An Introduction to Epitope Mapping

Identification of a conserved B-cell epitope on the capsid protein of porcine circovirus type 4

Porcine circovirus type 4 (PCV4), a recently identified circovirus, is prevalent in numerous provinces in China, as well as in South Korea, Thailand, and Europe. PCV4 virus rescued from an infectious clone showed pathogenicity, suggesting the economic impact of PCV4. However, there remains a lack of understanding regarding the immunogenicity and epitopes of PCV4. This study generated a monoclonal antibody (MAb) 1D8 by immunizing mice with PCV4 virus-like particles (VLPs). Subsequently, the epitope recognized by the MAb 1D8 was identified by truncated protein expression and alanine scanning mutagenesis analysis. Results showed that the 225PKQG228 located at the C-terminus of the PCV4 Cap protein is the minimal motif binding to the MAb. Homology modeling analysis and immunoelectron microscopy revealed that the epitope extends beyond the outer surface of the PCV4 VLP. Moreover, the epitope is highly conserved among PCV4 strains and does not react with other PCVs. Together, the MAb 1D8 recognized epitope shows potential for detecting PCV4. These findings significantly contribute to the design of antigens for PCV4 detection and control strategies.

IMPORTANCE

Porcine circovirus type 4 (PCV4) is a novel circovirus. Although PCV4 has been identified in several countries, including China, Korea, Thailand, and Spain, no vaccine is available. Given the potential pathogenic effects of PCV4 on pigs, PCV4 could threaten the global pig farming industry, highlighting the urgency for further investigation. Thus, epitopes of PCV4 remain to be determined. Our finding of a conserved epitope significantly advances vaccine development and pathogen detection.

Analysis of Virus-Specific B Cell Epitopes Reveals Extensive Antigen Degradation Prior to Recognition

B cell epitopes must be visible for recognition by cognate B cells and/or antibodies. Here, we studied that premise for known linear B cell epitopes that were collected from the Immune Epitope Database as being recognized by humans during microbial infections. We found that the majority of such known B cell epitopes are virus-specific linear B cell epitopes (87.96%), and most are located in antigens that remain enclosed in host cells and/or virus particles, preventing antibody recognition (18,832 out of 29,225 epitopes). Moreover, we estimated that only a minority (32.72%) of the virus-specific linear B cell epitopes that are found in exposed viral regions (e.g., the ectodomains of envelope proteins) are solvent accessible on intact antigens. Hence, we conclude that ample degradation/processing of viral particles and/or infected cells must occur prior to B cell recognition, thus shaping the B cell epitope repertoire.

Rapid and cost-effective epitope mapping using PURE ribosome display coupled with next-generation sequencing and bioinformatics

A novel, efficient and cost-effective approach for epitope identification of an antibody has been developed using a ribosome display platform. This platform, known as PURE ribosome display, utilizes an Escherichia coli-based reconstituted cell-free protein synthesis system (PURE system). It stabilizes the mRNA-ribosome-peptide complex via a ribosome-arrest peptide sequence. This system was complemented by next-generation sequencing (NGS) and an algorithm for analyzing binding epitopes. To showcase the effectiveness of this method, selection conditions were refined using the anti-PA tag monoclonal antibody with the PA tag peptide as a model. Subsequently, a random peptide library was constructed using 10 NNK triplet oligonucleotides via the PURE ribosome display. The resulting random peptide library-ribosome-mRNA complex was selected using a commercially available anti-HA (YPYDVPDYA) tag monoclonal antibody, followed by NGS and bioinformatic analysis. Our approach successfully identified the DVPDY sequence as an epitope within the hemagglutinin amino acid sequence, which was then experimentally validated. This platform provided a valuable tool for investigating continuous epitopes in antibodies.

Unleashing the power of antibodies: Engineering for tomorrow's therapy

Antibodies play a crucial role in host defense against various diseases. Antibody engineering is a multidisciplinary field that seeks to improve the quality of life of humans. In the context of disease, antibodies are highly specialized proteins that form a critical line of defense against pathogens and the disease caused by them. These infections trigger the innate arm of immunity by presenting on antigen-presenting cells such as dendritic cells. This ultimately links to the adaptive arm, where antibody production and maturation occur against that particular antigen. Upon binding with their specific antigens, antibodies trigger various immune responses to eliminate pathogens in a process called complement-dependent cytotoxicity and phagocytosis of invading microorganisms by immune cells or induce antibody-dependent cellular cytotoxicity is done by antibodies. These engineered antibodies are being used for various purposes, such as therapeutics, diagnostics, and biotechnology research. Cutting-edge techniques that include hybridoma technology, transgenic mice, display techniques like phage, yeast and ribosome displays, and next-generation sequencing are ways to engineer antibodies and mass production for the use of humankind. Considering the importance of antibodies in protecting from a diverse array of pathogens, investing in research holds great promise to develop future therapeutic targets to combat various diseases.

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost intensive. Computational methods have potential to accelerate epitope predictions, however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologs. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2 Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis alone each proved ineffectual in differentiating between two putative binding models referred to as parallel and perpendicular. However, our integrated approach based on dynamic network analysis showed that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols including cross linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Our research highlights the potential of deploying dynamic network analysis to refine AI-based structure predictions for precise predictions of protein-protein interaction interfaces.

T and B cell epitope analysis for the immunogenicity evaluation and mitigation of antibody-based therapeutics

The surge in the clinical use of therapeutic antibodies has reshaped the landscape of pharmaceutical therapy for many diseases, including rare and challenging conditions. However, the administration of exogenous biologics could potentially trigger unwanted immune responses such as generation of anti-drug antibodies (ADAs). Real-world experiences have illuminated the clear correlation between the ADA occurrence and unsatisfactory therapeutic outcomes as well as immune-related adverse events. By retrospectively examining research involving immunogenicity analysis, we noticed the growing emphasis on elucidating the immunogenic epitope profiles of antibody-based therapeutics aiming for mechanistic understanding the immunogenicity generation and, ideally, mitigating the risks. As such, we have comprehensively summarized here the progress in both experimental and computational methodologies for the characterization of T and B cell epitopes of therapeutics. Furthermore, the successful practice of epitope-driven deimmunization of biotherapeutics is exceptionally highlighted in this article.

Multi-perspectives and challenges in identifying B-cell epitopes

The identification of B-cell epitopes (BCEs) in antigens is a crucial step in developing recombinant vaccines or immunotherapies for various diseases. Over the past four decades, numerous in silico methods have been developed for predicting BCEs. However, existing reviews have only covered specific aspects, such as the progress in predicting conformational or linear BCEs. Therefore, in this paper, we have undertaken a systematic approach to provide a comprehensive review covering all aspects associated with the identification of BCEs. First, we have covered the experimental techniques developed over the years for identifying linear and conformational epitopes, including the limitations and challenges associated with these techniques. Second, we have briefly described the historical perspectives and resources that maintain experimentally validated information on BCEs. Third, we have extensively reviewed the computational methods developed for predicting conformational BCEs from the structure of the antigen, as well as the methods for predicting conformational epitopes from the sequence. Fourth, we have systematically reviewed the in silico methods developed in the last four decades for predicting linear or continuous BCEs. Finally, we have discussed the overall challenge of identifying continuous or conformational BCEs. In this review, we only listed major computational resources; a complete list with the URL is available from the BCinfo website (https://webs.iiitd.edu.in/raghava/bcinfo/).

Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind to the same epitope

The function of an antibody is intrinsically linked to the epitope it engages. Clonal clustering methods, based on sequence identity, are commonly used to group antibodies that will bind to the same epitope. However, such methods neglect the fact that antibodies with highly diverse sequences can exhibit similar binding site geometries and engage common epitopes. In a previous study, we described SPACE1, a method that structurally clustered antibodies in order to predict their epitopes. This methodology was limited by the inaccuracies and incomplete coverage of template-based modeling. In addition, it was only benchmarked at the level of domain-consistency on one virus class. Here, we present SPACE2, which uses the latest machine learning-based structure prediction technology combined with a novel clustering protocol, and benchmark it on binding data that have epitope-level resolution. On six diverse sets of antigen-specific antibodies, we demonstrate that SPACE2 accurately clusters antibodies that engage common epitopes and achieves far higher dataset coverage than clonal clustering and SPACE1. Furthermore, we show that the functionally consistent structural clusters identified by SPACE2 are even more diverse in sequence, genetic lineage, and species origin than those found by SPACE1. These results reiterate that structural data improve our ability to identify antibodies that bind to the same epitope, adding information to sequence-based methods, especially in datasets of antibodies from diverse sources. SPACE2 is openly available on GitHub (https://github.com/oxpig/SPACE2).

Mapping antibody footprints using binding profiles

The increasing use of monoclonal antibodies (mAbs) in biology and medicine necessitates efficient methods for characterizing their binding epitopes. Here, we developed a high-throughput antibody footprinting method based on binding profiles. We used an antigen microarray to profile 23 human anti-influenza hemagglutinin (HA) mAbs using HA proteins of 43 human influenza strains isolated between 1918 and 2018. We showed that the mAb's binding profile can be used to characterize its influenza subtype specificity, binding region, and binding site. We present mAb-Patch-an epitope prediction method that is based on a mAb's binding profile and the 3D structure of its antigen. mAb-Patch was evaluated using four mAbs with known solved mAb-HA structures. mAb-Patch identifies over 67% of the true epitope when considering only 50-60 positions along the antigen. Our work provides proof of concept for utilizing antibody binding profiles to screen large panels of mAbs and to down-select antibodies for further functional studies.

Molecular insights into recognition of GUCY2C by T-cell engaging bispecific antibody anti-GUCY2CxCD3

The intestinal epithelial receptor Guanylyl Cyclase C (GUCY2C) is a tumor-associated cell surface antigen expressed across gastrointestinal malignancies that can serve as an efficacious target for colorectal cancer immunotherapy. Here, we describe a yeast surface-display approach combined with an orthogonal peptide-based mapping strategy to identify the GUCY2C binding epitope of a novel anti-GUCY2CxCD3 bispecific antibody (BsAb) that recently advanced into the clinic for the treatment of cancer. The target epitope was localized to the N-terminal helix H2 of human GUCY2C, which enabled the determination of the crystal structure of the minimal GUCY2C epitope in complex with the anti-GUCY2C antibody domain. To understand if this minimal epitope covers the entire antibody binding region and to investigate the impact of epitope position on the antibody's activity, we further determined the structure of this interaction in the context of the full-length extracellular domain (ECD) of GUCY2C. We found that this epitope is positioned on the protruding membrane-distal helical region of GUCY2C and that its specific location on the surface of GUCY2C dictates the close spatial proximity of the two antigen arms in a diabody arrangement essential to the tumor killing activity of GUCY2CxCD3 BsAb.

Identification of Potential Novel B-Cell Epitopes of Capsid Protein VP2 in Senecavirus A

Senecavirus A (SVA) is a type of nonenveloped single-stranded, positive-sense RNA virus. The VP2 protein is a structural protein that plays an important role in inducing early and late immune responses of the host. However, its antigenic epitopes have not been fully elucidated. Therefore, defining the B epitopes of the VP2 protein is of great importance to revealing its antigenic characterization. In this study, we analyzed B-cell immunodominant epitopes (IDEs) of the VP2 protein from the SVA strain CH/FJ/2017 using the Pepscan approach and a bioinformatics-based computational prediction method. The following four novel IDEs of VP2 were identified: IDE1, 41TKSDPPSSSTDQPTTT56; IDE2, 145PDGKAKSLQELNEEQW160; IDE3, 161VEMSDDYRTGKNMPF175; and IDE4, 267PYFNGLRNRFTTGT280. Most of the IDEs were highly conserved among the different strains. To our knowledge, the VP2 protein is a major protective antigen of SVA that can induce neutralizing antibodies in animals. Here, we analyzed the immunogenicity and neutralization activity of four IDEs of VP2. Consequently, all four IDEs showed good immunogenicity that could elicit specific antibodies in guinea pigs. A neutralization test in vitro showed that the peptide-specific guinea pig antisera of IDE2 could neutralize SVA strain CH/FJ/2017, and IDE2 was identified as a novel potential neutralizing linear epitope. This is the first time VP2 IDEs have been identified by using the Pepscan method and a bioinformatics-based computational prediction method. These results will help elucidate the antigenic epitopes of VP2 and clarify the basis for immune responses against SVA. IMPORTANCE The clinical symptoms and lesions caused by SVA are indistinguishable from those of other vesicular diseases in pigs. SVA has been associated with recent outbreaks of vesicular disease and epidemic transient neonatal losses in several swine-producing countries. Due to the continuing spread of SVA and the lack of commercial vaccines, the development of improved control strategies is urgently needed. The VP2 protein is a crucial antigen on the capsids of SVA particles. Furthermore, the latest research showed that VP2 could be a promising candidate for the development of novel vaccines and diagnostic tools. Hence, a detailed exploration of epitopes in the VP2 protein is necessary. In this study, four novel B-cell IDEs were identified using two different antisera with two different methods. IDE2 was identified as a new neutralizing linear epitope. Our findings will help in the rational design of epitope vaccines and further understanding of the antigenic structure of VP2.

Determination of Binding Sites on Trastuzumab and Pertuzumab to Selective Affimers Using Hydrogen-Deuterium Exchange Mass Spectrometry

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is a method to probe the solvent accessibility and conformational dynamics of a protein or a protein-ligand complex with respect to exchangeable amide hydrogens. Here, we present the application of HDX-MS to determine the binding sites of Affimer reagents to the monoclonal antibodies trastuzumab and pertuzumab, respectively. Intact and subunit level HDX-MS analysis of antibody-affimer complexes showed significant protection from HDX in the antibody Fab region upon affimer binding. Bottom-up HDX-MS experiments including online pepsin digestion revealed that the binding sites of the affimer reagents were mainly located in the complementarity-determining region (CDR) 2 of the heavy chain of the respective antibodies. Three-dimensional models of the binding interaction between the affimer reagents and the antibodies were built by homology modeling and molecular docking based on the HDX data.

A modified ELISA assay differentiates CCL20 locked dimers from wild-type monomers

A novel engineered CCL20 locked dimer (CCL20LD) is nearly identical to the naturally occurring chemokine CCL20 but blocks CCR6-mediated chemotaxis and offers a new approach to treat the diseases of psoriasis and psoriatic arthritis. Methods for quantifying CCL20LD serum levels are needed to assess pharmacokinetics parameters and evaluate drug delivery, metabolism, and toxicity. Existing ELISA kits fail to discriminate between CCL20LD and the natural chemokine, CCL20WT (the wild type monomer). Herein, we tested several available CCL20 monoclonal antibodies to be able to identify one clone that can be used both as a capture and a detection antibody (with biotin-labeling) to specifically detect CCL20LD with high specificity. After validation using recombinant proteins, the CCL20LD-selective ELISA was used to analyze blood samples from CCL20LD treated mice, demonstrating the utility of this novel assay for preclinical development of a biopharmaceutical lead compound for psoriatic disease.

Immunoanalytical Approach for Detecting and Identifying Ancestral Peptide Biomarkers in Early Earth Analogue Environments

Several mass spectrometry and spectroscopic techniques have been used in the search for molecular biomarkers on Mars. A major constraint is their capability to detect and identify large and complex compounds such as peptides or other biopolymers. Multiplex immunoassays can detect these compounds, but antibodies must be produced for a large number of sequence-dependent molecular targets. Ancestral Sequence Reconstruction (ASR) followed by protein "resurrection" in the lab can help to narrow the selection of targets. Herein, we propose an immunoanalytical method to identify ancient and universally conserved protein/peptide sequences as targets for identifying ancestral biomarkers in nature. We have developed, tested, and validated this approach by producing antibodies to eight previously described ancestral resurrected proteins (three β-lactamases, three thioredoxins, one Elongation Factor Tu, and one RuBisCO, all of them theoretically dated as Precambrian), and used them as a proxy to search for any potential feature of them that could be present in current natural environments. By fluorescent sandwich microarray immunoassays (FSMI), we have detected positive immunoreactions with antibodies to the oldest β-lactamase and thioredoxin proteins (ca. 4 Ga) in samples from a hydrothermal environment. Fine epitope mapping and inhibitory immunoassays allowed the identification of well-conserved epitope peptide sequences that resulted from ASR and were present in the sample. We corroborated these results by metagenomic sequencing and found several genes encoding analogue proteins with significant matches to the peptide epitopes identified with the antibodies. The results demonstrated that peptides inferred from ASR studies have true counterpart analogues in Nature, which validates and strengthens the well-known ASR/protein resurrection technique and our immunoanalytical approach for investigating ancient environments and metabolisms on Earth and elsewhere.

A high-throughput single-particle imaging platform for antibody characterization and a novel competition assay for therapeutic antibodies

Monoclonal antibodies (mAbs) play an important role in diagnostics and therapy of infectious diseases. Here we utilize a single-particle interferometric reflectance imaging sensor (SP-IRIS) for screening 30 mAbs against Ebola, Sudan, and Lassa viruses (EBOV, SUDV, and LASV) to find out the ideal capture antibodies for whole virus detection using recombinant vesicular stomatitis virus (rVSV) models expressing surface glycoproteins (GPs) of EBOV, SUDV, and LASV. We also make use of the binding properties on SP-IRIS to develop a model for mapping the antibody epitopes on the GP structure. mAbs that bind to mucin-like domain or glycan cap of the EBOV surface GP show the highest signal on SP-IRIS, followed by mAbs that target the GP1-GP2 interface at the base domain. These antibodies were shown to be highly efficacious against EBOV infection in non-human primates in previous studies. For LASV detection, 8.9F antibody showed the best performance on SP-IRIS. This antibody binds to a unique region on the surface GP compared to other 15 mAbs tested. In addition, we demonstrate a novel antibody competition assay using SP-IRIS and rVSV-EBOV models to reveal the competition between mAbs in three successful therapeutic mAb cocktails against EBOV infection. We provide an explanation as to why ZMapp cocktail has higher efficacy compared to the other two cocktails by showing that three mAbs in this cocktail (13C6, 2G4, 4G7) do not compete with each other for binding to EBOV GP. In fact, the binding of 13C6 enhances the binding of 2G4 and 4G7 antibodies. Our results establish SP-IRIS as a versatile tool that can provide high-throughput screening of mAbs, multiplexed and sensitive detection of viruses, and evaluation of therapeutic antibody cocktails.

Deciphering cross-species reactivity of LAMP-1 antibodies using deep mutational epitope mapping and AlphaFold

Delineating the precise regions on an antigen that are targeted by antibodies has become a key step for the development of antibody therapeutics. X-ray crystallography and cryogenic electron microscopy are considered the gold standard for providing precise information about these binding sites at atomic resolution. However, they are labor-intensive and a successful outcome is not guaranteed. We used deep mutational scanning (DMS) of the human LAMP-1 antigen displayed on yeast surface and leveraged next-generation sequencing to observe the effect of individual mutants on the binding of two LAMP-1 antibodies and to determine their functional epitopes on LAMP-1. Fine-tuned epitope mapping by DMS approaches is augmented by knowledge of experimental antigen structure. As human LAMP-1 structure has not yet been solved, we used the AlphaFold predicted structure of the full-length protein to combine with DMS data and ultimately finely map antibody epitopes. The accuracy of this method was confirmed by comparing the results to the co-crystal structure of one of the two antibodies with a LAMP-1 luminal domain. Finally, we used AlphaFold models of non-human LAMP-1 to understand the lack of mAb cross-reactivity. While both epitopes in the murine form exhibit multiple mutations in comparison to human LAMP-1, only one and two mutations in the Macaca form suffice to hinder the recognition by mAb B and A, respectively. Altogether, this study promotes a new application of AlphaFold to speed up precision mapping of antibody-antigen interactions and consequently accelerate antibody engineering for optimization.

Epitope mapping of neutralising anti-SARS-CoV-2 monoclonal antibodies: Implications for immunotherapy and vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the coronavirus disease 2019 (COVID-19) pandemic. This disease has currently affected more than 346 million people and resulted in more than 5.5 million deaths in many countries. Neutralising monoclonal antibodies (MAbs) against the SARS-CoV-2 virus could serve as prophylactic/therapeutic agents in COVID-19 infection by providing passive protection against the virus in individuals. Until now, no Food and Drug Administration/European Medicines Agency-approved neutralising MAb against SARS-CoV-2 virus exists in the market, though a number of MAbs have been authorised for emergency use. Therefore, there is an urgent need for development of efficient anti-SARS-CoV-2 neutralising MAbs for use in the clinic. Moreover, neutralising anti-SARS-CoV-2 MAbs could be used as beneficial tools for designing epitope-based vaccines against the virus. Given that the target epitope of a MAb is a crucial feature influencing its neutralising potency, target epitopes of neutralising anti-SARS-CoV-2 MAbs already reported in the literature and reactivity of these MAbs with SARS-CoV-2 variants are reviewed herein.

Computational epitope binning reveals functional equivalence of sequence-divergent paratopes

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Epitope binning groups target-specific protein binders recognizing the same binding region.

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The “Epibin” method utilizes docking models to computationally predict competition and identify bins.

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Epibin recapitulated binding competition of repebody variants as determined by immunoassays.

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In addition, Epibin enabled identification of ‘paratope-equivalent’ residues in sequence-dissimilar variants.

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Computational epitope binning can scale to allow characterization of entire antigen-specific antibody repertoires.

The therapeutic efficacy of a protein binder largely depends on two factors: its binding site and its binding affinity. Advances in in vitro library display screening and next-generation sequencing have enabled accelerated development of strong binders, yet identifying their binding sites still remains a major challenge. The differentiation, or “binning”, of binders into different groups that recognize distinct binding sites on their target is a promising approach that facilitates high-throughput screening of binders that may show different biological activity. Here we study the extent to which the information contained in the amino acid sequences comprising a set of target-specific binders can be leveraged to bin them, inferring functional equivalence of their binding regions, or paratopes, based directly on comparison of the sequences, their modeled structures, or their modeled interactions. Using a leucine-rich repeat binding scaffold known as a “repebody” as the source of diversity in recognition against interleukin-6 (IL-6), we show that the “Epibin” approach introduced here effectively utilized structural modelling and docking to extract specificity information encoded in the repebody amino acid sequences and thereby successfully recapitulate IL-6 binding competition observed in immunoassays. Furthermore, our computational binning provided a basis for designing in vitro mutagenesis experiments to pinpoint specificity-determining residues. Finally, we demonstrate that the Epibin approach can extend to antibodies, retrospectively comparing its predictions to results from antigen-specific antibody competition studies. The study thus demonstrates the utility of modeling structure and binding from the amino acid sequences of different binders against the same target, and paves the way for larger-scale binning and analysis of entire repertoires.

Immuno-Informatics Based Peptides: An Approach for Vaccine Development Against Outer Membrane Proteins of Pseudomonas Genus

Pseudomonas genus is among the top nosocomial pathogens known to date. Being highly opportunistic, members of pseudomonas genus are most commonly connected with nosocomial infections of urinary tract and ventilator-associated pneumonia. Nevertheless, vaccine development for this pathogenic genus is slow because of no information regarding immunity correlated functional mechanism. In this present work, an immunoinformatics pipeline is used for vaccine development based on epitope-based peptide design, which can result in crucial immune response against outer membrane proteins of pseudomonas genus. A total of 127 outer membrane proteins were analysed, studied and out of them three sequences were obtained to be the producer of non-allergic, highly antigenic T-cell and B-cell epitopes which show good binding affinity towards class II HLA molecules. After performing rigorous screening utilizing docking, simulation, modelling techniques, we had one nonameric peptide (WLLATGIFL)as a good vaccine candidate. The predicted epitopes needs to be further validated for its apt use as vaccine. This work paves a new way with extensive therapeutic application against Pseudomonas genus and their associated diseases.

Epitope mapping of anti-drug antibodies to a clinical candidate bispecific antibody

Anti-drug antibodies (ADA) can limit the efficacy and safety of therapeutic antibodies. However, determining the exact nature of ADA interactions with the target drug via epitope mapping is challenging due to the polyclonal nature of the IgG response. Here, we demonstrate successful proof-of-concept for the application of hydroxyl radical footprinting (HRF)-mass spectrometry for epitope mapping of ADAs obtained from goats that were administered a knob-into-hole bispecific antibody (BsAb1). Subsequently, we performed epitope mapping of ADAs obtained from cynomolgus (cyno) monkeys that were administered BsAb1 as we described in a recently published paper. Herein, we provide the first data to demonstrate the feasibility of using HRF for ADA epitope mapping, and show that both goat and cyno-derived ADAs specifically target the complementary-determining regions in both arms of BsAb1, suggesting that the ADA epitopes on BsAb1 may be species-independent.

The binding epitope of sintilimab on PD-1 revealed by AbMap

PD-1 plays an important role as an immune checkpoint. Sintilimab is a newly approved PD-1 antibody for cancer immunotherapy with an unknown binding epitope on PD-1. In this study, to elucidate the molecular mechanism by which sintilimab blocks PD-1 activation, we applied Antibody binding epitope Mapping (AbMap) to identify the binding epitope of sintilimab. An epitope was successfully identified, i.e. SLAPKA, aa 127-132. By constructing a series of point mutations, the dominant residues S127, L128, A129, P130, and A132 of PD-1 were further validated by western blot analysis, biolayer interferometry, and flow cytometry. Structural analysis showed that the epitope is partially within the binding interface of PD-1 and PD-L1, and this epitope also partially overlaps with that of nivolumab and pembrolizumab. These results demonstrate that sintilimab can attenuate PD-1 activation by directly competing with the interaction between PD-1 and PD-L1 through binding with the key residues of the FG loop on PD-1. This study also demonstrates the high efficiency and accuracy of AbMap for determining the binding epitope of therapeutic antibodies.

Defining the epitope of a blood-brain barrier crossing single domain antibody specific for the type 1 insulin-like growth factor receptor

Ligand-activated signaling through the type 1 insulin-like growth factor receptor (IGF1R) is implicated in many physiological processes ranging from normal human growth to cancer proliferation and metastasis. IGF1R has also emerged as a target for receptor-mediated transcytosis, a transport phenomenon that can be exploited to shuttle biotherapeutics across the blood–brain barrier (BBB). We employed differential hydrogen–deuterium exchange mass spectrometry (HDX-MS) and nuclear magnetic resonance (NMR) to characterize the interactions of the IGF1R ectodomain with a recently discovered BBB-crossing single-domain antibody (sdAb), VHH-IR5, in comparison with IGF-1 binding. HDX-MS confirmed that IGF-1 induced global conformational shifts in the L1/FnIII-1/-2 domains and α-CT helix of IGF1R. In contrast, the VHH-IR5 sdAb-mediated changes in conformational dynamics were limited to the α-CT helix and its immediate vicinity (L1 domain). High-resolution NMR spectroscopy titration data and linear peptide scanning demonstrated that VHH-IR5 has high-affinity binding interactions with a peptide sequence around the C-terminal region of the α-CT helix. Taken together, these results define a core linear epitope for VHH-IR5 within the α-CT helix, overlapping the IGF-1 binding site, and suggest a potential role for the α-CT helix in sdAb-mediated transcytosis.

Synthetic peptides to produce antivenoms against the Cys-rich toxins of arachnids

Scorpion and spider envenomation is treated with the appropriate antivenoms, prepared as described by Césaire Auguste Phisalix and Albert Calmette in 1894. Such treatment requires the acquisition and manipulation of arachnid venoms, both very complicated procedures. Most of the toxins in the venoms of spiders and scorpions are extremely stable cysteine-rich peptide neurotoxins. Many strategies have been developed to obtain synthetic immunogens to facilitate the production of antivenoms against these toxins. For example, whole peptide toxins can be synthesized by solid-phase peptide synthesis (SPPS). Also, epitopes of the toxins can be identified and after the chemical synthesis of these peptide epitopes by SPPS, they can be coupled to protein carriers to develop efficient immunogens. Moreover, multiple antigenic peptides with a polylysine core can be designed and synthesized. This review focuses on the strategies developed to obtain synthetic immunogens for the production of antivenoms against the toxic Cys-rich peptides of scorpions and spiders.

Physicochemical determinants of antibody-protein interactions

Antibodies are specialized proteins generated by immune system for high specificity and affinity binding to target antigens. Because of their essential roles in immune system, antibodies have been successfully developed and engineered as biopharmaceuticals for treatment of various diseases. Analysis of antibody-protein interactions is always required to get detailed information on effectivity of such antibody-based therapeutics. Although physicochemical rules cannot be generalized for every antibody-protein interaction, there are some features which should be taken into account during antibody development and engineering efforts. In this chapter, physicochemical analysis of antibody paratope-protein epitope interactions will be discussed to highlight important characteristics. First, paratope and non-paratope regions of antibodies will be described and important roles of these regions on binding and biophysical features of antibodies will be discussed. Then, general features of epitope regions of protein antigens will be introduced along with several computational/experimental tools to identify them. Lastly, a rising star of antibody biopharmaceuticals, nanobodies, will be described to show importance of next-generation antibody fragment based biopharmaceuticals in drug development.