its results in terms of reactivity prediction, and highlights some open issues concerning the propensity of a peptide to react with human antibodies.     

The concept and operational definition of protein epitopes

The antigenic determinants or epitopes of a protein correspond to those parts of the molecule that are specifically recognized by the binding sites or paratopes of certain immunoglobulin molecules. Epitopes are thus relational entities that require complementary paratopes for their operational recognition. Some authors consider that the concept of epitope necessarily involves the two properties of antigenic reactivity (ability to bind to a paratope) and immunogenicity (ability to induce an immune response). Such a view creates difficulties because it makes the existence of epitopes in a protein depend on immunogenetic and regulatory mechanisms of the immunized host. The delineation of epitopes can be achieved by antigenic cross-reactivity studies or by X-ray crystallography. Both approaches require specific criteria for deciding which residues of the antigen are in contact with the paratope and are functionally part of the epitope. The relative contribution of static accessibility, segmental mobility and induced fit to immune recognition remains controversial. Each of the methods used for analysing antigenic specificity is subject to various operational constraints originating from the type of experimental probe and from the format sensitivity and specificity of the immunoassay used. If a protein is assumed to contain as many epitopes as the number of different monoclonal antibodies that can be raised against it, the delineation of epitopes corresponds to the summation in various hosts of the immune repertoire specific for the antigen. Neutralization epitopes are a special subclass of the epitopes of infectious agents and toxins that are specifically recognized by antibody molecules able to neutralize the biological activity of the antigen. The identification of neutralization epitopes is important for the development of synthetic vaccines because it is this type of epitope that should be mimicked by synthesis and used as a vaccine for eliciting protective immunity. The first demonstration that synthetic peptides could elicit antibodies that neutralized viral infectivity was made by Anderer and his colleagues in the 1960s in their work with tobacco mosaic virus. Nearly 20 years passed before it was shown that antibodies to synthetic peptides were also able to neutralize the infectivity of other viruses such as foot-and-mouth disease, polio and hepatitis B viruses.     

Stepwise prediction of conformational discontinuous B-cell epitopes using the Mapitope algorithm

Mapping the epitope of an antibody is of great interest, since it contributes much to our understanding of the mechanisms of molecular recognition and provides the basis for rational vaccine design. Here we present Mapitope, a computer algorithm for epitope mapping. The algorithm input is a set of affinity isolated peptides obtained by screening phage display peptide-libraries with the antibody of interest. The output is usually 1-3 epitope candidates on the surface of the atomic structure of the antigen. We have systematically tested the performance of Mapitope by assessing the effect of the algorithm parameters on the final prediction. Thus, we have examined the effect of the statistical threshold (ST) parameter, relating to the frequency distribution and enrichment of amino acid pairs from the isolated peptides and the D (distance) and E (exposure) parameters which relate to the physical parameters of the antigen. Two model systems were analyzed in which the antibody of interest had previously been co-crystallized with the antigen and thus the epitope is a given. The Mapitope algorithm successfully predicted the epitopes in both models. Accordingly, we formulated a stepwise paradigm for the prediction of discontinuous conformational epitopes using peptides obtained from screening phage display libraries. We applied this paradigm to successfully predict the epitope of the Trastuzumab antibody on the surface of the Her-2/neu receptor in a third model system.     

Prediction of residues in discontinuous B-cell epitopes using protein 3D structures

Discovery of discontinuous B-cell epitopes is a major challenge in vaccine design. Previous epitope prediction methods have mostly been based on protein sequences and are not very effective. Here, we present DiscoTope, a novel method for discontinuous epitope prediction that uses protein three-dimensional structural data. The method is based on amino acid statistics, spatial information, and surface accessibility in a compiled data set of discontinuous epitopes determined by X-ray crystallography of antibody/antigen protein complexes. DiscoTope is the first method to focus explicitly on discontinuous epitopes. We show that the new structure-based method has a better performance for predicting residues of discontinuous epitopes than methods based solely on sequence information, and that it can successfully predict epitope residues that have been identified by different techniques. DiscoTope detects 15.5% of residues located in discontinuous epitopes with a specificity of 95%. At this level of specificity, the conventional Parker hydrophilicity scale for predicting linear B-cell epitopes identifies only 11.0% of residues located in discontinuous epitopes. Predictions by the DiscoTope method can guide experimental epitope mapping in both rational vaccine design and development of diagnostic tools, and may lead to more efficient epitope identification.     

B细胞表位作图研究进展

抗原-抗体的特异性结合是由抗体表面的抗原决定簇与抗原表面的表位基序间的特异性互补识别决定的。B细胞表位作图既包括B细胞抗原表位基序的鉴定(即确定抗原分子上被B细胞表面受体或抗体特异性识别并结合的氨基酸基序),也包括绘制抗原蛋白的全部或接近全部的B细胞表位基序在其一级或高级结构上的分布图谱的过程。B细胞表位作图是研发表位疫苗、治疗性表位抗体药物和建立疾病免疫诊断方法的重要前提。目前,已经建立了多种B细胞表位鉴定或绘制抗原蛋白B细胞表位图谱的实验方法。基于抗原-单抗复合物晶体结构的X-射线晶体学分析的B细胞表位作图和基于抗原蛋白或抗原片段的突变体库筛选技术的B细胞表位作图可以在氨基酸水平,甚至原子水平上揭示抗原分子上与单抗特异性结合的关键基序;其它B细胞表位作图方法(如基于ELISA的肽库筛选技术)常常只能获得包含B细胞表位的抗原性肽段,因而,很少用于最小表位基序的鉴定;而改良的生物合成肽法多用于B细胞表位的最小基序鉴定和精细作图。鉴于每种B细胞作图方法都存在各自的优势与不足,B细胞表位作图往往需要多种作图方法的有机结合。本文对目前常用的B细胞表位作图的实验方法及其在动物疫病防控中的应用进行综述,以期为研究者设计最佳的表位作图方案提供参考。     

Determination of protein-derived epitopes by mass spectrometry

Mass spectrometry has evolved as a technique suitable for the characterization of peptides and proteins beyond their linear sequence. The advantages of mass spectrometric sample analysis are high sensitivity, high mass accuracy, rapid analysis time and low sample consumption. In epitope mapping, the molecular structure of an antigen (the epitope or antigenic determinant) that interacts with the paratope (recognition surface) of the antibody is identified. To obtain information on linear, conformational and/or discontinuous epitopes, various approaches have been developed in conjunction with mass spectrometry. These methods include limited proteolysis and epitope footprinting, epitope excision and epitope extraction for linear epitopes and probing the surface accessibility of residues by differential chemical modifications of specific amino acid side chains or by differential hydrogen/deuterium exchange of the protein backbone amides for conformational and discontinuous epitopes. Epitope mapping by mass spectrometry is applicable in basic biochemical research and, with increasing robustness, should soon find its implementation in routine clinical diagnosis.     

Structural consensus among antibodies defines the antigen binding site

The Complementarity Determining Regions (CDRs) of antibodies are assumed to account for the antigen recognition and binding and thus to contain also the antigen binding site. CDRs are typically discerned by searching for regions that are most different, in sequence or in structure, between different antibodies. Here, we show that ~20% of the antibody residues that actually bind the antigen fall outside the CDRs. However, virtually all antigen binding residues lie in regions of structural consensus across antibodies. Furthermore, we show that these regions of structural consensus which cover the antigen binding site are identifiable from the sequence of the antibody. Analyzing the predicted contribution of antigen binding residues to the stability of the antibody-antigen complex, we show that residues that fall outside of the traditionally defined CDRs are at least as important to antigen binding as residues within the CDRs, and in some cases, they are even more important energetically. Furthermore, antigen binding residues that fall outside of the structural consensus regions but within traditionally defined CDRs show a marginal energetic contribution to antigen binding. These findings allow for systematic and comprehensive identification of antigen binding sites, which can improve the understanding of antigenic interactions and may be useful in antibody engineering and B-cell epitope identification.     

The mapping and reconstitution of a conformational discontinuous B-cell epitope of HIV-1

A method for the discovery of the structure of conformational discontinuous epitopes of monoclonal antibodies (mAbs) is described. The mAb is used to select specific phages from combinatorial phage-display peptide libraries that in turn are used as an epitope-defining database that is applied via a novel computer algorithm to analyze the crystalline structure of the original antigen. The algorithm is based on the following: (1) Most contacts between a mAb and an antigen are through side-chain atoms of the residues. (2) In the three-dimensional structure of a protein, amino acid residues remote in linear sequence can juxtapose to one another through folding. (3) Tandem amino acid residues of the selected phage-displayed peptides can represent pairs of juxtaposed amino acid residues of the antigen. (4) Contact residues of the epitope are accessible to the antigen surface. (5) The most frequent tandem pairs of amino acid residues in the selected phage-displayed peptides can reflect pairs of juxtaposed amino acid residues of the epitope. Application of the algorithm enabled prediction of epitopes. On the basis of these predictions, segments of an antigen were used to reconstitute an antigenic epitope mimetic that was recognized by its original mAb.