Structure-guided mutations in CDRs for enhancing the affinity of neutralizing SARS-CoV-2 nanobody.

The optimization of antibodies to attain the desired levels of affinity and specificity holds great promise for the development of next generation therapeutics. This study delves into the refinement and engineering of complementarity-determining regions (CDRs) through in silico affinity maturation followed by binding validation using isothermal titration calorimetry (ITC) and pseudovirus-based neutralization assays. Specifically, it focuses on engineering CDRs targeting the epitopes of receptor-binding domain (RBD) of the spike protein of SARS-CoV-2. A structure-guided virtual library of 112 single mutations in CDRs was generated and screened against RBD to select the potential affinity-enhancing mutations. Protein-protein docking analysis identified 32 single mutants of which nine mutants were selected for molecular dynamics (MD) simulations. Subsequently, biophysical ITC studies provided insights into binding affinity, and consistent with in silico findings, six mutations that demonstrated better binding affinity than native nanobody were further tested in vitro for neutralization activity against SARS-CoV-2 pseudovirus. Leu106Thr mutant was found to be most effective in virus-neutralization with IC50 values of ∼0.03 µM, as compared to the native nanobody (IC50 ∼0.77 µM). Thus, in this study, the developed computational pipeline guided by structure-aided interface profiles and thermodynamic analysis holds promise for the streamlined development of antibody-based therapeutic interventions against emerging variants of SARS-CoV-2 and other infectious pathogens.

Unsupervised evolution of protein and antibody complexes with a structure-informed language model.

Large language models trained on sequence information alone can learn high-level principles of protein design. However, beyond sequence, the three-dimensional structures of proteins determine their specific function, activity, and evolvability. Here, we show that a general protein language model augmented with protein structure backbone coordinates can guide evolution for diverse proteins without the need to model individual functional tasks. We also demonstrate that ESM-IF1, which was only trained on single-chain structures, can be extended to engineer protein complexes. Using this approach, we screened about 30 variants of two therapeutic clinical antibodies used to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We achieved up to 25-fold improvement in neutralization and 37-fold improvement in affinity against antibody-escaped viral variants of concern BQ.1.1 and XBB.1.5, respectively. These findings highlight the advantage of integrating structural information to identify efficient protein evolution trajectories without requiring any task-specific training data.

SARS-CoV-2: Prediction of critical ionic amino acid mutations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that caused coronavirus disease 2019 (COVID-19), has been studied thoroughly, and several variants are revealed across the world with their corresponding mutations. Studies and vaccines development focus on the genetic mutations of the S protein due to its vital role in allowing the virus attach and fuse with the membrane of a host cell. In this perspective, we study the effects of all ionic amino acid mutations of the SARS-CoV-2 viral spike protein S1 when bound to Antibody CC12.1 within the SARS-CoV-2:CC12.1 complex model. Binding free energy calculations between SARS-CoV-2 and antibody CC12.1 are based on the Analysis of Electrostatic Similarities of Proteins (AESOP) framework, where the electrostatic potentials are calculated using Adaptive Poisson-Boltzmann Solver (APBS). The atomic radii and charges that feed into the APBS calculations are calculated using the PDB2PQR software. Our results are the first to propose in silico potential life-threatening mutations of SARS-CoV-2 beyond the present mutations found in the five common variants worldwide. We find each of the following mutations: K378A, R408A, K424A, R454A, R457A, K458A, and K462A, to play significant roles in the binding to Antibody CC12.1, since they are turned into strong inhibitors on both chains of the S1 protein, whereas the mutations D405A, D420A, and D427A, show to play important roles in this binding, as they are turned into mild inhibitors on both chains of the S1 protein.

Comparative single-cell transcriptomic profile of hybrid immunity induced by adenovirus vector-based COVID-19 vaccines.

In this study, antibody response and a single-cell RNA-seq analysis were conducted on peripheral blood mononuclear cells from five different groups: naïve subjects vaccinated with AZD1222 (AZ) or Ad5-nCoV (Cso), individuals previously infected and later vaccinated (hybrid) with AZD1222 (AZ-hb) or Ad5-nCoV (Cso-hb), and those who were infected and had recovered from COVID-19 (Inf). The results showed that AZ induced more robust neutralizing antibody responses than Cso. The single-cell RNA data revealed a high frequency of memory B cells in the Cso and Cso-hb. In contrast, AZ and AZ-hb groups exhibited the highest proportion of activated naïve B cells expressing CXCR4. Transcriptomic analysis of CD4+ and CD8+ T cells demonstrated a heterogeneous response following vaccination, hybrid immunity, or natural infection. However, a single dose of Ad5-nCoV was sufficient to strongly activate CD4+ T cells (naïve and memory) expressing ANX1 and FOS, similar to the hybrid response observed with AZ. An interesting finding was the robust activation of a subset of CD8+ T cells expressing GZMB, GZMH, and IFNG genes in the Cso-hb group. Our findings suggest that both vaccines effectively stimulated the cellular immune response; however, the Ad5-nCoV induced a more robust CD8+ T-cell response in previously infected individuals.

Efficient evolution of human antibodies from general protein language models.

Natural evolution must explore a vast landscape of possible sequences for desirable yet rare mutations, suggesting that learning from natural evolutionary strategies could guide artificial evolution. Here we report that general protein language models can efficiently evolve human antibodies by suggesting mutations that are evolutionarily plausible, despite providing the model with no information about the target antigen, binding specificity or protein structure. We performed language-model-guided affinity maturation of seven antibodies, screening 20 or fewer variants of each antibody across only two rounds of laboratory evolution, and improved the binding affinities of four clinically relevant, highly mature antibodies up to sevenfold and three unmatured antibodies up to 160-fold, with many designs also demonstrating favorable thermostability and viral neutralization activity against Ebola and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudoviruses. The same models that improve antibody binding also guide efficient evolution across diverse protein families and selection pressures, including antibiotic resistance and enzyme activity, suggesting that these results generalize to many settings.

Predicting the immune escape of SARS-CoV-2 neutralizing antibodies upon mutation.

COVID-19 has resulted in millions of deaths and severe impact on economies worldwide. Moreover, the emergence of SARS-CoV-2 variants presented significant challenges in controlling the pandemic, particularly their potential to avoid the immune system and evade vaccine immunity. This has led to a growing need for research to predict how mutations in SARS-CoV-2 reduces the ability of antibodies to neutralize the virus. In this study, we assembled a set of 1813 mutations from the interface of SARS-CoV-2 spike protein's receptor binding domain (RBD) and neutralizing antibody complexes and developed a machine learning model to classify high or low escape mutations using interaction energy, inter-residue contacts and predicted binding free energy change. Our approach achieved an Area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.91 using the Random Forest classifier on the test dataset with 217 mutations. The model was further utilized to predict the escape mutations on a dataset of 29,165 mutations located at the interface of 83 RBD-neutralizing antibody complexes. A small subset of this dataset was also validated based on available experimental data. We found that top 10 % high escape mutations were dominated by charged to nonpolar mutations whereas low escape mutations were dominated by polar to nonpolar mutations. We believe that the present method will allow prioritization of high/low escape mutations in the context of neutralizing antibodies targeting SARS-CoV-2 RBD region and assist antibody design for current and emerging variants.

The interaction and mediation effects between the host genetic factors and Epstein-Barr virus VCA-IgA in the risk of nasopharyngeal carcinoma.

Previous studies have demonstrated strong associations between host genetic factors and Epstein-Barr virus (EBV) VCA-IgA with the risk of nasopharyngeal carcinoma (NPC). However, the specific interplay between host genetics and EBV VCA-IgA on NPC risk is not well understood. In this two-stage case-control study (N = 4804), we utilized interaction and mediation analysis to investigate the interplay between host genetics (genome-wide association study-derived polygenic risk score [PRS]) and EBV VCA-IgA antibody level in the NPC risk. We employed a four-way decomposition analysis to assess the extent to which the genetic effect on NPC risk is mediated by or interacts with EBV VCA-IgA. We consistently found a significant interaction between the PRS and EBV VCA-IgA on NPC risk (discovery population: synergy index [SI] = 2.39, 95% confidence interval [CI] = 1.85-3.10; replication population: SI = 3.10, 95% CI = 2.17-4.44; all pinteraction < 0.001). Moreover, the genetic variants included in the PRS demonstrated similar interactions with EBV VCA-IgA antibody. We also observed an obvious dose-response relationship between the PRS and EBV VCA-IgA antibody on NPC risk (all ptrend < 0.001). Furthermore, our decomposition analysis revealed that a substantial proportion (approximately 90%) of the genetic effects on NPC risk could be attributed to host genetic-EBV interaction, while the risk effects mediated by EBV VCA-IgA antibody were weak and statistically insignificant. Our study provides compelling evidence for an interaction between host genetics and EBV VCA-IgA antibody in the development of NPC. These findings emphasize the importance of implementing measures to control EBV infection as a crucial strategy for effectively preventing NPC, particularly in individuals at high genetic risk.

Deoptimization of FMDV P1 Region Results in Robust Serotype-Independent Viral Attenuation.

Foot-and-mouth disease (FMD), caused by the FMD virus (FMDV), is a highly contagious disease of cloven-hoofed livestock that can have severe economic impacts. Control and prevention strategies, including the development of improved vaccines, are urgently needed to effectively control FMD outbreaks in endemic settings. Previously, we employed two distinct strategies (codon pair bias deoptimization (CPD) and codon bias deoptimization (CD)) to deoptimize various regions of the FMDV serotype A subtype A12 genome, which resulted in the development of an attenuated virus in vitro and in vivo, inducing varying levels of humoral responses. In the current study, we examined the versatility of the system by using CPD applied to the P1 capsid coding region of FMDV serotype A subtype, A24, and another serotype, Asia1. Viruses carrying recoded P1 (A24-P1Deopt or Asia1-P1Deopt) exhibited different degrees of attenuation (i.e., delayed viral growth kinetics and replication) in cultured cells. Studies in vivo using a mouse model of FMD demonstrated that inoculation with the A24-P1Deopt and Asia1-P1Deopt strains elicited a strong humoral immune response capable of offering protection against challenge with homologous wildtype (WT) viruses. However, different results were obtained in pigs. While clear attenuation was detected for both the A24-P1Deopt and Asia1-P1Deopt strains, only a limited induction of adaptive immunity and protection against challenge was detected, depending on the inoculated dose and serotype deoptimized. Our work demonstrates that while CPD of the P1 coding region attenuates viral strains of multiple FMDV serotypes/subtypes, a thorough assessment of virulence and induction of adaptive immunity in the natural host is required in each case in order to finely adjust the degree of deoptimization required for attenuation without affecting the induction of protective adaptive immune responses.

Viral Capsid, Antibody, and Receptor Interactions: Experimental Analysis of the Antibody Escape Evolution of Canine Parvovirus.

Canine parvovirus (CPV) is a small nonenveloped single-stranded DNA virus that causes serious diseases in dogs worldwide. The original strain of the virus (CPV-2) emerged in dogs during the late 1970s due to a host range switch of a virus similar to the feline panleukopenia virus that infected another host. The virus that emerged in dogs had altered capsid receptor and antibody binding sites, with some changes affecting both functions. Further receptor and antibody binding changes arose when the virus became better adapted to dogs or to other hosts. Here, we used in vitro selection and deep sequencing to reveal how two antibodies with known interactions select for escape mutations in CPV. The antibodies bound two distinct epitopes, and one largely overlapped the host receptor binding site. We also generated mutated antibody variants with altered binding structures. Viruses were passaged with wild-type (WT) or mutated antibodies, and their genomes were deep sequenced during the selective process. A small number of mutations were detected only within the capsid protein gene during the first few passages of selection, and most sites remained polymorphic or were slow to go to fixation. Mutations arose both within and outside the antibody binding footprints on the capsids, and all avoided the transferrin receptor type 1 binding footprint. Many selected mutations matched those that have arisen in the natural evolution of the virus. The patterns observed reveal the mechanisms by which these variants have been selected in nature and provide a better understanding of the interactions between antibody and receptor selections. IMPORTANCE Antibodies protect animals against infection by many different viruses and other pathogens, and we are gaining new information about the epitopes that induce antibody responses against viruses and the structures of the bound antibodies. However, less is known about the processes of antibody selection and antigenic escape and the constraints that apply in this system. Here, we used an in vitro model system and deep genome sequencing to reveal the mutations that arose in the virus genome during selection by each of two monoclonal antibodies or their mutated variants. High-resolution structures of each of the Fab:capsid complexes revealed their binding interactions. The wild-type antibodies or their mutated variants allowed us to examine how changes in antibody structure influence the mutational selection patterns seen in the virus. The results shed light on the processes of antibody binding, neutralization escape, and receptor binding, and they likely have parallels for many other viruses.

Goats with low levels of AAV antibody may serve as candidates for large animal gene therapy.

AAV vector-mediated gene therapy has been proposed as a feasible strategy for several eye diseases. However, AAV antibodies in the serum prior to treatment hinder the transduction efficiency and thus the therapeutic effect. Therefore, it is necessary to evaluate AAV antibodies in the serum before gene therapy. As large animals, goats are more closely related to humans than rodents and more economically available than nonhuman primates. Here, we first evaluated the AAV2 antibody serum level in rhesus monkeys before AAV injection. Then, we optimized a cell-based neutralizing antibody assay for detecting AAV antibodies in the serum of Saanen goats and evaluated the consistency of the cell-based neutralizing antibody assay and ELISA for goat serum antibody evaluation. The cell-based neutralizing antibody assay showed that the percentage of macaques with low antibody levels was 42.86%; however, there were no macaques with low antibody levels when the serum was evaluated by ELISA. The proportion of goats with low antibody levels was 56.67% according to the neutralizing antibody assay and 33. 33% according to the ELISA, and McNemar's test showed that the results of the two assays were not significantly different (P = 0.754), but that their consistency is poor (Kappa = 0.286, P = 0.114). Moreover, longitudinal evaluation of serum antibodies before and after intravitreal injection of AAV2 in goats revealed that the level of AAV antibodies increased and transduction inhibition subsequently increased, as reported in humans, indicating that transduction inhibition should be taken into account at different stages of gene therapy. In summary, starting with an evaluation of monkey serum antibodies, we optimized a detection method of goat serum antibodies, providing an alternative large animal model for gene therapy, and our serum antibody measurement method may be applied to other large animals.

A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses.

Surface antigens of pathogens are commonly targeted by vaccine-elicited antibodies but antigenic variability, notably in RNA viruses such as influenza, HIV and SARS-CoV-2, pose challenges for control by vaccination. For example, influenza A(H3N2) entered the human population in 1968 causing a pandemic and has since been monitored, along with other seasonal influenza viruses, for the emergence of antigenic drift variants through intensive global surveillance and laboratory characterisation. Statistical models of the relationship between genetic differences among viruses and their antigenic similarity provide useful information to inform vaccine development, though accurate identification of causative mutations is complicated by highly correlated genetic signals that arise due to the evolutionary process. Here, using a sparse hierarchical Bayesian analogue of an experimentally validated model for integrating genetic and antigenic data, we identify the genetic changes in influenza A(H3N2) virus that underpin antigenic drift. We show that incorporating protein structural data into variable selection helps resolve ambiguities arising due to correlated signals, with the proportion of variables representing haemagglutinin positions decisively included, or excluded, increased from 59.8% to 72.4%. The accuracy of variable selection judged by proximity to experimentally determined antigenic sites was improved simultaneously. Structure-guided variable selection thus improves confidence in the identification of genetic explanations of antigenic variation and we also show that prioritising the identification of causative mutations is not detrimental to the predictive capability of the analysis. Indeed, incorporating structural information into variable selection resulted in a model that could more accurately predict antigenic assay titres for phenotypically-uncharacterised virus from genetic sequence. Combined, these analyses have the potential to inform choices of reference viruses, the targeting of laboratory assays, and predictions of the evolutionary success of different genotypes, and can therefore be used to inform vaccine selection processes.

[Mumps virus (Paramyxoviridae: Orthorubulavirus: Mumps orthorubulavirus) genotyping as a component of laboratory confirmation of infection].

INTRODUCTION: Mumps is a viral infection of high social significance. National program Elimination of measles and rubella and achievement of a stable sporadic incidence of epidemic mumps in the Russian Federation (20212025) sets the aim of gradual integration of mumps surveillance into the existing measles and rubella surveillance system. One of the key components of surveillance system is a laboratory confirmation of mumps cases. There are two approaches for laboratory confirmation of mumps cases, based on serological or molecular genetic methods. The aim of the work is molecular genetic characteristic of the mumps viruses (MuVs) circulated in the Russian Federation in 2022. MATERIALS AND METHODS: Samples of swabs from the inner surface of the cheek of 11 patients with mumps were collected for the study. Viral RNA was isolated directly from the samples. The isolated RNA was used as a matrix for RT-PCR. PCR products were sequenced using the Sanger method, and phylogenetic analysis was performed using the MEGA-X software. RESULTS: The MuV genotype G was detected in all samples. Phylogenetic analysis showed the presence of two virus genetic groups G-1 and G-2 that were significantly different from the viruses circulating in other countries. CONCLUSION: The identification of two MuV genetic groups in a limited area suggests a high genetic diversity of the pathogen.

SARS-CoV-2 multi-antigen protein microarray for detailed characterization of antibody responses in COVID-19 patients.

Antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) target multiple epitopes on different domains of the spike protein, and other SARS-CoV-2 proteins. We developed a SARS-CoV-2 multi-antigen protein microarray with the nucleocapsid, spike and its domains (S1, S2), and variants with single (D614G, E484K, N501Y) or double substitutions (N501Y/Deletion69/70), allowing a more detailed high-throughput analysis of the antibody repertoire following infection. The assay was demonstrated to be reliable and comparable to ELISA. We analyzed antibodies from 18 COVID-19 patients and 12 recovered convalescent donors. The S IgG level was higher than N IgG in most of the COVID-19 patients, and the receptor-binding domain of S1 showed high reactivity, but no antibodies were detected against the heptad repeat domain 2 of S2. Furthermore, antibodies were detected against S variants with single and double substitutions in COVID-19 patients who were infected with SARS-CoV-2 early in the pandemic. Here we demonstrated that the SARS-CoV-2 multi-antigen protein microarray is a powerful tool for detailed characterization of antibody responses, with potential utility in understanding the disease progress and assessing current vaccines and therapies against evolving SARS-CoV-2.

A single, improbable B cell receptor mutation confers potent neutralization against cytomegalovirus.

Cytomegalovirus (CMV) is a leading cause of infant hearing loss and neurodevelopmental delay, but there are no clinically licensed vaccines to prevent infection, in part due to challenges eliciting neutralizing antibodies. One of the most well-studied targets for CMV vaccines is the viral fusogen glycoprotein B (gB), which is required for viral entry into host cells. Within gB, antigenic domain 2 site 1 (AD-2S1) is a target of potently neutralizing antibodies, but gB-based candidate vaccines have yet to elicit robust responses against this region. We mapped the genealogy of B cells encoding potently neutralizing anti-gB AD-2S1 antibodies from their inferred unmutated common ancestor (UCA) and characterized the binding and function of early lineage ancestors. Surprisingly, we found that a single amino acid heavy chain mutation A33N, which was an improbable mutation rarely generated by somatic hypermutation machinery, conferred broad CMV neutralization to the non-neutralizing UCA antibody. Structural studies revealed that this mutation mediated key contacts with the gB AD-2S1 epitope. Collectively, these results provide insight into potently neutralizing gB-directed antibody evolution in a single donor and lay a foundation for using this B cell-lineage directed approach for the design of next-generation CMV vaccines.

Expanding and improving nanobody repertoires using a yeast display method: Targeting SARS-CoV-2.

COVID-19, caused by the coronavirus SARS-CoV-2, represents a serious worldwide health issue, with continually emerging new variants challenging current therapeutics. One promising alternate therapeutic avenue is represented by nanobodies, small single-chain antibodies derived from camelids with numerous advantageous properties and the potential to neutralize the virus. For identification and characterization of a broad spectrum of anti-SARS-CoV-2 Spike nanobodies, we further optimized a yeast display method, leveraging a previously published mass spectrometry-based method, using B-cell complementary DNA from the same immunized animals as a source of VHH sequences. Yeast display captured many of the sequences identified by the previous approach, as well as many additional sequences that proved to encode a large new repertoire of nanobodies with high affinities and neutralization activities against different SARS-CoV-2 variants. We evaluated DNA shuffling applied to the three complementarity-determining regions of antiviral nanobodies. The results suggested a surprising degree of modularity to complementarity-determining region function. Importantly, the yeast display approach applied to nanobody libraries from immunized animals allows parallel interrogation of a vast number of nanobodies. For example, we employed a modified yeast display to carry out massively parallel epitope binning. The current yeast display approach proved comparable in efficiency and specificity to the mass spectrometry-based approach, while requiring none of the infrastructure and expertise required for that approach, making these highly complementary approaches that together appear to comprehensively explore the paratope space. The larger repertoires produced maximize the likelihood of discovering broadly specific reagents and those that powerfully synergize in mixtures.

Human antibody BD-218 has broad neutralizing activity against concerning variants of SARS-CoV-2.

As SARS-CoV-2 variants of concern (VOC) reduce the effectiveness of existing anti-COVID therapeutics, it is increasingly critical to identify highly potent neutralizing antibodies (nAbs) that bind to conserved regions across multiple variants, especially beta, delta, and omicron variants. Using single-cell sequencing with biochemical methods and pseudo-typed virus neutralization experiments, here we report the characterization of a potent nAb BD-218, identified from an early screen of patients recovering from the original virus. We have determined the cryo-EM structure of the BD-218/spike protein complex to define its epitope in detail, which revealed that BD-218 interacts with a novel epitope on the receptor-binding domain (RBD) of the spike protein. We concluded that BD-218 is a highly effective and broadly active nAb against SARS-CoV-2 variants with promising potential for therapeutic development.

Molecular characterization of recombinant premembrane protein of dengue virus serotype-2 for development of diagnostic assay.

Dengue is an acute arboviral infection common in tropical and subtropical countries. Dengue has been highlighted as a public health concern in the last five decades, affecting almost 50% of the population in developing nations. Dengue infection results in a complex symptomatic disease that ranges from headache, fever, and skin rash to extreme hemorrhage fever and liver dysfunction. The diagnosis of the disease is essential for effective treatment. The early onset of the infection can be detected through viral structural peptides that act as markers for detection, including Pre-Membrane (Pre-M) protein. In the currently proposed research, the structural gene obtained from local isolates was targeted for studies. For this purpose, recombinant structural protein Pre-M was amplified, cloned, and expressed in the bacterial expression system. The expression of the structural protein (Pre-M) was scrutinized by Sodium Dodecyl Sulphate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) and validated by western blot and dot blot, and afterwards, the antigen was purified. The purified Pre-M protein carries the potential for the development of in-house diagnostic assay as well as for vaccine production. This study aimed to develop a highly specific, sensitive, and cost-effective in-house enzyme-linked immunoassay (ELISA) for the detection of antibodies of Pakistani most prevalent dengue virus serotype 2 (DENV-2). The success of this research would also pave the way toward developing novel vaccines for the future prevention of dengue infection.

Exploring the role of framework mutations in enabling breadth of a cross-reactive antibody (CR3022) against the SARS-CoV-2 RBD and its variants of concern.

Cross-reactive and broadly neutralizing antibodies against surface proteins of diverse strains of rapidly evolving viral pathogens like SARS-CoV-2 can prevent infection and therefore are crucial for the development of effective universal vaccines. While antibodies typically incorporate mutations in their complementarity determining regions during affinity maturation, mutations in the framework regions have been reported as players in determining properties of broadly neutralizing antibodies against HIV and the Influenza virus. We propose an increase in the cross-reactive potential of CR3022 against the emerging SARS- CoV-2 variants of concern through enhanced conformational flexibility. In this study, we use molecular dynamics simulations, in silico mutagenesis, structural modeling, and docking to explore the role of light chain FWR mutations in CR3022, a SARS-CoV anti-spike (S)-protein antibody cross-reactive to the S-protein receptor binding domain of SARS-CoV-2. Our study shows that single substitutions in the light chain framework region of CR3022 with conserved epitopes across SARS-CoV strains allow targeting of diverse antibody epitope footprints that align with the epitopes of recently-categorized neutralizing antibody classes while enabling binding to more than one strain of SARS-CoV-2. Our study has implications for rapid and evolution-based engineering of broadly neutralizing antibodies and reaffirms the role of framework mutations in effective change of antibody orientation and conformation via improved flexibility.Communicated by Ramaswamy H. Sarma.

A bovine antibody possessing an ultralong complementarity-determining region CDRH3 targets a highly conserved epitope in sarbecovirus spike proteins.

Broadly neutralizing antibodies have huge potential as novel antiviral therapeutics due to their ability to recognize highly conserved epitopes that are seldom mutated in viral variants. A subset of bovine antibodies possess an ultralong complementarity-determining region (CDR)H3 that is highly adept at recognizing such conserved epitopes, but their reactivity against Sarbecovirus Spike proteins has not been explored previously. Here, we use a SARS-naïve library to isolate a broadly reactive bovine CDRH3 that binds the receptor-binding domain of SARS-CoV, SARS-CoV-2, and all SARS-CoV-2 variants. We show further that it neutralizes viruses pseudo-typed with SARS-CoV Spike, but this is not by competition with angiotensin-converting enzyme 2 (ACE2) binding. Instead, using differential hydrogen-deuterium exchange mass spectrometry, we demonstrate that it recognizes the major site of vulnerability of Sarbecoviruses. This glycan-shielded cryptic epitope becomes available only transiently via interdomain movements of the Spike protein such that antibody binding triggers destruction of the prefusion complex. This proof of principle study demonstrates the power of in vitro expressed bovine antibodies with ultralong CDRH3s for the isolation of novel, broadly reactive tools to combat emerging pathogens and to identify key epitopes for vaccine development.