The SARS-CoV-2 pandemic highlights the need for a detailed molecular understanding of protective antibody responses. This is underscored by the emergence and spread of SARS-CoV-2 variants, including Alpha (B.1.1.7) and Delta (B.1.617.2), some of which appear to be less effectively targeted by current monoclonal antibodies and vaccines. Here we report a high resolution and comprehensive map of antibody recognition of the SARS-CoV-2 spike receptor binding domain (RBD), which is the target of most neutralizing antibodies, using computational structural analysis. With a dataset of nonredundant experimentally determined antibody-RBD structures, we classified antibodies by RBD residue binding determinants using unsupervised clustering. We also identified the energetic and conservation features of epitope residues and assessed the capacity of viral variant mutations to disrupt antibody recognition, revealing sets of antibodies predicted to effectively target recently described viral variants. This detailed structure-based reference of antibody RBD recognition signatures can inform therapeutic and vaccine design strategies. Author summary The ongoing COVID-19 pandemic, and the emergence of SARS-CoV-2 variants that evade antibodies induced by vaccines and natural infection, highlights the need for assessment of key molecular and structural features of immune responses against the SARS-CoV-2 virus. Using a large nonredundant set of structures of monoclonal antibodies in complex with the SARS-CoV-2 spike receptor binding domain, we performed analysis of molecular determinants of antibody recognition of the spike glycoprotein, mapping key residues through analysis of atomic contacts and computational modeling to identify molecular hotspots. Clustering was used to identify four major groups of antibodies based on target residues, and we compared epitope conservation and impact of SARS-CoV-2 variant mutations, showing that certain sets of antibodies predicted to be affected by those variants, while others are capable of targeting escape variants. This analysis can serve as a useful reference for vaccine and immunotherapeutic studies, and we provide updated classifications of antibodies to the research community on our CoV3D site.
【초록키워드】 Structure, Vaccine, immune response, Mutation, Vaccines, Neutralizing antibodies, antibody, SARS-CoV-2 pandemic, COVID-19 pandemic, monoclonal antibody, Vaccine design, mutations, spike glycoprotein, SARS-CoV-2 variant, Delta, B.1.617.2, SARS-CoV-2 virus, monoclonal antibodies, variants, Receptor binding domain, Spread, Viral, SARS-CoV-2 variants, B.1.1.7, RBD, immune responses, therapeutic, Research, Clustering, Community, Viral variants, Alpha, target, dataset, molecular, group, natural infection, epitope, viral variant, binding, Protective antibody, Analysis, structures, Structural analysis, Contact, high resolution, determinant, computational modeling, Author, complex, residue, residues, Unsupervised clustering, epitope conservation, protective antibody responses, feature, highlight, described, predicted, identify, performed, affected, was used, atomic, less, evade, disrupt, the SARS-CoV-2, the SARS-CoV-2 virus, 【제목키워드】 antibody, SARS-CoV-2 receptor, binding domain, circulating variant,