Nanobody derived using a peptide epitope from the Spike protein receptor-binding motif inhibits entry of SARS-CoV-2 variants.

The emergence of new escape mutants of the SARS-CoV-2 virus has escalated its penetration among the human population and has reinstated its status as a global pandemic. Therefore, developing effective antiviral therapy against emerging SARS-CoV variants and other viruses in a short period of time becomes essential. Blocking SARS-CoV-2 entry into human host cells by disrupting the Spike glycoprotein-angiotensin-converting enzyme 2 (ACE2) interaction has already been exploited for vaccine development and monoclonal antibody therapy. Unlike the previous reports, our study used a nine-amino acid peptide from the receptor-binding motif (RBM) of the Spike (S) protein as an epitope. We report the identification of an efficacious nanobody N1.2 that blocks the entry of pseudovirus-containing SARS-CoV-2 Spike as the surface glycoprotein. Moreover, using mCherry fluorescence based reporter assay we observe a more potent neutralizing effect against both the hCoV19 (Wuhan/WIV04/2019) and the Omicron (BA.1) pseudotyped Spike virus with a bivalent version of the N1.2 nanobody. In summary, our study presents a rapid, and efficient methodology to use peptide sequences from a protein-receptor interaction interface as epitopes for screening nanobodies against potential pathogenic targets. We propose that this approach can also be widely extended to target other viruses and pathogens in the future.

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.

Mapping monoclonal anti-SARS-CoV-2 antibody repertoires against diverse coronavirus antigens.

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged continuously, challenging the effectiveness of vaccines, diagnostics, and treatments. Moreover, the possibility of the appearance of a new betacoronavirus with high transmissibility and high fatality is reason for concern. In this study, we used a natively paired yeast display technology, combined with next-generation sequencing (NGS) and massive bioinformatic analysis to perform a comprehensive study of subdomain specificity of natural human antibodies from two convalescent donors. Using this screening technology, we mapped the cross-reactive responses of antibodies generated by the two donors against SARS-CoV-2 variants and other betacoronaviruses. We tested the neutralization potency of a set of the cross-reactive antibodies generated in this study and observed that most of the antibodies produced by these patients were non-neutralizing. We performed a comparison of the specific and non-specific antibodies by somatic hypermutation in a repertoire-scale for the two individuals and observed that the degree of somatic hypermutation was unique for each patient. The data from this study provide functional insights into cross-reactive antibodies that can assist in the development of strategies against emerging SARS-CoV-2 variants and divergent betacoronaviruses.

Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain.

The continual evolution of SARS-CoV-2 and the emergence of variants that show resistance to vaccines and neutralizing antibodies threaten to prolong the COVID-19 pandemic. Selection and emergence of SARS-CoV-2 variants are driven in part by mutations within the viral spike protein and in particular the ACE2 receptor-binding domain (RBD), a primary target site for neutralizing antibodies. Here, we develop deep mutational learning (DML), a machine-learning-guided protein engineering technology, which is used to investigate a massive sequence space of combinatorial mutations, representing billions of RBD variants, by accurately predicting their impact on ACE2 binding and antibody escape. A highly diverse landscape of possible SARS-CoV-2 variants is identified that could emerge from a multitude of evolutionary trajectories. DML may be used for predictive profiling on current and prospective variants, including highly mutated variants such as Omicron, thus guiding the development of therapeutic antibody treatments and vaccines for COVID-19.

Massively multiplexed affinity characterization of therapeutic antibodies against SARS-CoV-2 variants.

Antibody therapies represent a valuable tool to reduce COVID-19 deaths and hospitalizations. Multiple antibody candidates have been granted emergency use authorization by the Food and Drug Administration and many more are in clinical trials. Most antibody therapies for COVID-19 are engineered to bind to the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein and disrupt its interaction with angiotensin-converting enzyme 2 (ACE2). Notably, several SARS-CoV-2 strains have accrued mutations throughout the RBD that improve ACE2 binding affinity, enhance viral transmission and escape some existing antibody therapies. Here, we measure the binding affinity of 33 therapeutic antibodies against a large panel of SARS-CoV-2 variants and related strains of clinical significance using AlphaSeq, a high-throughput yeast mating-based assay to determine epitopic residues, determine which mutations result in loss of binding and predict how future RBD variants may impact antibody efficacy.

Paired heavy- and light-chain signatures contribute to potent SARS-CoV-2 neutralization in public antibody responses.

Understanding mechanisms of protective antibody recognition can inform vaccine and therapeutic strategies against SARS-CoV-2. We report a monoclonal antibody, 910-30, targeting the SARS-CoV-2 receptor-binding site for ACE2 as a member of a public antibody response encoded by IGHV3-53/IGHV3-66 genes. Sequence and structural analyses of 910-30 and related antibodies explore how class recognition features correlate with SARS-CoV-2 neutralization. Cryo-EM structures of 910-30 bound to the SARS-CoV-2 spike trimer reveal binding interactions and its ability to disassemble spike. Despite heavy-chain sequence similarity, biophysical analyses of IGHV3-53/3-66-encoded antibodies highlight the importance of native heavy:light pairings for ACE2-binding competition and SARS-CoV-2 neutralization. We develop paired heavy:light class sequence signatures and determine antibody precursor prevalence to be ∼1 in 44,000 human B cells, consistent with public antibody identification in several convalescent COVID-19 patients. These class signatures reveal genetic, structural, and functional immune features that are helpful in accelerating antibody-based medical interventions for SARS-CoV-2.

Antibody screening at reduced pH enables preferential selection of potently neutralizing antibodies targeting SARS-CoV-2.

Antiviral monoclonal antibody (mAb) discovery enables the development of antibody-based antiviral therapeutics. Traditional antiviral mAb discovery relies on affinity between antibody and a viral antigen to discover potent neutralizing antibodies, but these approaches are inefficient because many high affinity mAbs have no neutralizing activity. We sought to determine whether screening for anti-SARS-CoV-2 mAbs at reduced pH could provide more efficient neutralizing antibody discovery. We mined the antibody response of a convalescent COVID-19 patient at both physiological pH (7.4) and reduced pH (4.5), revealing that SARS-CoV-2 neutralizing antibodies were preferentially enriched in pH 4.5 yeast display sorts. Structural analysis revealed that a potent new antibody called LP5 targets the SARS-CoV-2 N-terminal domain supersite via a unique binding recognition mode. Our data combine with evidence from prior studies to support antibody screening at pH 4.5 to accelerate antiviral neutralizing antibody discovery.

Yeast display of MHC-II enables rapid identification of peptide ligands from protein antigens (RIPPA).

CD4+ T cells orchestrate adaptive immune responses via binding of antigens to their receptors through specific peptide/MHC-II complexes. To study these responses, it is essential to identify protein-derived MHC-II peptide ligands that constitute epitopes for T cell recognition. However, generating cells expressing single MHC-II alleles and isolating these proteins for use in peptide elution or binding studies is time consuming. Here, we express human MHC alleles (HLA-DR4 and HLA-DQ6) as native, noncovalent αß dimers on yeast cells for direct flow cytometry-based screening of peptide ligands from selected antigens. We demonstrate rapid, accurate identification of DQ6 ligands from pre-pro-hypocretin, a narcolepsy-related immunogenic target. We also identify 20 DR4-binding SARS-CoV-2 spike peptides homologous to SARS-CoV-1 epitopes, and one spike peptide overlapping with the reported SARS-CoV-2 epitope recognized by CD4+ T cells from unexposed individuals carrying DR4 subtypes. Our method is optimized for immediate application upon the emergence of novel pathogens.

Engineered ACE2 receptor traps potently neutralize SARS-CoV-2.

An essential mechanism for severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here, we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest-affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human immunoglobulin crystallizable fragment (Fc) domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2-pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50s) in the 10- to 100-ng/mL range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-using coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be predesigned for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated from convalescent patients.