Mapping the epitope of PD-L1 to the paratope of the antibody durvalumab using molecular dynamics simulation

OBJECTIVES

Durvalumab, a human monoclonal antibody that stops PD-L1 from attaching itself to CD80 and PD-1, was approved by the Food and Drug Administration for use in cancer therapy. An essential stage in antibody optimization is mapping paratope residues to epitope residues. In this study, our earlier computer-aided method based on molecular dynamics (MD) simulations was used to observe the paratope residues on durvalumab and their companions on PD-L1.

METHODS

The durvalumab/PD-L1 complex model was obtained from the Protein Data Bank and used in a rectangular box for solvation. On durvalumab, the paratope residues and their companions on PD-L1 were identified using MD simulations. The interface residues were ranked on the basis of their contributions to the binding of durvalumab and PD-L1 by assessing the stability of hydrogen bonds and salt bridges. This assessment was conducted using free and guided MD simulations.

RESULTS

Seventeen residues, including ASP26, GLU58, GLU60, ASP61, ARG113, ARG125, and THR127 on PD-L1 and H31ARG, H52LYS, H53GLN, H57GLU, H99GLU, H103PHE, H113ARG, L28ARG, L31SER, and L92TYR on durvalumab, were expected to be necessary for the binding of durvalumab to PD-L1. ASP26, ARG113, and ARG125 on PD-L1 were essential for its binding to PD-1. Eight residues (GLU60, ASP61, and THR127 on PD-L1 and L31SER, H99GLU, H53GLU, H31ARG, and H113ARG on durvalumab) were newly found, and two residues (LYS124 on PD-L1 and L94SER on durvalumab) proven nonessential for complexation, compared to the findings from the examined crystal structure.

CONCLUSIONS

The antithrombotic antibody of durvalumab's paratope may be effectively mapped to the PD-L1 epitope using the existing computer method. This information will help optimize durvalumab.

Impact of antibody architecture and paratope valency on effector functions of bispecific NKp30 x EGFR natural killer cell engagers

Natural killer (NK) cells emerged as a promising effector population that can be harnessed for anti-tumor therapy. In this work, we constructed NK cell engagers (NKCEs) based on NKp30-targeting single domain antibodies (sdAbs) that redirect the cytotoxic potential of NK cells toward epidermal growth factor receptor (EGFR)-expressing tumor cells. We investigated the impact of crucial parameters such as sdAb location, binding valencies, the targeted epitope on NKp30, and the overall antibody architecture on the redirection capacity. Our study exploited two NKp30-specific sdAbs, one of which binds a similar epitope on NKp30 as its natural ligand B7-H6, while the other sdAb addresses a non-competing epitope. For EGFR-positive tumor targeting, humanized antigen-binding domains of therapeutic antibody cetuximab were used. We demonstrate that NKCEs bivalently targeting EGFR and bivalently engaging NKp30 are superior to monovalent NKCEs in promoting NK cell-mediated tumor cell lysis and that the architecture of the NKCE can substantially influence killing capacities depending on the NKp30-targeting sdAb utilized. While having a pronounced impact on NK cell killing efficacy, the capabilities of triggering antibody-dependent cellular phagocytosis or complement-dependent cytotoxicity were not significantly affected comparing the bivalent IgG-like NKCEs with cetuximab. However, the fusion of sdAbs can have a slight impact on the NK cell release of immunomodulatory cytokines, as well as on the pharmacokinetic profile of the NKCE due to unfavorable spatial orientation within the molecule architecture. Ultimately, our findings reveal novel insights for the engineering of potent NKCEs triggering the NKp30 axis.

Antibody Binding Captures High Energy State of an Antigen: The Case of Nsp1 SARS-CoV-2 as Revealed by Hydrogen-Deuterium Exchange Mass Spectrometry

We describe an investigation using structural mass spectrometry (MS) of the impact of two antibodies, 15497 and 15498, binding the highly flexible SARS-CoV-2 Nsp1 protein. We determined the epitopes and paratopes involved in the antibody-protein interactions by using hydrogen-deuterium exchange MS (HDX-MS). Notably, the Fab (Fragment antigen binding) for antibody 15498 captured a high energy form of the antigen exhibiting significant conformational changes that added flexibility over most of the Nsp1 protein. The Fab for antibody 15497, however, showed usual antigen binding behavior, revealing local changes presumably including the binding site. These findings illustrate an unusual antibody effect on an antigen and are consistent with the dynamic nature of the Nsp1 protein. Our studies suggest that this interaction capitalizes on the high flexibility of Nsp1 to undergo conformational change and be trapped in a higher energy state by binding with a specific antibody.

Widespread impact of immunoglobulin V-gene allelic polymorphisms on antibody reactivity

The ability of the human immune system to generate antibodies to any given antigen can be strongly influenced by immunoglobulin V-gene allelic polymorphisms. However, previous studies have provided only limited examples. Therefore, the prevalence of this phenomenon has been unclear. By analyzing >1,000 publicly available antibody-antigen structures, we show that many V-gene allelic polymorphisms in antibody paratopes are determinants for antibody binding activity. Biolayer interferometry experiments further demonstrate that paratope allelic polymorphisms on both heavy and light chains often abolish antibody binding. We also illustrate the importance of minor V-gene allelic polymorphisms with low frequency in several broadly neutralizing antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus. Overall, this study not only highlights the pervasive impact of V-gene allelic polymorphisms on antibody binding but also provides mechanistic insights into the variability of antibody repertoires across individuals, which in turn have important implications for vaccine development and antibody discovery.

SARS-CoV-2 Spike Protein Interaction Space

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a +sense single-strand RNA virus. The virus has four major surface proteins: spike (S), envelope (E), membrane (M), and nucleocapsid (N), respectively. The constitutive proteins present a high grade of symmetry. Identifying a binding site is difficult. The virion is approximately 50-200 nm in diameter. Angiotensin-converting enzyme 2 (ACE2) acts as the cell receptor for the virus. SARS-CoV-2 has an increased affinity to human ACE2 compared with the original SAR strain. Topological space, and its symmetry, is a critical component in molecular interactions. By exploring this space, a suitable ligand space can be characterized accordingly. A spike protein (S) computational model in a complex with ACE 2 was generated using silica methods. Topological spaces were probed using high computational throughput screening techniques to identify and characterize the topological space of both SARS and SARS-CoV-2 spike protein and its ligand space. In order to identify the symmetry clusters, computational analysis techniques, together with statistical analysis, were utilized. The computations are based on crystallographic protein data bank PDB-based models of constitutive proteins. Cartesian coordinates of component atoms and some cluster maps were generated and analyzed. Dihedral angles were used in order to compute a topological receptor space. This computational study uses a multimodal representation of spike protein interactions with some fragment proteins. The chemical space of the receptors (a dimensional volume) suggests the relevance of the receptor as a drug target. The spike protein S of SARS and SARS-CoV-2 is analyzed and compared. The results suggest a mirror symmetry of SARS and SARS-CoV-2 spike proteins. The results show thatSARS-CoV-2 space is variable and has a distinct topology. In conclusion, surface proteins grant virion variability and symmetry in interactions with a potential complementary target (protein, antibody, ligand). The mirror symmetry of dihedral angle clusters determines a high specificity of the receptor space.

Specific attributes of the VL domain influence both the structure and structural variability of CDR-H3 through steric effects

Antibodies, through their ability to target virtually any epitope, play a key role in driving the adaptive immune response in jawed vertebrates. The binding domains of standard antibodies are their variable light (VL) and heavy (VH) domains, both of which present analogous complementarity-determining region (CDR) loops. It has long been known that the VH CDRs contribute more heavily to the antigen-binding surface (paratope), with the CDR-H3 loop providing a major modality for the generation of diverse paratopes. Here, we provide evidence for an additional role of the VL domain as a modulator of CDR-H3 structure, using a diverse set of antibody crystal structures and a large set of molecular dynamics simulations. We show that specific attributes of the VL domain such as subtypes, CDR canonical forms and genes can influence the structural diversity of the CDR-H3 loop, and provide a physical model for how this effect occurs through inter-loop contacts and packing of CDRs against each other. Our results indicate that the rigid minor loops fine-tune the structure of CDR-H3, thereby contributing to the generation of surfaces complementary to the vast number of possible epitope topologies, and provide insights into the interdependent nature of CDR conformations, an understanding of which is important for the rational antibody design process.

A comparison of the binding sites of antibodies and single-domain antibodies

Antibodies are the largest class of biotherapeutics. However, in recent years, single-domain antibodies have gained traction due to their smaller size and comparable binding affinity. Antibodies (Abs) and single-domain antibodies (sdAbs) differ in the structures of their binding sites: most significantly, single-domain antibodies lack a light chain and so have just three CDR loops. Given this inherent structural difference, it is important to understand whether Abs and sdAbs are distinguishable in how they engage a binding partner and thus, whether they are suited to different types of epitopes. In this study, we use non-redundant sequence and structural datasets to compare the paratopes, epitopes and antigen interactions of Abs and sdAbs. We demonstrate that even though sdAbs have smaller paratopes, they target epitopes of equal size to those targeted by Abs. To achieve this, the paratopes of sdAbs contribute more interactions per residue than the paratopes of Abs. Additionally, we find that conserved framework residues are of increased importance in the paratopes of sdAbs, suggesting that they include non-specific interactions to achieve comparable affinity. Furthermore, the epitopes of sdAbs are only marginally less accessible than those of Abs: we posit that this may be explained by differences in the orientation and compaction of sdAb and Ab CDR-H3 loops. Overall, our results have important implications for the engineering and humanization of sdAbs, as well as the selection of the best modality for targeting a particular epitope.

Unveiling CD59-Antibody Interactions to Design Paratope-Mimicking Peptides for Complement Modulation

CD59 is an abundant immuno-regulatory human protein that protects cells from damage by inhibiting the complement system. CD59 inhibits the assembly of the Membrane Attack Complex (MAC), the bactericidal pore-forming toxin of the innate immune system. In addition, several pathogenic viruses, including HIV-1, escape complement-mediated virolysis by incorporating this complement inhibitor in their own viral envelope. This makes human pathogenic viruses, such as HIV-1, not neutralised by the complement in human fluids. CD59 is also overexpressed in several cancer cells to resist the complement attack. Consistent with its importance as a therapeutical target, CD59-targeting antibodies have been proven to be successful in hindering HIV-1 growth and counteracting the effect of complement inhibition by specific cancer cells. In this work, we make use of bioinformatics and computational tools to identify CD59 interactions with blocking antibodies and to describe molecular details of the paratope-epitope interface. Based on this information, we design and produce paratope-mimicking bicyclic peptides able to target CD59. Our results set the basis for the development of antibody-mimicking small molecules targeting CD59 with potential therapeutic interest as complement activators.

Breaking barriers in antibody discovery: harnessing divergent species for accessing difficult and conserved drug targets

To exploit highly conserved and difficult drug targets, including multipass membrane proteins, monoclonal antibody discovery efforts increasingly rely on the advantages offered by divergent species such as rabbits, camelids, and chickens. Here, we provide an overview of antibody discovery technologies, analyze gaps in therapeutic antibodies that stem from the historic use of mice, and examine opportunities to exploit previously inaccessible targets through discovery now possible in alternate species. We summarize the clinical development of antibodies raised from divergent species, discussing how these animals enable robust immune responses against highly conserved binding sites and yield antibodies capable of penetrating functional pockets via long HCDR3 regions. We also discuss the value of pan-reactive molecules often produced by these hosts, and how these antibodies can be tested in accessible animal models, offering a faster path to clinical development.

Switching Heavy Chain Constant Domains Denatures the Paratope 3D Architecture of Influenza Monoclonal Antibodies

Several human monoclonal Abs for treating Influenza have been evaluated in clinical trials with limited success despite demonstrating superiority in preclinical animal models including mice. To conduct efficacy studies in mice, human monoclonal Abs are genetically engineered to contain mouse heavy chain constant domain to facilitate the engagement of Fc-receptors on mouse immune effector cells. Although studies have consistently reported discrepancies in Ab effectiveness following genetic engineering, the structural and mechanistic basis for these inconsistencies remain uncharacterized. Here, we use homology modeling to predict variable region (VR) analogous monoclonal Abs possessing human IgG1, mouse IgG1, and mouse IgG2a heavy chain constant domains. We then examine predicted 3D structures for variations in the spatial location and orientation of corresponding paratope amino acid residues. By structurally aligning crystal structures of Fabs in complex with hemagglutinin (HA), we show that corresponding paratope amino acid residues for VR-analogous human IgG1, mouse IgG1, and mouse IgG2a monoclonal Abs interact differentially with HA suggesting that their epitopes might not be identical. To demonstrate that variations in the paratope 3D fine architecture have implications for Ab specificity and effectiveness, we genetically engineered VR-analogous human IgG1, human IgG4, mouse IgG1, and mouse IgG2a monoclonal Abs and explored their specificity and effectiveness in protecting MDCK cells from infection by pandemic H1N1 and H3N2 Influenza viruses. We found that VR-analogous monoclonal Abs placed on mouse heavy chain constant domains were more efficacious at protecting MDCK cells from Influenza virus infection relative to those on human heavy chain constant domains. Interestingly, mouse but not human heavy chain constant domains increased target breadth in some monoclonal Abs. These data suggest that heavy chain constant domain sequences play a role in shaping Ab repertoires that go beyond class or sub-class differences in immune effector recruitment. This represents a facet of Ab biology that can potentially be exploited to improve the scope and utilization of current therapeutic or prophylactic candidates for influenza.

Research progress on unique paratope structure, antigen binding modes, and systematic mutagenesis strategies of single-domain antibodies

Single-domain antibodies (sdAbs) showed the incredible advantages of small molecular weight, excellent affinity, specificity, and stability compared with traditional IgG antibodies, so their potential in binding hidden antigen epitopes and hazard detection in food, agricultural and veterinary fields were gradually explored. Moreover, its low immunogenicity, easy-to-carry target drugs, and penetration of the blood-brain barrier have made sdAbs remarkable achievements in medical treatment, toxin neutralization, and medical imaging. With the continuous development and maturity of modern molecular biology, protein analysis software and database with different algorithms, and next-generation sequencing technology, the unique paratope structure and different antigen binding modes of sdAbs compared with traditional IgG antibodies have aroused the broad interests of researchers with the increased related studies. However, the corresponding related summaries are lacking and needed. Different antigens, especially hapten antigens, show distinct binding modes with sdAbs. So, in this paper, the unique paratope structure of sdAbs, different antigen binding cases, and the current maturation strategy of sdAbs were classified and summarized. We hope this review lays a theoretical foundation to elucidate the antigen-binding mechanism of sdAbs and broaden the further application of sdAbs.

Complexity of Viral Epitope Surfaces as Evasive Targets for Vaccines and Therapeutic Antibodies

The dynamic interplay between virus and host plays out across many interacting surfaces as virus and host evolve continually in response to one another. In particular, epitope-paratope interactions (EPIs) between viral antigen and host antibodies drive much of this evolutionary race. In this review, we describe a series of recent studies examining aspects of epitope complexity that go beyond two interacting protein surfaces as EPIs are typically understood. To structure our discussion, we present a framework for understanding epitope complexity as a spectrum along a series of axes, focusing primarily on 1) epitope biochemical complexity (e.g., epitopes involving N-glycans) and 2) antigen conformational/dynamic complexity (e.g., epitopes with differential properties depending on antigen state or fold-axis). We highlight additional epitope complexity factors including epitope tertiary/quaternary structure, which contribute to epistatic relationships between epitope residues within- or adjacent-to a given epitope, as well as epitope overlap resulting from polyclonal antibody responses, which is relevant when assessing antigenic pressure against a given epitope. Finally, we discuss how these different forms of epitope complexity can limit EPI analyses and therapeutic antibody development, as well as recent efforts to overcome these limitations.

Immune escape facilitation by mutations of epitope residues in RdRp of SARS-CoV-2

Mutations drive viral evolution and genome variability that causes viruses to escape host immunity and to develop drug resistance. SARS-CoV-2 has considerably higher mutation rate. SARS-CoV-2 possesses a RNA dependent RNA polymerase (RdRp) which helps to replicate its genome. The mutation P323L in RdRp is associated with the loss of a particular epitope (321-327) from this protein. We consider the effects of mutations in some of the epitope region including the naturally occurring mutation P323L on the structure of the epitope and their interface with paratope using all-atom molecular dynamics (MD) simulation studies. We observe that the mutations cause conformational changes in the epitope region by opening up the region associated with increase in the radius of gyration and intramolecular hydrogen bonds, making the region less accessible. Moreover, we study the conformational stability of the epitope region and epitope:paratope interface under the mutation from the fluctuations in the dihedral angles. We observe that the mutation renders the epitope and the epitope:paratope interface unstable compared to the corresponding wild type ones. Thus, the mutations may help in escaping antibody mediated immunity of the hostCommunicated by Ramaswamy H. Sarma.

In silico proof of principle of machine learning-based antibody design at unconstrained scale

Generative machine learning (ML) has been postulated to become a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing arbitrarily large numbers of antibody sequences for their most critical design parameters: paratope, epitope, affinity, and developability. To address this challenge, we leveraged a lattice-based antibody-antigen binding simulation framework, which incorporates a wide range of physiological antibody-binding parameters. The simulation framework enables the computation of synthetic antibody-antigen 3D-structures, and it functions as an oracle for unrestricted prospective evaluation and benchmarking of antibody design parameters of ML-generated antibody sequences. We found that a deep generative model, trained exclusively on antibody sequence (one dimensional: 1D) data can be used to design conformational (three dimensional: 3D) epitope-specific antibodies, matching, or exceeding the training dataset in affinity and developability parameter value variety. Furthermore, we established a lower threshold of sequence diversity necessary for high-accuracy generative antibody ML and demonstrated that this lower threshold also holds on experimental real-world data. Finally, we show that transfer learning enables the generation of high-affinity antibody sequences from low-N training data. Our work establishes a priori feasibility and the theoretical foundation of high-throughput ML-based mAb design.

Polyreactivity and polyspecificity in therapeutic antibody development: risk factors for failure in preclinical and clinical development campaigns

Antibody-based drugs, which now represent the dominant biologic therapeutic modality, are used to modulate disparate signaling pathways across diverse disease indications. One fundamental premise that has driven this therapeutic antibody revolution is the belief that each monoclonal antibody exhibits exquisitely specific binding to a single-drug target. Herein, we review emerging evidence in antibody off-target binding and relate current key findings to the risk of failure in therapeutic development. We further summarize the current state of understanding of structural mechanisms underpining the different phenomena that may drive polyreactivity and polyspecificity, and highlight current thinking on how de-risking studies may be best implemented in the screening triage. We conclude with a summary of what we believe to be key observations in the field to date, and a call for the wider antibody research community to work together to build the tools needed to maximize our understanding in this nascent area.

Antibody-mediated enzyme formation: Its legacy at age fifty-four

Antibody‐mediated enzyme formation is a phenomenon first described in 1968 and further studied by molecular Immunologists and Biochemists over the following five decades. The present review is made mainly by analyzing the 27 articles concerned with AMEF that appeared over the course of 47 years, commenting 16 original figures selected to be re‐printed in AMEF's Legacy. We, the reviewers, started by revisiting our own “insider's” experience of discovery, and followed by considering all results, our own and of members of other AMEF Labs. We had planned to conclude the review by correlating the various AMEF mutants to a detailed knowledge of the consensus betaGal structure. However, we became aware of several “robust” papers, published between 1989 and 2014, by authors outside of AMEF Labs. We familiarly called this surge: “The Second Wave” and adorned it with a doodle in Hokusai style. We were thrilled and happy to take them on board and properly examined their data. A team of this second wave had imagined unique uses for AMEF, and new doors to modern biotechnology. Another one had used AMEF as Tool and Marker to attain high levels of crystallography, solving puzzles of conformation, and ultimate structure. Together, they doubled our motivation to review AMEF. Serendipity gives us back the pleasure of finding, a treat at any age.

An Antigenic Space Framework for Understanding Antibody Escape of SARS-CoV-2 Variants

The evolution of mutations in SARS-CoV-2 at antigenic sites that impact neutralizing antibody responses in humans poses a risk to immunity developed through vaccination and natural infection. The highly successful RNA-based vaccines have enabled rapid vaccine updates that incorporate mutations from current variants of concern (VOCs). It is therefore important to anticipate future antigenic mutations as the virus navigates the heterogeneous global landscape of host immunity. Toward this goal, we survey epitope-paratope interfaces of anti-SARS-CoV-2 antibodies to map an antigenic space that captures the role of each spike protein residue within the polyclonal antibody response directed against the ACE2-receptor binding domain (RBD) or the N-terminal domain (NTD). In particular, the antigenic space map builds on recently published epitope definitions by annotating epitope overlap and orthogonality at the residue level. We employ the antigenic space map as a framework to understand how mutations on nine major variants contribute to each variant's evasion of neutralizing antibodies. Further, we identify constellations of mutations that span the orthogonal epitope regions of the RBD and NTD on the variants with the greatest antibody escape. Finally, we apply the antigenic space map to predict which regions of antigenic space-should they mutate-may be most likely to complementarily augment antibody evasion for the most evasive and transmissible VOCs.

Epitope-Paratope Interaction of a Neutralizing Human Anti-Hepatitis B Virus PreS1 Antibody That Recognizes the Receptor-Binding Motif

Hepatitis B virus (HBV) is a global health burden that causes acute and chronic hepatitis. To develop an HBV-neutralizing antibody that effectively prevents HBV infection, we previously generated a human anti-preS1 monoclonal antibody (1A8) that binds to genotypes A–D and validated its HBV-neutralizing activity in vitro. In the present study, we aimed to determine the fine epitope and paratope of 1A8 to understand the mechanism of HBV neutralization. We performed alanine-scanning mutagenesis on the preS1 (aa 19–34, genotype C) and the heavy (HCDR) and light (LCDR) chain complementarity-determining regions. The 1A8 recognized the three residues (Leu22, Gly23, and Phe25) within the highly conserved receptor-binding motif (NPLGFFP) of the preS1, while four CDR residues of 1A8 were critical in antigen binding. Structural analysis of the epitope–paratope interaction by molecular modeling revealed that Leu100 in the HCDR3, Ala50 in the HCDR2, and Tyr96 in the LCDR3 closely interacted with Leu22, Gly23, and Phe25 of the preS1. Additionally, we found that 1A8 also binds to the receptor-binding motif (NPLGFLP) of infrequently occurring HBV. The results suggest that 1A8 may broadly and effectively block HBV entry and thus have potential as a promising candidate for the prevention and treatment of HBV infection.

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo antibody and (neo-)epitope design. A fundamental premise for the predictability of antibody-antigen binding is the existence of paratope-epitope interaction motifs that are universally shared among antibody-antigen structures. In a dataset of non-redundant antibody-antigen structures, we identify structural interaction motifs, which together compose a commonly shared structure-based vocabulary of paratope-epitope interactions. We show that this vocabulary enables the machine learnability of antibody-antigen binding on the paratope-epitope level using generative machine learning. The vocabulary (1) is compact, less than 10⁴ motifs; (2) distinct from non-immune protein-protein interactions; and (3) mediates specific oligo- and polyreactive interactions between paratope-epitope pairs. Our work leverages combined structure- and sequence-based learning to demonstrate that machine-learning-driven predictive paratope and epitope engineering is feasible.

Antibodies validated for routinely processed tissues stain frozen sections unpredictably

Background: Antibody validation for tissue staining is required for reproducibility; criteria to ensure validity have been published recently. The majority of these recommendations imply the use of routinely processed (formalin-fixed, paraffin-embedded) tissue. Materials & methods: We applied to lightly fixed frozen sections a panel of 126 antibodies validated for formalin-fixed, paraffin-embedded tissue with extended criteria. Results: Less than 30% of the antibodies performed as expected with all fixations. 35% preferred one fixation over another, 13% gave nonspecific staining and 23% did not stain at all. Conclusion: Individual antibody variability of the paratope's fitness for the fixed antigen may be the cause. Revalidation of established antibody panels is required when they are applied to sections whose fixation and processing are different from the tissue where they were initially validated.

Ab-Ligity: identifying sequence-dissimilar antibodies that bind to the same epitope

Solving the structure of an antibody-antigen complex gives atomic level information of the interactions between an antibody and its antigen, but such structures are expensive and hard to obtain. Alternative experimental sources include epitope mapping and binning experiments, which can be used as a surrogate to identify key interacting residues. However, their resolution is usually not sufficient to identify if two antibodies have identical interactions. Computational approaches to this problem have so far been based on the premise that antibodies with similar sequences behave similarly. Such approaches will fail to identify sequence-distant antibodies that target the same epitope. Here, we present Ab-Ligity, a structure-based similarity measure tailored to antibody-antigen interfaces. Using predicted paratopes on model antibody structures, we assessed its ability to identify those antibodies that target highly similar epitopes. Most antibodies adopting similar binding modes can be identified from sequence similarity alone, using methods such as clonotyping. In the challenging subset of antibodies whose sequences differ significantly, Ab-Ligity is still able to predict antibodies that would bind to highly similar epitopes (precision of 0.95 and recall of 0.69). We compared Ab-Ligity's performance to an existing tool for comparing general protein interfaces, InterComp, and showed improved performance on antibody cases achieved in a substantially reduced time. These results suggest that Ab-Ligity will allow the identification of diverse (sequence-dissimilar) antibodies that bind to the same epitopes from large datasets such as immune repertoires. The tool is available at http://opig.stats.ox.ac.uk/resources.

A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-pertussis toxoid antibodies

Due to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However, current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies that can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.

Abbreviations: BCR: B-cell receptor; CDR: complementarity-determining region; PTx: pertussis toxoid

Reconstitution of an Anti-HER2 Antibody Paratope by Grafting Dual CDR-Derived Peptides onto a Small Protein Scaffold

Target-binding small proteins are promising alternatives to conventional monoclonal antibodies (mAbs), offering advantages in terms of tissue penetration and manufacturing costs. Recently, a design strategy to create small proteins called fluctuation-regulated affinity proteins (FLAPs) consisting of a structurally immobilized peptide from the complementarity-determining region (CDR) loops of mAbs (CDR-derived peptide) and a protein scaffold was developed. Because mAb paratopes are usually composed of multiple CDRs, FLAPs with multiple binding peptides may have an enhanced target-binding capability. Here, a strategy to create FLAPs bearing dual CDR-derived peptides (D-FLAPs) using the anti-human epithelial growth factor receptor type 2 (HER2) mAb trastuzumab as a basis is developed. Computationally selected CDR-derived peptides are first grafted onto two adjacent loops of the fibronectin type III domain (FN3) scaffold, yielding 80 D-FLAP candidates. After computational screening based on their similarity to the parental mAb with regard to the conformation of paratope residues, two candidates are selected. After further evaluation with ELISA, one D-FLAP with HYTTPP and GDGFYA peptides from CDR-L3 and CDR-H3 of the parental mAb, respectively, is found to bind HER2 with a dissociation constant of 58 nm. This method applies to various mAb drugs and allows the rational design of small protein alternatives.

De novo discovery of antibody drugs - great promise demands scrutiny

We live in an era of rapidly advancing computing capacity and algorithmic sophistication. "Big data" and "artificial intelligence"find progressively wider use in all spheres of human activity, including healthcare. A diverse array of computational technologies is being applied with increasing frequency to antibody drug research and development (R&D). Their successful applications are met with great interest due to the potential for accelerating and streamlining the antibody R&D process. While this excitement is very likely justified in the long term, it is less likely that the transition from the first use to routine practice will escape challenges that other new technologies had experienced before they began to blossom. This transition typically requires many cycles of iterative learning that rely on the deconstruction of the technology to understand its pitfalls and define vectors for optimization. The study by Vasquez et al. identifies a key obstacle to such learning: the lack of transparency regarding methodology in computational antibody design reports, which has the potential to mislead the community efforts.

IMGT® and 30 Years of Immunoinformatics Insight in Antibody V and C Domain Structure and Function

At the 10th Human Genome Mapping (HGM10) Workshop, in New Haven, for the first time, immunoglobulin (IG) or antibody and T cell receptor (TR) variable (V), diversity (D), joining (J), and constant (C) genes were officially recognized as 'genes', as were the conventional genes. Under these HGM auspices, IMGT®, the international ImMunoGeneTics information system®, was created in June 1989 at Montpellier (University of Montpellier and CNRS). The creation of IMGT® marked the birth of immunoinformatics, a new science, at the interface between immunogenetics and bioinformatics. The accuracy and the consistency between genes and alleles, sequences, and three-dimensional (3D) structures are based on the IMGT Scientific chart rules generated from the IMGT-ONTOLOGY axioms and concepts: IMGT standardized keywords (IDENTIFICATION), IMGT gene and allele nomenclature (CLASSIFICATION), IMGT standardized labels (DESCRIPTION), IMGT unique numbering and IMGT Collier de Perles (NUMEROTATION). These concepts provide IMGT® immunoinformatics insights for antibody V and C domain structure and function, used for the standardized description in IMGT® web resources, databases and tools, immune repertoires analysis, single cell and/or high-throughput sequencing (HTS, NGS), antibody humanization, and antibody engineering in relation with effector properties.

Antibody Specific B-Cell Epitope Predictions: Leveraging Information From Antibody-Antigen Protein Complexes

B-cells can neutralize pathogenic molecules by targeting them with extreme specificity using receptors secreted or expressed on their surface (antibodies). This is achieved via molecular interactions between the paratope (i.e., the antibody residues involved in the binding) and the interacting region (epitope) of its target molecule (antigen). Discerning the rules that define this specificity would have profound implications for our understanding of humoral immunogenicity and its applications. The aim of this work is to produce improved, antibody-specific epitope predictions by exploiting features derived from the antigens and their cognate antibodies structures, and combining them using statistical and machine learning algorithms. We have identified several geometric and physicochemical features that are correlated in interacting paratopes and epitopes, used them to develop a Monte Carlo algorithm to generate putative epitopes-paratope pairs, and train a machine-learning model to score them. We show that, by including the structural and physicochemical properties of the paratope, we improve the prediction of the target of a given B-cell receptor. Moreover, we demonstrate a gain in predictive power both in terms of identifying the cognate antigen target for a given antibody and the antibody target for a given antigen, exceeding the results of other available tools.

Anti-PD1 'SHR-1210' aberrantly targets pro-angiogenic receptors and this polyspecificity can be ablated by paratope refinement

Monoclonal anti-programmed cell death 1 (PD1) antibodies are successful cancer therapeutics, but it is not well understood why individual antibodies should have idiosyncratic side-effects. As the humanized antibody SHR-1210 causes capillary hemangioma in patients, a unique toxicity amongst anti-PD1 antibodies, we performed human receptor proteome screening to identify nonspecific interactions that might drive angiogenesis. This screen identified that SHR-1210 mediated aberrant, but highly selective, low affinity binding to human receptors such as vascular endothelial growth factor receptor 2 (VEGFR2), frizzled class receptor 5 and UL16 binding protein 2 (ULBP2). SHR-1210 was found to be a potent agonist of human VEGFR2, which may thereby drive hemangioma development via vascular endothelial cell activation. The v-domains of SHR-1210's progenitor murine monoclonal antibody 'Mab005' also exhibited off-target binding and agonism of VEGFR2, proving that the polyspecificity was mediated by the original mouse complementarity-determining regions (CDRs), and had survived the humanization process. Molecular remodelling of SHR-1210 by combinatorial CDR mutagenesis led to deimmunization, normalization of binding affinity to human and cynomolgus PD1, and increased potency in PD1/PD-L1 blockade. Importantly, CDR optimization also ablated all off-target binding, rendering the resulting antibodies fully PD1-specific. As the majority of changes to the paratope were found in the light chain CDRs, the germlining of this domain drove the ablation of off-target binding. The combination of receptor proteome screening and optimization of the antibody binding interface therefore succeeded in generating novel, higher-potency, specificity-enhanced therapeutic IgGs from a single, clinically sub-optimal progenitor. This study showed that highly-specific off-target binding events might be an under-appreciated phenomenon in therapeutic antibody development, but that these unwanted properties can be fully ameliorated by paratope refinement.

Indirect Microcontact Printing to Create Functional Patterns of Physisorbed Antibodies

Microcontact printing (µCP) is a practical and versatile approach to create nanostructured patterns of biomolecular probes, but it involves conformational changes on the patterned bioreceptors that often lead to a loss on the biological activity of the resulting structures. Herein we introduce indirect µCP to create functional patterns of bioreceptors on solid substrates. This is a simple strategy that relies on physisorbing biomolecular probes of interest in the nanostructured gaps that result after patterning backfilling agents by standard µCP. This study presents the approach, assesses bovine serum albumin as backfilling agent for indirect µCP on different materials, reports the limitations of standard µCP on the functionality of patterned antibodies, and demonstrates the capabilities of indirect µCP to solve this issue. Bioreceptors were herein structured as diffractive gratings and used to measure biorecognition events in label-free conditions. Besides, as a preliminary approach towards sensing biomarkers, this work also reports the implementation of indirect µCP in an immunoassay to detect human immunoglobulin E.

Antigen recognition by single-domain antibodies: structural latitudes and constraints

Single-domain antibodies (sdAbs), the autonomous variable domains of heavy chain-only antibodies produced naturally by camelid ungulates and cartilaginous fishes, have evolved to bind antigen using only three complementarity-determining region (CDR) loops rather than the six present in conventional V_H:V_L antibodies. It has been suggested, based on limited evidence, that sdAbs may adopt paratope structures that predispose them to preferential recognition of recessed protein epitopes, but poor or non-recognition of protuberant epitopes and small molecules. Here, we comprehensively surveyed the evidence in support of this hypothesis. We found some support for a global structural difference in the paratope shapes of sdAbs compared with those of conventional antibodies: sdAb paratopes have smaller molecular surface areas and diameters, more commonly have non-canonical CDR1 and CDR2 structures, and have elongated CDR3 length distributions, but have similar amino acid compositions and are no more extended (interatomic distance measured from CDR base to tip) than conventional antibody paratopes. Comparison of X-ray crystal structures of sdAbs and conventional antibodies in complex with cognate antigens showed that sdAbs and conventional antibodies bury similar solvent-exposed surface areas on proteins and form similar types of non-covalent interactions, although these are more concentrated in the compact sdAb paratope. Thus, sdAbs likely have privileged access to distinct antigenic regions on proteins, but only owing to their small molecular size and not to general differences in molecular recognition mechanism. The evidence surrounding the purported inability of sdAbs to bind small molecules was less clear. The available data provide a structural framework for understanding the evolutionary emergence and function of autonomous heavy chain-only antibodies.

Analysis of nanobody paratopes reveals greater diversity than classical antibodies

Nanobodies (Nbs) are a class of antigen-binding protein derived from camelid immune systems, which achieve equivalent binding affinities and specificities to classical antibodies (Abs) despite being comprised of only a single variable domain. Here, we use a data set of 156 unique Nb:antigen complex structures to characterize Nb-antigen binding and draw comparison to a set of 156 unique Ab:antigen structures. We analyse residue composition and interactions at the antigen interface, together with structural features of the paratopes of both data sets. Our analysis finds that the set of Nb structures displays much greater paratope diversity, in terms of the structural segments involved in the paratope, the residues used at these positions to contact the antigen and furthermore the type of contacts made with the antigen. Our findings suggest a different relationship between contact propensity and sequence variability from that observed for Ab VH domains. The distinction between sequence positions that control interaction specificity and those that form the domain scaffold is much less clear-cut for Nbs, and furthermore H3 loop positions play a much more dominant role in determining interaction specificity.

When monoclonal antibodies are not monospecific: Hybridomas frequently express additional functional variable regions

Monoclonal antibodies are commonly assumed to be monospecific, but anecdotal studies have reported genetic diversity in antibody heavy chain and light chain genes found within individual hybridomas. As the prevalence of such diversity has never been explored, we analyzed 185 random hybridomas, in a large multicenter dataset. The hybridomas analyzed were not biased towards those with cloning difficulties or known to have additional chains. Of the hybridomas we evaluated, 126 (68.1%) contained no additional productive chains, while the remaining 59 (31.9%) contained one or more additional productive heavy or light chains. The expression of additional chains degraded properties of the antibodies, including specificity, binding signal and/or signal-to-noise ratio, as determined by enzyme-linked immunosorbent assay and immunohistochemistry. The most abundant mRNA transcripts found in a hybridoma cell line did not necessarily encode the antibody chains providing the correct specificity. Consequently, when cloning antibody genes, functional validation of all possible VH and VL combinations is required to identify those with the highest affinity and lowest cross-reactivity. These findings, reflecting the current state of hybridomas used in research, reiterate the importance of using sequence-defined recombinant antibodies for research or diagnostic use.

Humanization of rabbit monoclonal antibodies via grafting combined Kabat/IMGT/Paratome complementarity-determining regions: Rationale and examples

Rabbit monoclonal antibodies (RabMAbs) can recognize diverse epitopes, including those poorly immunogenic in mice and humans. However, there have been only a few reports on RabMAb humanization, an important antibody engineering step usually done before clinical applications are investigated. To pursue a general method for humanization of RabMAbs, we analyzed the complex structures of 5 RabMAbs with their antigens currently available in the Protein Data Bank, and identified antigen-contacting residues on the rabbit Fv within the 6 Angstrom distance to its antigen. We also analyzed the supporting residues for antigen-contacting residues on the same heavy or light chain. We identified "HV4" and "LV4" in rabbit Fvs, non-complementarity-determining region (CDR) loops that are structurally close to the antigen and located in framework 3 of the heavy chain and light chain, respectively. Based on our structural and sequence analysis, we designed a humanization strategy by grafting the combined Kabat/IMGT/Paratome CDRs, which cover most antigen-contacting residues, into a human germline framework sequence. Using this strategy, we humanized 4 RabMAbs that recognize poorly immunogenic epitopes in the cancer target mesothelin. Three of the 4 humanized rabbit Fvs have similar or improved functional binding affinity for mesothelin-expressing cells. Interestingly, 4 immunotoxins composed of the humanized scFvs fused to a clinically used fragment of Pseudomonas exotoxin (PE38) showed stronger cytotoxicity against tumor cells than the immunotoxins derived from their original rabbit scFvs. Our data suggest that grafting the combined Kabat/IMGT/Paratome CDRs to a stable human germline framework can be a general approach to humanize RabMAbs.

Molecular basis for the antagonistic activity of an anti-CXCR4 antibody

Antagonistic antibodies targeting the G-protein C-X-C chemokine receptor 4 (CXCR4) hold promising therapeutic potential in various diseases. We report for the first time the detailed mechanism of action at a molecular level of a potent anti-CXCR4 antagonistic antibody (MEDI3185). We characterized the MEDI3185 paratope using alanine scanning on all 6 complementary-determining regions (CDRs). We also mapped its epitope using CXCR4 mutagenesis to assess the relative importance of the CXCR4 N-terminal peptide, extracellular loops (ECL) and ligand-binding pocket. We show that the interaction between MEDI3185 and CXCR4 is mediated mostly by CDR3H in MEDI3185 and ECL2 in CXCR4. The MEDI3185 epitope comprises the entire ECL2 sequence, lacks any so-called ‘hot-spot’ and is remarkably resistant to mutations. The structure of MEDI3185 variable domains was modeled, and suggested a β-strand/β-strand interaction between MEDI3185 CDR3H and CXCR4 ECL2, resulting in direct steric hindrance with CXCR4 ligand SDF-1. These findings may have important implications for designing antibody therapies against CXCR4.

Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies

Although humanized antibodies have been highly successful in the clinic, all current humanization techniques have potential limitations, such as: reliance on rodent hosts, immunogenicity due to high non-germ-line amino acid content, v-domain destabilization, expression and formulation issues. This study presents a technology that generates stable, soluble, ultrahumanized antibodies via single-step complementarity-determining region (CDR) germ-lining. For three antibodies from three separate key immune host species, binary substitution CDR cassettes were inserted into preferred human frameworks to form libraries in which only the parental or human germ-line destination residue was encoded at each position. The CDR-H3 in each case was also augmented with 1 ± 1 random substitution per clone. Each library was then screened for clones with restored antigen binding capacity. Lead ultrahumanized clones demonstrated high stability, with affinity and specificity equivalent to, or better than, the parental IgG. Critically, this was mainly achieved on germ-line frameworks by simultaneously subtracting up to 19 redundant non-germ-line residues in the CDRs. This process significantly lowered non-germ-line sequence content, minimized immunogenicity risk in the final molecules and provided a heat map for the essential non-germ-line CDR residue content of each antibody. The ABS technology therefore fully optimizes the clinical potential of antibodies from rodents and alternative immune hosts, rendering them indistinguishable from fully human in a simple, single-pass process.

Protein Crystallography in Vaccine Research and Development

The use of protein X-ray crystallography for structure-based design of small-molecule drugs is well-documented and includes several notable success stories. However, it is less well-known that structural biology has emerged as a major tool for the design of novel vaccine antigens. Here, we review the important contributions that protein crystallography has made so far to vaccine research and development. We discuss several examples of the crystallographic characterization of vaccine antigen structures, alone or in complexes with ligands or receptors. We cover the critical role of high-resolution epitope mapping by reviewing structures of complexes between antigens and their cognate neutralizing, or protective, antibody fragments. Most importantly, we provide recent examples where structural insights obtained via protein crystallography have been used to design novel optimized vaccine antigens. This review aims to illustrate the value of protein crystallography in the emerging discipline of structural vaccinology and its impact on the rational design of vaccines.

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.

The structural basis of antibody-antigen recognition

The function of antibodies (Abs) involves specific binding to antigens (Ags) and activation of other components of the immune system to fight pathogens. The six hypervariable loops within the variable domains of Abs, commonly termed complementarity determining regions (CDRs), are widely assumed to be responsible for Ag recognition, while the constant domains are believed to mediate effector activation. Recent studies and analyses of the growing number of available Ab structures, indicate that this clear functional separation between the two regions may be an oversimplification. Some positions within the CDRs have been shown to never participate in Ag binding and some off-CDRs residues often contribute critically to the interaction with the Ag. Moreover, there is now growing evidence for non-local and even allosteric effects in Ab-Ag interaction in which Ag binding affects the constant region and vice versa. This review summarizes and discusses the structural basis of Ag recognition, elaborating on the contribution of different structural determinants of the Ab to Ag binding and recognition. We discuss the CDRs, the different approaches for their identification and their relationship to the Ag interface. We also review what is currently known about the contribution of non-CDRs regions to Ag recognition, namely the framework regions (FRs) and the constant domains. The suggested mechanisms by which these regions contribute to Ag binding are discussed. On the Ag side of the interaction, we discuss attempts to predict B-cell epitopes and the suggested idea to incorporate Ab information into B-cell epitope prediction schemes. Beyond improving the understanding of immunity, characterization of the functional role of different parts of the Ab molecule may help in Ab engineering, design of CDR-derived peptides, and epitope prediction.

An automated immunoassay for early specificity profiling of antibodies

Antibody-based therapeutics are of great value for the treatment of human diseases. In addition to functional activity, affinity or physico-chemical properties, antibody specificity is considered to be one of the most crucial attributes for safety and efficacy. Consequently, appropriate studies are required before entering clinical trials. High content protein arrays are widely applied to assess antibody specificity, but this commercial solution can only be applied to final therapeutic antibody candidates because such arrays are expensive and their throughput is limited. A flexible, high-throughput and economical assay that allows specificity testing of IgG or Fab molecules during early discovery is described here. The 384-well microtiter plate assay contains a comprehensive panel of 32 test proteins and uses electrochemiluminescence as readout. The Protein Panel Profiling ( 3P) was used to analyze marketed therapeutic antibodies that all showed highly specific binding profiles. Subsequently, 3P was applied to antibody candidates from early discovery and the results compared well with those obtained with a commercially available high content protein chip. Our results suggest that 3P can be applied as an additional filter for lead selection, allowing the identification of favorable antibody candidates in early discovery and thereby increasing the speed and possibility of success in drug development.

Variable region identical immunoglobulins differing in isotype express different paratopes

The finding that the antibody (Ab) constant (C) region can influence fine specificity suggests that isotype switching contributes to the generation of Ab diversity and idiotype restriction. Despite the centrality of this observation for diverse immunological effects such as vaccine responses, isotype-restricted antibody responses, and the origin of primary and secondary responses, the molecular mechanism(s) responsible for this phenomenon are not understood. In this study, we have taken a novel approach to the problem by probing the paratope with (15)N label peptide mimetics followed by NMR spectroscopy and fluorescence emission spectroscopy. Specifically, we have explored the hypothesis that the C region imposes conformational constraints on the variable (V) region to affect paratope structure in a V region identical IgG(1), IgG(2a), IgG(2b), and IgG(3) mAbs. The results reveal isotype-related differences in fluorescence emission spectroscopy and temperature-related differences in binding and cleavage of a peptide mimetic. We conclude that the C region can modify the V region structure to alter the Ab paratope, thus providing an explanation for how isotype can affect Ab specificity.

Mechanism of lethal toxin neutralization by a human monoclonal antibody specific for the PA(20) region of Bacillus anthracis protective antigen

The primary immunogenic component of the currently approved anthrax vaccine is the protective antigen (PA) unit of the binary toxin system. PA-specific antibodies neutralize anthrax toxins and protect against infection. Recent research has determined that in humans, only antibodies specific for particular determinants are capable of effecting toxin neutralization, and that the neutralizing epitopes recognized by these antibodies are distributed throughout the PA monomer. The mechanisms by which the majority of these epitopes effect neutralization remain unknown. In this report we investigate the process by which a human monoclonal antibody specific for the amino-terminal domain of PA neutralizes lethal toxin in an in vitro assay of cytotoxicity, and find that it neutralizes LT by blocking the requisite cleavage of the amino-terminal 20 kD portion of the molecule (PA₂₀) from the remainder of the PA monomer. We also demonstrate that the epitope recognized by this human monoclonal does not encompass the ₁₆₆RKKR₁₆₉ furin recognition sequence in domain 1 of PA.