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Therapeutic antibody discovery using synthetic diversity has been proved productive, especially for target proteins not suitable for traditional animal immunization-based antibody discovery approaches. Recently, many lines of evidences suggest that the quality of synthetic diversity design limits the development success of synthetic antibody hits. The aim of our study is to understand the quality limitation and to properly address the challenges with a better design. Using VH3–23 as a model framework, we observed and quantitatively mapped CDR-H3 loop length-dependent usage of human IGHJ4 and IGHJ6 germline genes in the natural human immune repertoire. Skewed usage of DH2-JH6 and DH3-JH6 rearrangements was quantitatively determined in a CDR-H3 length-dependent manner in natural human antibodies with long CDR-H3 loops. Structural modeling suggests choices of JH help to stabilize antibody CDR-H3 loop and JH only partially contributes to the paratope. Our observations shed light on the design of next-generation synthetic diversity with improved probability of success.

A comparative canine–human therapeutics model is being developed in B-cell lymphoma through the generation of a hybridoma cell that produces a murine monoclonal antibody specific for canine CD20. The hybridoma cell produces two light chains, light chain-3, and light chain-7. However, the contribution of either light chain to the authentic full-length hybridoma derived IgG is undefined. Mass spectrometry was used to identify only one of the two light chains, light chain-7, as predominating in the full-length IgG. Gene synthesis created a recombinant murine–canine chimeric monoclonal antibody expressing light chain-7 that reconstituted the IgG binding to CD20. Using light chain-7 as a reference sequence, hydrogen deuterium exchange mass spectrometry was used to identify the dominant CDR region implicated in CD20 antigen binding. Early in the deuteration reaction, the CD20 antigen suppressed deuteration at CDR3 (VH). In later time points, deuterium suppression occurred at CDR2 (VH) and CDR2 (VL), with the maintenance of the CDR3 (VH) interaction. These data suggest that CDR3 (VH) functions as the dominant antigen docking motif and that antibody aggregation is induced at later time points after antigen binding. These approaches define a methodology for fine mapping of CDR contacts using nested enzymatic reactions and hydrogen deuterium exchange mass spectrometry. These data support the further development of an engineered, synthetic canine–murine monoclonal antibody, focused on CDR3 (VH), for use as a canine lymphoma therapeutic that mimics the human–murine chimeric anti-CD20 antibody Rituximab.

Objective To characterize T‐cell receptors (TCRs) and identify target epitopes in multiple sclerosis (MS). Methods Peripheral blood mononuclear cells were obtained from 39 MS patients and 19 healthy controls (HCs). TCR repertoires for α/β/δ/γ chains, TCR diversity, and V/J usage were determined by next‐generation sequencing. TCR β chain repertoires were compared with affectation status using a novel clustering method, Grouping of Lymphocyte Interactions by Paratope Hotspots (GLIPH). Cytomegalovirus (CMV)‐IgG was measured in an additional 113 MS patients and 93 HCs. Regulatory T cells (Tregs) were measured by flow cytometry. Results TCR diversity for all four chains decreased with age. TCRα and TCRβ diversity was higher in MS patients (P = 0.0015 and 0.024, respectively), even after age correction. TRAJ56 and TRBV4‐3 were more prevalent in MS patients than in HCs (pcorr = 0.027 and 0.040, respectively). GLIPH consolidated 208,674 TCR clones from MS patients into 1,294 clusters, among which two candidate clusters were identified. The TRBV4‐3 cluster was shared by HLA‐DRB1*04:05‐positive patients (87.5%) and predicted to recognize CMV peptides (CMV‐TCR). MS Severity Score (MSSS) was lower in patients with CMV‐TCR than in those without (P = 0.037). CMV‐IgG‐positivity was associated with lower MSSS in HLA‐DRB1*04:05 carriers (P = 0.0053). HLA‐DRB1*04:05‐positive individuals demonstrated higher CMV‐IgG titers than HLA‐DRB1*04:05‐negative individuals (P = 0.017). CMV‐IgG‐positive patients had more Tregs than CMV‐IgG‐negative patients (P = 0.054). Interpretation High TCRα/TCRβ diversity, regardless of age, is characteristic of MS. Association of a CMV‐recognizing TCR with mild disability indicates CMV’s protective role in HLA‐DRB1*04:05‐positive MS.

Synthetic antibodies hold great promise in combating diseases, diagnosis, and a wide range of biomedical applications. However, designing a therapeutically amenable, synthetic antibody that can arrest the aggregation of amyloid-β (Aβ) remains challenging. Here, we report a flexible, hairpin-like synthetic paratope (SP1, ∼2 kDa), which prevents the aggregation of Aβ monomers and reverses the preformed amyloid fibril to a non-toxic species. Structural and biophysical studies further allowed dissecting the mode and affinity of molecular recognition events between SP1 and Aβ. Subsequently, SP1 reduces Aβ-induced neurotoxicity, neuronal apoptosis, and ROS-mediated oxidative damage in human neuroblastoma cells (SH-SY5Y). The non-toxic nature of SP1 and its ability to ameliorate hippocampal neurodegeneration in a rat model of AD demonstrate its therapeutic potential. This paratope engineering module could readily implement discoveries of cost-effective molecular probes to nurture the basic principles of protein misfolding, thus combating related diseases.

In the last decades, antibodies have emerged as one of the most important and successful classes of biopharmaceuticals. The highest variability and diversity of an antibody is concentrated on six hypervariable loops, also known as complementarity determining regions (CDRs) shaping the antigen-binding site, the paratope. Whereas it was assumed that certain sequences can only adopt a limited set of backbone conformations, in this study we present a kinetic classification of several paratope states in solution. Using molecular dynamics simulations in combination with experimental structural information we capture the involved conformational transitions between different canonical clusters and additional dominant solution structures occurring in the micro-to-millisecond timescale. Furthermore, we observe a strong correlation of CDR loop movements. Another important aspect when characterizing different paratope states is the relative VH/VL orientation and the influence of the distinct CDR loop states on the VH/VL interface. Conformational rearrangements of the CDR loops do not only have an effect on the relative VH/VL orientations, but also influence in some cases the elbow-angle dynamics and shift the respective distributions. Thus, our results show that antibodies exist as several interconverting paratope states, each contributing to the antibody’s properties. Fernandez-Quintero et al. employ molecular dynamics simulations in combination with experimental structural information to demonstrate that antibodies exist as several interconverting paratope states. They propose that dynamic conformational transitions on the micro-to-millisecond timescale are responsible for antibody allostery in contrast to the long believed paradigm of static canonical structures determining binding properties and specificity of antibodies.

Macromolecular protease inhibitors and camelid single-domain antibodies achieve their enzymic inhibition functions often through protruded structures that directly interact with catalytic centers of targeted proteases. Inspired by this phenomenon, we constructed synthetic human antibody libraries encoding long CDR-H3s, from which highly selective monoclonal antibodies (mAbs) that inhibit multiple proteases were discovered. To elucidate their molecular mechanisms, we performed in-depth biochemical characterizations on a panel of matrix metalloproteinase (MMP)-14 inhibitory mAbs. Assays included affinity and potency measurements, enzymatic kinetics, a competitive enzyme-linked immunosorbent assay, proteolytic stability, and epitope mapping followed by quantitative analysis of binding energy changes. The results collectively indicated that these mAbs of convex paratopes were competitive inhibitors recognizing the vicinity of the active cleft, with their significant epitopes scattered across the north and south rims of the cleft. Remarkably, identified epitopes were the surface loops that were highly diverse among MMPs and predominately located at the prime side of the proteolytic site, shedding light on the mechanisms of target selectivity and proteolytic resistance. Substrate sequence profiling and paratope mutagenesis further suggested that mAb 3A2 bound to the active-site cleft in a canonical (substrate-like) manner, by direct interactions between (100h)NLVATP(100m) of its CDR-H3 and subsites S1–S5′ of MMP-14. Overall, synthetic mAbs carrying convex paratopes can achieve efficient inhibition and thus hold great therapeutic promise for effectively and safely targeting biomedically important proteases.

Eplets are functional units of structural epitopes on donor HLA, potentially recognized by complementarity-determining regions of the paratope of the recipients' B-cell receptors or antibodies (Ab). Their individual immunogenicity is poorly described, yet this feature would be of clinical importance for pretransplant risk assessment. The aim of this study was to determine the relative immunogenicity of HLA class I eplets in the pregnancy setting, where mismatched eplets are present on paternal HLA antigens of the unborn child. One hundred fifty-nine predominantly Caucasian mothers giving birth at the University Hospital Basel and their first newborns were HLA-typed at high-resolution by next-generation sequencing (NGS) (NGSgo Workflow and NGSengine from GenDx; sequencing with a Miseq from Illumina) and eplets were determined using HLAMatchmaker. HLA class I specific IgG Ab was assessed in maternal sera drawn immediately after full-term delivery, by OneLambda LABScreen single antigen ibeads. The Ab profile was subsequently evaluated for eplet-associated patterns. All 72 currently Ab-verified HLA class I eplets were examined for their immunogenicity according to the frequency of child-specific HLA Ab (CSA) directed against their structures. Four hundred twelve of 477 (86.4%) paternal HLA-A, -B or -C alleles were mismatched. CSA were present in 46 mothers (28.9%), directed against 80 (19.4%) of these mismatches. The 10 most immunogenic eplets were 62GK, 145KHA, 144TKH, 62GE, 107W, 80I, 82LR, 41T, 127K, 45KE with immunogenicity rates between 45.8% and 27.3%. This pregnancy study also identified five non-reactive eplets: 62RR, 76ESN, 80TLR, 156DA, 163RW. Based on our results, immunogenic hot and cold spots on the surface of HLA class I molecules were localized and visualized on 3D models. This study strengthens the presumption that different eplets represent different immunogenic potentials. Validation of these results in the clinical transplant setting is an essential next step in identifying those eplets representing a particularly high-risk potential.

Significance We describe an antibody optimization strategy that seeks to overcome the restrictive nature of existing affinity-maturation methods, by rapidly exploring a vast sequence space in an unbiased manner through application of PCR techniques and ribosome display. We exemplified the significance of this method by contrasting the crystal structure of the parent and optimized antibodies bound to Arginase 2, which revealed a striking reorientation of the binding paratope, concurrent with distinct improvements in inhibitory potency and binding properties. The nature and magnitude of the epitope expansion was extraordinary and unlikely to have been produced through conventional affinity-maturation methods. This innovative approach demonstrates broad applicability to the optimization of candidate therapeutic antibodies, even those less amenable to CDRH3 targeting., Affinity maturation is a powerful technique in antibody engineering for the in vitro evolution of antigen binding interactions. Key to the success of this process is the expansion of sequence and combinatorial diversity to increase the structural repertoire from which superior binding variants may be selected. However, conventional strategies are often restrictive and only focus on small regions of the antibody at a time. In this study, we used a method that combined antibody chain shuffling and a staggered-extension process to produce unbiased libraries, which recombined beneficial mutations from all six complementarity-determining regions (CDRs) in the affinity maturation of an inhibitory antibody to Arginase 2 (ARG2). We made use of the vast display capacity of ribosome display to accommodate the sequence space required for the diverse library builds. Further diversity was introduced through pool maturation to optimize seven leads of interest simultaneously. This resulted in antibodies with substantial improvements in binding properties and inhibition potency. The extensive sequence changes resulting from this approach were translated into striking structural changes for parent and affinity-matured antibodies bound to ARG2, with a large reorientation of the binding paratope facilitating increases in contact surface and shape complementarity to the antigen. The considerable gains in therapeutic properties seen from extensive sequence and structural evolution of the parent ARG2 inhibitory antibody clearly illustrate the advantages of the unbiased approach developed, which was key to the identification of high-affinity antibodies with the desired inhibitory potency and specificity.

Background The recent outbreak by SARS-CoV-2 has generated a chaos in global health and economy and claimed/infected a large number of lives. Closely resembling with SARS CoV, the present strain has manifested exceptionally higher degree of spreadability, virulence and stability possibly due to some unidentified mutations. The viral spike glycoprotein is very likely to interact with host Angiotensin-Converting Enzyme 2 (ACE2) and transmits its genetic materials and hijacks host machinery with extreme fidelity for self propagation. Few attempts have been made to develop a suitable vaccine or ACE2 blocker or virus-receptor inhibitor within this short period of time. Methods Here, attempt was taken to develop some therapeutic and vaccination strategies with a comparison of spike glycoproteins among SARS-CoV, MERS-CoV and the SARS-CoV-2. We verified their structure quality (SWISS-MODEL, Phyre2, and Pymol) topology (ProFunc), motifs (MEME Suite, GLAM2Scan), gene ontology based conserved domain (InterPro database) and screened several epitopes (SVMTrip) of SARS CoV-2 based on their energetics, IC50 and antigenicity with regard to their possible glycosylation and MHC/paratope binding (Vaxigen v2.0, HawkDock, ZDOCK Server) effects. Results We screened here few pairs of spike protein epitopic regions and selected their energetic, Inhibitory Concentration50 (IC50), MHC II reactivity and found some of those to be very good target for vaccination. A possible role of glycosylation on epitopic region showed profound effects on epitopic recognition. Conclusion The present work might be helpful for the urgent development of a suitable vaccination regimen against 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 host Communicated by Ramaswamy H. Sarma

Vaccination remains one of the most successful biomedical interventions for preventing viral diseases. While early vaccines were developed by attenuating the infectious agent in cell cultures or by inactivation, new delivery platforms are on the rise thanks to the advent of genetic engineering. The COVID-19 pandemic stimulated the rapid adoption and a massive deployment of these platforms. Viral vector vaccines elicit antigen expression within cells and induce a robust cytotoxic T cell response, unlike protein subunit vaccines conferring mainly humoral immunity. mRNA vaccines also deliver the antigen inside the cells while offering more manageable and faster manufacturing possibilities. Unlike DNA-based vaccines, mRNA does not enter the nucleus, and thus, the probability of disrupting gene expression in the recipient cell is diminished. This thesis aims to offer an overview of current approaches in vaccinology and discuss the various platforms in use. The thesis will also present recent advances in the development of prophylactic vaccines against infections with human immunodeficiency virus-1 (HIV-1) and hepatitis C virus (HCV) and also will focus on a recently proposed strategy for vaccine development based on non-cognate ligands mimicking epitopes recognised by broadly neutralising antibodies...

International audience; The human monoclonal antibody C10 exhibits extraordinary cross-reactivity, potently neutralizing Zika virus (ZIKV) and the four serotypes of dengue virus (DENV1-DENV4). Here we describe a comparative structure-function analysis of C10 bound to the envelope (E) protein dimers of the five viruses it neutralizes. We demonstrate that the C10 Fab has high affinity for ZIKV and DENV1 but not for DENV2, DENV3, and DENV4. We further show that the C10 interaction with the latter viruses requires an E protein conformational landscape that limits binding to only one of the three independent epitopes per virion. This limited affinity is nevertheless counterbalanced by the particle's icosahedral organization, which allows two different dimers to be reached by both Fab arms of a C10 immunoglobulin. The epitopes' geometric distribution thus confers C10 its exceptional neutralization breadth. Our results highlight the importance not only of paratope/epitope complementarity but also the topological distribution for epitope-focused vaccine design.

An individual’s B cell receptor (BCR) repertoire encodes information about past immune responses, and potential for future disease protection. Deciphering the information stored in BCR sequence datasets will transform our fundamental understanding of disease and enable discovery of novel diagnostics and antibody therapeutics. One of the grand challenges of BCR sequence analysis is the prediction of BCR properties from their amino acid sequence alone. Here we present an antibody-specific language model, AntiBERTa, which provides a contextualised representation of BCR sequences. Following pre-training, we show that AntiBERTa embeddings learn biologically relevant information, generalizable to a range of applications. As a case study, we demonstrate how AntiBERTa can be fine-tuned to predict paratope positions from an antibody sequence, outperforming public tools across multiple metrics. To our knowledge, AntiBERTa is the deepest protein family-specific language model, providing a rich representation of BCRs. AntiBERTa embeddings are primed for multiple downstream tasks and can improve our understanding of the language of antibodies.

Synthetic genetic polymers (xeno-nucleic acids, XNAs) have the potential to transition aptamers from laboratory tools to therapeutic agents, but additional functionality is needed to compete with antibodies. Here, we describe the evolution of a biologically stable artificial genetic system composed of α-l-threofuranosyl nucleic acid (TNA) that facilitates the production of backbone- and base-modified aptamers termed "threomers" that function as high quality protein capture reagents. Threomers were discovered against two prototypical protein targets implicated in human diseases through a combination of in vitro selection and next-generation sequencing using uracil nucleotides that are uniformly equipped with aromatic side chains commonly found in the paratope of antibody-antigen crystal structures. Kinetic measurements reveal that the side chain modifications are critical for generating threomers with slow off-rate binding kinetics. These findings expand the chemical space of evolvable non-natural genetic systems to include functional groups that enhance protein target binding by mimicking the structural properties of traditional antibodies.

The coronavirus disease 2019 (COVID‐19) has affected the lives of millions of people around the world. In an effort to develop therapeutic interventions and control the pandemic, scientists have isolated several neutralizing antibodies against SARS‐CoV‐2 from the vaccinated and convalescent individuals. These antibodies can be explored further to understand SARS‐CoV‐2 specific antigen–antibody interactions and biophysical parameters related to binding affinity, which can be utilized to engineer more potent antibodies for current and emerging SARS‐CoV‐2 variants. In the present study, we have analyzed the interface between spike protein of SARS‐CoV‐2 and neutralizing antibodies in terms of amino acid residue propensity, pair preference, and atomic interaction energy. We observed that Tyr residues containing contacts are highly preferred and energetically favorable at the interface of spike protein–antibody complexes. We have also developed a regression model to relate the experimental binding affinity for antibodies using structural features, which showed a correlation of 0.93. Moreover, several mutations at the spike protein–antibody interface were identified, which may lead to immune escape (epitope residues) and improved affinity (paratope residues) in current/emerging variants. Overall, the work provides insights into spike protein–antibody interactions, structural parameters related to binding affinity and mutational effects on binding affinity change, which can be helpful to develop better therapeutics against COVID‐19.

In this work, we have generated epidermal growth factor receptor (EGFR)-specific cattle-derived ultralong CDR-H3 antibodies by combining cattle immunization with yeast surface display. After immunization, ultralong CDR-H3 regions were specifically amplified and grafted onto an IGHV1-7 scaffold by homologous recombination to facilitate Fab display. Antigen-specific clones were readily obtained by fluorescence-activated cell sorting (FACS) and reformatted as chimeric antibodies. Binning experiments revealed epitope targeting of domains I, II, and IV of EGFR with none of the generated binders competing with Cetuximab, Matuzumab, or EGF for binding to EGFR. Cattle-derived chimeric antibodies were potent in inducing antibody-dependent cell-mediated cytotoxicity (ADCC) against EGFR-overexpressing tumor cells with potencies (EC50 killing) in the picomolar range. Moreover, most of the antibodies were able to significantly inhibit EGFR-mediated downstream signaling. Furthermore, we demonstrate that a minor fraction of CDR-H3 knobs derived from generated antibodies was capable of independently functioning as a paratope facilitating EGFR binding when grafted onto the Fc part of human IgG1. Besides slightly to moderately diminished capacities, these engineered Knobbodies largely retained main properties of their parental antibodies such as cellular binding and triggering of ADCC. Hence, Knobbodies might emerge as promising tools for biotechnological applications upon further optimization.

The recent emergence of Zika virus (ZIKV) has affected many countries, with severe clinical manifestations such as fetal microcephaly and Guillain-Barré syndrome. However, even though it is a major public health concern, there is no approved treatment available. Structural knowledge of the main neutralization regions of the envelope (E) protein of ZIKV and its interactions with neutralizing antibodies (nAbs) are crucial for the rational development of subunit vaccines and establishment of antibody-based interventions. In this study we screened from public data hot spot epitopes in conserved regions of ZIKV E protein that are nAbs targets. The result points to a conserved epitope located at domain II of the ZIKV E protein, namely adjacent dimer epitope, which is the ZIKV-117 and Z20 nAbs target. Although these two nAbs have been isolated from different donors, we have demonstrated, from structural and energetic details obtained by molecular dynamics of native and mutants, that hot spots residues of the epitope are the same for these nAbs, thereby indicating that they may share similar binding and neutralization mechanism. This convergence of information between these nAbs is important because both are potential targets for the development of therapies against ZIKV and only Z20 has its sequence and its complex structure with ZIKV E protein determined. Finally, these findings also contribute to existing knowledge, by fine mapping of the epitope/paratope residue pairs that are important for biotechnological development of therapies such as epitope mimetics for subunit vaccines and the rational design for antibody-based interventions against ZIKV. Communicated by Ramaswamy H. Sarma.

Designed ankyrin repeat proteins (DARPins) are artificial binding proteins that have found many uses in therapy, diagnostics and biochemical research. They substantially extend the scope of antibody-derived binders. Their high affinity and specificity, rigidity, extended paratope, and facile bacterial production make them attractive for structural biology. Complexes with simple DARPins have been crystallized for a long time, but particularly the rigid helix fusion strategy has opened new opportunities. Rigid DARPin fusions expand crystallization space, enable recruitment of targets in a host lattice and reduce the size limit for cryo-EM. Besides applications in structural biology, rigid DARPin fusions also serve as molecular probes in cells to investigate spatial restraints in targets.

Conventional monoclonal antibodies (mAbs) have been widely used in research and diagnostic applications due to their high affinity and specificity. However, multiple limitations, such as large size, complex structure and sensitivity to extreme ambient temperature potentially weaken the performance of mAbs in certain applications. To address this problem, the exploration of new antigen binders is extensively required in relation to improve the quality of current diagnostic platforms. In recent years, a new immunoglobulin-based protein, namely variable domain of new antigen receptor (VNAR) was discovered in sharks. Unlike conventional mAbs, several advantages of VNARs, include small size, better thermostability and peculiar paratope structure have attracted interest of researchers to further explore on it. This article aims to first present an overview of the shark VNARs and outline the characteristics as an outstanding new reagent for diagnostic and therapeutic applications., Highlights • Antibodies are powerful tools due to their high affinity and specificity. • In tropical regions degradation of mAbs in test kits due to high temperatures is problematic. • Shark single domain antibody (VNAR) can have better thermostability than mAbs. • VNAR potentially provides new reagents for diagnostic and therapeutic applications.

Nimotuzumab is a humanized monoclonal antibody against the Epidermal Growth Factor Receptor with a long history of therapeutic use, recognizing an epitope different from the ones targeted by other antibodies against the same antigen. It is also distinguished by much less toxicity resulting in a better safety profile, which has been attributed to its lower affinity compared to these other antibodies. Nevertheless, the ideal affinity window for optimizing the balance between anti-tumor activity and toxic effects has not been determined. In the current work, the paratope of the phage-displayed nimotuzumab Fab fragment was evolved in vitro to obtain affinity-matured variants. Soft-randomization of heavy chain variable region CDRs and phage selection resulted in mutated variants with improved binding ability. Two recombinant antibodies were constructed using these variable regions, which kept the original fine epitope specificity and showed moderate affinity increases against the target (3-4-fold). Such differences were translated into a greatly enhanced inhibitory capacity upon ligand-induced receptor phosphorylation on tumor cells. The new antibodies, named K4 and K5, are valuable tools to explore the role of affinity in nimotuzumab biological properties, and could be used for applications requiring a fine-tuning of the balance between binding to tumor cells and healthy tissues.

The existing repertoire of HIV-1 patient derived broadly neutralising antibodies (bNAbs) that target the HIV-1 envelope glycoprotein (Env) present numerous and exciting opportunities for immune-based therapeutic and preventative strategies against HIV-1. Combination antibody therapy is required to ensure greater neutralization coverage and limit Env mediated escape mutations following treatment pressure. Engineered bispecific bNAbs (bibNAbs) assimilate the advantages of combination therapy into a single antibody molecule with several configurations reporting potency enhancement as a result of the increased avidity and simultaneous engagement of targeted epitopes. We report the engineering of a novel bibNAb (iMab-CAP256) comprising the highly potent, CAP256.VRC26.25 bNAb with anticipated extension in neutralization coverage through pairing with the host directed, anti-CD4 antibody, ibalizumab (iMab). Recombinant expression of parental monoclonal antibodies and the iMab-CAP256 bibNAb was performed in HEK293T (Human embryonic kidney 293 T antigen) cells, purified to homogeneity by Protein-A affinity chromatography followed by size exclusion chromatography. Antibody assembly and binding functionality of Fab moieties was confirmed by SDS-PAGE (sodium dodecyl sulphate polyacrylamide gel electrophoresis) and ELISA, respectively. Breadth and potency were evaluated against a geographical diverse HIV-1 pseudovirus panel (n = 20). Overall, iMab-CAP256 demonstrated an expanded neutralizing coverage, neutralizing single, parental antibody resistant pseudovirus strains and an enhanced neutralization potency against all dual sensitive strains (average fold increase over the more potent parental antibody of 11.4 (range 2 to 31.8). Potency enhancement was not observed for the parental antibody combination treatment (iMab + CAP256) suggesting the presence of a synergistic relationship between the CAP256 and iMab paratope combination in this bibNAb configuration. In addition, iMab-CAP256 bibNAbs exhibited comparable efficacy to other bibNAbs PG9-iMab and 10E08-iMab previously reported in the literature. The enhanced neutralization coverage and potency of iMAb-CAP256 over the parental bNAbs should facilitate superior clinical performance as a therapeutic or preventative strategy against HIV-1.

Background: The development of effective vaccine preventing HIV-1 infection is hindered by enormous antigenic variability and unique biochemical and immunological properties of HIV-1 Env glycoprotein, the most promising target for HIV-1 neutralizing antibody. Functional studies of rare elite neutralizers led to the discovery of broadly neutralizing antibodies. Methods: We employed a highly complex combinatorial protein library derived from a 5 kDa albumin-binding domain scaffold, fused with protein backbone of total 38 kDa, to screen for binders of broadly neutralizing antibody VRC01 paratope. The most specific binders were used for immunization of experimental mice to elicit Env-specific antibodies and to test their neutralization activity using a panel of HIV-1 clade C and B pseudoviruses. Findings: Three most specific binders designated as VRA017, VRA019, and VRA177 exhibited high specificity to VRC01 antibody. Immunized mice produced Env-binding antibodies which neutralize five of eight HIV-1 pseudoviruses. Molecular modelling revealed a high structural similarity of the VRA proteins to VRC01-interacting Env surface. Interpretation: This strategy based on identification of protein replicas of broadly neutralizing antibody paratope as a "reverse vaccinology variety" represents a novel approach in HIV-1 vaccine development. This approach is not affected by inherited low immungenicity, variability, and unique biochemical properties of HIV-1 Env used as a crucial antigen in majority of contemporary tested vaccines. Funding: Czech Health Research Council 15-32198A, European Regional Development Fund CZ.1.05/1.1.00/02.0109, European Structural Funds, Operational Programme Research, Development and Education of the Ministry of Education, Youth and Sports CZ.02.1.01/0.0/0.0/16_025/0007397 and CZ.02.1.01/0.0/0.0/15_003/, Institutional Research Concepts RVO:86652036 and RO0519. Declaration of Interest: Nothing to declare. Ethical Approval: The vaccination experiments were approved by the Ethics Committee of the Faculty of Medicine and Dentistry (Palacky University in Olomouc), and the Ministry of Education, Youth and Sports, Czech Republic (MSMT-15434/2015-7).

The claim that it is possible to rationally design a structure-based HIV-1 vaccine is based on misconceptions regarding the nature of protein epitopes and of immunological specificity. Attempts to use reverse vaccinology to generate an HIV-1 vaccine on the basis of the structure of viral epitopes bound to monoclonal neutralizing antibodies have failed so far because it was not possible to extrapolate from an observed antigenic structure to the immunogenic structure required in a vaccine. Vaccine immunogenicity depends on numerous extrinsic factors such as the host immunoglobulin gene repertoire, the presence of various cellular and regulatory mechanisms in the immunized host and the process of antibody affinity maturation. All these factors played a role in the appearance of the neutralizing antibody used to select the epitope to be investigated as potential vaccine immunogen, but they cannot be expected to be present in identical form in the host to be vaccinated. It is possible to rationally design and optimize an epitope to fit one particular antibody molecule or to improve the paratope binding efficacy of a monoclonal antibody intended for passive immunotherapy. What is not possible is to rationally design an HIV-1 vaccine immunogen that will elicit a protective polyclonal antibody response of predetermined efficacy. An effective vaccine immunogen can only be discovered by investigating experimentally the immunogenicity of a candidate molecule and demonstrating its ability to induce a protective immune response. It cannot be discovered by determining which epitopes of an engineered antigen molecule are recognized by a neutralizing monoclonal antibody. This means that empirical immunogenicity trials rather than structural analyses of antigens offer the best hope of discovering an HIV-1 vaccine.

The construction of large libraries in mammalian cells allows the direct screening of millions of molecular variants for binding properties in a cell type relevant for screening or production. We have created mammalian cell libraries of up to 10 million clones displaying a repertoire of IgG-formatted antibodies on the cell surface. TALE nucleases or CRISPR/Cas9 were used to direct the integration of the antibody genes into a single genomic locus, thereby rapidly achieving stable expression and transcriptional normalization. The utility of the system is illustrated by the affinity maturation of a PD-1-blocking antibody through the systematic mutation and functional survey of 4-mer variants within a 16 amino acid paratope region. Mutating VH CDR3 only, we identified a dominant “solution” involving substitution of a central tyrosine to histidine. This appears to be a local affinity maximum, and this variant was surpassed by a lysine substitution when light chain variants were introduced. We achieve this comprehensive and quantitative interrogation of sequence space by combining high-throughput oligonucleotide synthesis with mammalian display and flow cytometry operating at the multi-million scale.

The isolation of nanobodies from pre-immune libraries by means of biopanning is a straightforward process. Nevertheless, the recovered candidates often require optimization to improve some of their biophysical characteristics. In principle, CDRs are not mutated because they are likely to be part of the antibody paratope, but in this work, we describe a mutagenesis strategy that specifically addresses CDR1. Its sequence was identified as an instability hot spot by the PROSS program, and the available structural information indicated that four CDR1 residues bound directly to the antigen. We therefore modified the loop flexibility with the addition of an extra glycine rather than by mutating single amino acids. This approach significantly increased the nanobody yields but traded-off with moderate affinity loss. Accurate modeling coupled with atomistic molecular dynamics simulations enabled the modifications induced by the glycine insertion and the rationale behind the engineering design to be described in detail.

MotivationAntibodies are a type of important biomolecules in the humoral immunity system, which can bind tightly to potential antigens with high affinity and specificity. An accurate identification of the paratope, the binding sites with antigens, is crucial for antibody mechanistic research and design. Although many methods have been developed for paratope prediction, further improvement of their accuracy is necessary.ResultsIn this study, we concatenated the sequences of Complementarity Determining Regions (CDRs) within a single antibody to better capture nonlocal interactions between different CDRs and loop type-specific features for improving paratope prediction. We further integrated BiLSTM and transformer networks to gain the dependencies among the residues within the concatenated CDR sequences and to increase the interpretability of the model. The new method called DeepANIS (Antibody Interacting Site prediction) outperforms other antibody paratope prediction methods compared.AvailabilityThe DeepANIS method is freely available as a webserver at https://biomed.nscc-gz.cn:9094/apps/DeepANIS and for download at https://github.com/HideInDust/DeepANISContactyangyd25@mail.sysu.edu.cn or zhouyq@szbl.ac.cnSupplementary informationSupplementary data are available at Bioinformatics online.

Nanobodies (Nbs) as capture antibodies in enzyme-linked immunosorbent assays (ELISAs) is greatly hampered by their poor performance after attaching onto polystyrene microplates. Reasons behind those phenomena remain unknown. One of possible explanation is that Nbs with a single domain might lose their accessibility of paratope when adsorbed on the plates. Increasing their binding sites might improve performance in capture Nbs-based ELISA. In this study, anti-3-phenoxybenzoic acid (3-PBA) Nbs was assembled to trivalent form (Nb3) in tandem with flexible linkers (G4S)3. Direct competitive ELISA on the basis of Nb3 and 3-PBA-horseradish peroxidase was developed for detection of 3-PBA in livestock urine. The ELISA had a half-maximum (IC50) inhibition concentration of 0.51 ng/mL, with a limit of detection of 0.02 ng/mL, which was more sensitive than that of the parental Nb with a IC50 of 2.39 ng/mL. The average recoveries of 3-PBA spiked in swine, sheep and dairy cow urine samples by the assay ranged from 89.52% to 114.25% and agreed well with those of liquid chromatography mass spectrometry (LC-MS). The above results indicated that multivalent Nbs could be treated as the capture antibody in ELISA for routine screening analysis of 3-PBA residues in urine.

Antibodies have the remarkable ability to recognise their cognate antigens with extraordinary affinity and specificity. Discerning the rules that define antibody-antigen recognition is a fundamental step in the rational design and engineering of functional antibodies with desired properties. In this study we apply the 3D Zernike formalism to the analysis of the surface properties of the antibody complementary determining regions (CDRs). Our results show that shape and electrostatic 3DZD descriptors of the surface of the CDRs are predictive of antigen specificity, with classification accuracy of 81% and area under the receiver operating characteristic curve (AUC) of 0.85. Additionally, while in terms of surface size, solvent accessibility and amino acid composition, antibody epitopes are typically not distinguishable from non-epitope, solvent-exposed regions of the antigen, the 3DZD descriptors detect significantly higher surface complementarity to the paratope, and are able to predict correct paratope-epitope interaction with an AUC = 0.75.

Antibodies are proteins which play a vital role in the immune system by recognizing and neutralizing antigens. The region on the antibody binding to an antigen, known as paratope, mediates antibody-antigen interaction with high affinity and specificity. And the accurate prediction of those regions from antibody sequence contributes to the design of therapeutic antibodies and remains challenging. However, the experimental methods are time-consuming and expensive. In this article, we propose a sequence-based method for antibody paratope prediction by combing local and global information of antibody sequence and partner features from partner antigen sequence. Convolution Neural Networks(CNNs) and a sliding window approach on antibody sequence are used to extract local information. Attention-based Bidirectional Long Short-Term Memory (Att-BLSTM) on antibody sequence are used to extract global information. Also, the partner antigen is vital for paratope prediction, and we employ Att-BLSTM on the partner antigen sequence as well. The outputs of CNNs and Att-BLSTM networks are combined to predict antibody paratope by fully-connected networks. The experiments show that our proposed method achieves superior performance over the state-of-the-art sequenced-based antibody paratope prediction methods on benchmark datasets.

Generative machine learning (ML) has been postulated to be 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 both the computation of antibody-antigen 3D-structures as well as functions as an oracle for unrestricted prospective evaluation of the antigen specificity of ML-generated antibody sequences. We found that a deep generative model, trained exclusively on antibody sequence (1D) data can be used to design native-like conformational (3D) epitope-specific antibodies, matching or exceeding the training dataset in affinity and developability variety. Furthermore, we show that transfer learning enables the generation of high-affinity antibody sequences from low-N training data. Finally, we validated that the antibody design insight gained from simulated antibody-antigen binding data is applicable to experimental real-world data. Our work establishes a priori feasibility and the theoretical foundation of high-throughput ML-based mAb design.HighlightsA large-scale dataset of 70M [3 orders of magnitude larger than the current state of the art] synthetic antibody-antigen complexes, that reflect biological complexity, allows the prospective evaluation of antibody generative deep learningCombination of generative learning, synthetic antibody-antigen binding data, and prospective evaluation shows that deep learning driven antibody design and discovery at an unconstrained level is feasibleTransfer learning (low-N learning) coupled to generative learning shows that antibody-binding rules may be transferred across unrelated antibody-antigen complexesExperimental validation of antibody-design conclusions drawn from deep learning on synthetic antibody-antigen binding dataGraphical abstractWe leverage large synthetic ground-truth data to demonstrate the (A,B) unconstrained deep generative learning-based generation of native-like antibody sequences, (C) the prospective evaluation of conformational (3D) affinity, paratope-epitope pairs, and developability. (D) Finally, we show increased generation quality of low-N-based machine learning models via transfer learning.

Machine learning (ML) is a key technology to enable accurate prediction of antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two orthogonal problems hinder the current application of ML to antibody-specificity prediction and the benchmarking thereof: (i) The lack of a unified formalized mapping of immunological antibody specificity prediction problems into ML notation and (ii) the unavailability of large-scale training datasets. Here, we developed the Absolut! software suite that allows the parameter-based unconstrained generation of synthetic lattice-based 3D-antibody-antigen binding structures with ground-truth access to conformational paratope, epitope, and affinity. We show that Absolut!-generated datasets recapitulate critical biological sequence and structural features that render antibody-antigen binding prediction challenging. To demonstrate the immediate, high-throughput, and large-scale applicability of Absolut!, we have created an online database of 1 billion antibody-antigen structures, the extension of which is only constrained by moderate computational resources. We translated immunological antibody specificity prediction problems into ML tasks and used our database to investigate paratope-epitope binding prediction accuracy as a function of structural information encoding, dataset size, and ML method, which is unfeasible with existing experimental data. Furthermore, we found that in silico investigated conditions, predicted to increase antibody specificity prediction accuracy, align with and extend conclusions drawn from experimental antibody-antigen structural data. In summary, the Absolut! framework enables the development and benchmarking of ML strategies for biotherapeutics discovery and design. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/451258v2_ufig1.gif" ALT="Figure 1"> View larger version (81K): org.highwire.dtl.DTLVardef@418bfforg.highwire.dtl.DTLVardef@14e1ec9org.highwire.dtl.DTLVardef@1c75b50org.highwire.dtl.DTLVardef@13bf69d_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO The software framework Absolut! enables (A,B) the generation of virtually arbitrarily large numbers of in silico 3D-antibody-antigen structures, (C,D) the formalization of antibody specificity as machine learning (ML) tasks as well as the exploration of ML strategies for paratope-epitope prediction. C_FIG Highlights- Software framework Absolut! to generate an arbitrarily large number of in silico 3D-antibody-antigen structures - Generation of one billion in silico antigen-antibody structures reflecting biological layers of complexity that make ML predictions challenging - Immunological antibody specificity prediction problems formalized as machine learning tasks for which the in silico complexes are immediately usable as benchmark. - Exploration of machine learning architectures for paratope-epitope interaction prediction accuracy as a function of neural network depth, dataset size, and sequence-structure encoding

Cysteine-rich knob domains found in the ultralong complementarity determining regions of a subset of bovine antibodies, are capable of functioning autonomously as 3-6 kDa peptides. While they can be expressed recombinantly in cellular systems, in this paper we show that knob domains are also readily amenable to chemical synthesis, with a co-crystal structure of a chemically synthesised knob domain in complex with antigen showing structural equivalence to the biological product. For drug discovery, following immunisation of cattle, knob domain peptides can be synthesised directly from antibody sequence data, combining the power and diversity of the bovine immune repertoire with the ability to rapidly incorporate non-biological modifications. We demonstrate that, through rational design with non-natural amino acids, paratope diversity can be massively expanded, in this case improving the efficacy of an allosteric peptide. As a potential route to further improve stability, we also performed head-to-tail cyclisation, exploiting the unusual proximity of the N- and C-termini to synthesise functional, fully cyclic antibody fragments. Lastly, we highlight the stability of knob domains in plasma and, through pharmacokinetic studies, use palmitoylation as a route to extend the plasma half-life of knob domains in vivo. This study presents an antibody-derived medicinal chemistry platform, with protocols for solid-phase synthesis of knob domains; together with characterisation of their molecular structures, in vitro pharmacology and pharmacokinetics.

SARS-CoV-2 mutations with antigenic effects pose a risk to immunity developed through vaccination and natural infection. While vaccine updates for current variants of concern (VOCs) are underway, it is likewise important to prepare for further antigenic mutations as the virus navigates the heterogeneous global landscape of host immunity. Toward this end, a wealth of data and tools exist that can augment existing genetic surveillance of VOC evolution. In this study, we integrate published datasets describing genetic, structural, and functional constraints on mutation along with computational analyses of antibody-spike co-crystal structures to identify a set of potential antigenic drift sites (PADS) within the receptor binding domain (RBD) and N-terminal domain (NTD) of SARS-CoV-2 spike protein. Further, we project the PADS set into a continuous epitope-paratope space to facilitate interpretation of the degree to which newly observed mutations might be antigenically synergistic with existing VOC mutations, and this representation suggests that functionally convergent and synergistic antigenic mutations are accruing across VOC NTDs. The PADS set and synergy visualization serve as a reference as new mutations are detected on VOCs, enable proactive investigation of potentially synergistic mutations, and offer guidance to antibody and vaccine design efforts., Graphical Abstract

Understanding the molecular mechanisms by which antibodies target and neutralize the HIV-1 envelope glycoprotein (Env) is critical in guiding immunogen design and vaccine development aimed at eliciting cross-reactive neutralizing antibodies (NAbs). Here, we analyzed monoclonal antibodies (mAbs) isolated from non-human primates (NHPs) immunized with variants of a native flexibly linked (NFL) HIV-1 Env stabilized trimer derived from the tier 2 clade C 16055 strain. The antibodies displayed neutralizing activity against the autologous virus with potencies ranging from 0.005 to 3.68 μg/ml (IC50). Structural characterization using negative-stain EM and X-ray crystallography identified the variable region 2 (V2) of the 16055 NFL trimer to be the common epitope for these antibodies. The crystal structures revealed that the V2 segment adopts a β-hairpin motif identical to that observed in the 16055 NFL crystal structure. These results depict how vaccine-induced antibodies derived from different clonal lineages penetrate through the glycan shield to recognize a hypervariable region within V2 (residues 184–186) that is unique to the 16055 strain. They also provide potential explanations for the potent autologous neutralization of these antibodies, confirming the immunodominance of this site and revealing that multiple angles of approach are permissible for affinity/avidity that results in potent neutralizing capacity. The structural analysis reveals that the most negatively charged paratope correlated with the potency of the mAbs. The atomic level information is of interest to both define the means of autologous neutralization elicited by different tier 2-based immunogens and facilitate trimer redesign to better target more conserved regions of V2 to potentially elicit cross-neutralizing HIV-1 antibodies., Author summary NHPs immunizations with an HIV-1 immunogen (native-like tier 2 clade C 16055 strain) elicit potent HIV-1 tier 2 autologous polyclonal neutralizing antibodies. To understand the basis of the autologous neutralization, we determined structures of antibodies isolated from the vaccinated NHPs in complex with their epitopes. Our structural analysis reveals that the V2 hypervariable region, unique to 16055, is immunodominant and targeted by antibodies from diverse lineages. Additionally, vaccine-elicited V2 NAbs use different binding angles to avoid Env N-glycan shield and the more negatively charged paratope displays potent autologous neutralizing function. In summary, detailed analysis of how vaccine-elicited monoclonal antibodies interact with the target antigen provide valuable information for the design of immunogens aimed to elicit more broadly HIV-neutralizing antibodies. The use of cocktail/prime-boost sequential regimens that include a range of sequence variation combined with the removal/shielding of unwanted immunodominant epitopes will likely be needed to reach this goal.

Members of the αv family of integrins regulate activation of transforming growth factor beta (TGFβ) and are directly involved in pro-tumorigenic phenotypes. Thus, αv integrins may be therapeutic targets for fibrosis and cancer, yet the isolation of selective inhibitors is currently a challenge. We generated synthetic antibodies selective for αv integrins by phage display selections on cell lines that displayed integrin heterodimers. We identified antibodies that targeted two distinct epitopes on cell-surface αv integrins and partially inhibited cell adhesion mediated by interactions between integrins and the latency-associated peptide, part of the pro-form of TGFβ. Using the isolated antibody paratope sequences we engineered a bispecific antibody capable of binding to both epitopes simultaneously; this antibody potently and completely inhibited cell adhesion mediated by integrins αvβ1, αvβ3 and αvβ5. In addition, the bispecific antibody inhibited proliferation and migration of lung carcinoma lines, where the highest and lowest potencies observed correlated with integrin-αv cell surface expression levels. Taken together, our results demonstrate that phage display selections with live cells can yield high quality anti-integrin antibodies, which we used as biparatopic building blocks to construct a bispecific antibody that strongly inhibited integrin function and may be a therapeutic candidate for cancer and fibrosis.

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

Cancer is a major cause of morbidity and mortality worldwide and constitutes a considerable burden on society. The inhibitors targeting the programmed death receptor–1 (PD-1)/programmed death ligand 1 protein (PD-L1) pathway are the most promising approaches for cancer treatment. Toripalimab, a humanized IgG4 antibody targeting PD-1, was approved by the China National Medical Products Administration in 2018. Although the crystal structure of the toripalimab/PD-1 complex was reported in 2019, it was just a frozen structure and needs to be further studied dynamically to fully understand the blockade mechanism of the antibody toripalimab. Thus, long-time molecular dynamics (MD) simulations were performed for toripalimab/PD-1 and PD-1/PD-L1 complexes. Nine residues were predicted to be epitope and paratope residues for toripalimab, including PD-1PRO130, PD-1LYS131, PD-1ALA132, PD-1ILE134 and GLU99H, GLY100H, THR102H, TYR111H, HSE31L. The PD-1ALA132 locating on the FG loop is the common binding site for PD-L1 and toripalimab. Thus, antibody toripalimab block PD-1/PD-L1 interaction through direct competitive binding of the FG loop of PD-1.

SARS-CoV-2 has caused a worldwide epidemic of coronavirus disease 19 (COVID-19). Antibody drugs present an effective weapon for tens of millions of COVID-19 patients. Antibodies disrupting the interactions between the receptor-binding domain (RBD) of SARS-CoV-2 S protein and the angiotensin converting enzyme 2 (ACE2) effectively block SARS-CoV-2 cell entry into host cells. In order to rapidly develop more potent neutralizing antibodies, we utilized virtual scanning mutageneses and molecular dynamics simulations to optimize the antibody of P2B-2F6 isolated from single B cells of SARS-CoV-2 infected patients. Two potent P2B-2F6 mutants, namely H:V106R and H:V106R/H:P107Y, were found to possess higher binding affinities with the RBD domain of SARS-CoV-2 than others. Polar interactions are preferred near 106 and 107 paratope residues of the heavy chain. The mutations also increase the hydrogen-bonding network formed between the antibody and the RBD. Notably, the optimized antibodies possess potential neutralizing activity against the alarming SARS-CoV-2 variant of N501Y. This study provides insights into structure-based optimization of antibodies with higher affinity to the antigen. We hope that our proposed antibody mutants could contribute to the development of improved therapies against COVID-19.