Stabilization of the SARS-CoV-2 receptor binding domain by protein core redesign and deep mutational scanning.

Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen-specific antibodies at multiple distinct epitopes. This is a challenge, as stability enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study, we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L receptor binding domain mutations, maintains recognition by the receptor ACE2 and a panel of different anti-receptor binding domain monoclonal antibodies, is between 1 and 2°C more thermally stable than the original receptor binding domain using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original receptor binding domain. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes. We envision that this strategy may be particularly powerful for cases when there are multiple or unknown binding sites.

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.

Identification of SARS-CoV-2 S RBD escape mutants using yeast screening and deep mutational scanning.

Here, we describe a protocol to identify escape mutants on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) receptor-binding domain (RBD) using a yeast screen combined with deep mutational scanning. Over 90% of all potential single S RBD escape mutants can be identified for monoclonal antibodies that directly compete with angiotensin-converting enzyme 2 for binding. Six to 10 antibodies can be assessed in parallel. This approach has been shown to determine escape mutants that are consistent with more laborious SARS-CoV-2 pseudoneutralization assays. For complete details on the use and execution of this protocol, please refer to Francino-Urdaniz et al. (2021).

One-shot identification of SARS-CoV-2 S RBD escape mutants using yeast screening.

The potential emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) escape mutants is a threat to the efficacy of existing vaccines and neutralizing antibody (nAb) therapies. An understanding of the antibody/S escape mutation landscape is urgently needed to preemptively address this threat. Here we describe a rapid method to identify escape mutants for nAbs targeting the S receptor binding site. We identified escape mutants for five nAbs, including three from the public germline class VH3-53 elicited by natural coronavirus disease 2019 (COVID-19) infection. Escape mutations predominantly mapped to the periphery of the angiotensin-converting enzyme 2 (ACE2) recognition site on the RBD with K417, D420, Y421, F486, and Q493 as notable hotspots. We provide libraries, methods, and software as an openly available community resource to accelerate new therapeutic strategies against SARS-CoV-2.