Structural and energetic profiling of SARS-CoV-2 receptor binding domain antibody recognition and the impact of circulating variants

• Main Authors: Gowthaman, R. (Author), Guest, J.D (Author), Mittra, I. (Author), Pierce, B.G (Author), Quackenbush, J. (Author), Taherzadeh, G. (Author), Yin, R. (Author)
• Format: Article
• Language: English
• Published: Public Library of Science 2021
• Subjects: angiotensin converting enzyme 2; Antibodies, Viral; antibody response; Article; binding affinity; binding site; Binding Sites; biology; chemistry; cluster analysis; Cluster Analysis; Computational Biology; computer model; coronavirus spike glycoprotein; COVID-19; cryoelectron microscopy; genetics; human; Humans; hydrogen bond; metabolism; Models, Molecular; molecular docking; molecular model; mutagenesis; phylogenetic tree; protein binding; Protein Binding; protein fingerprinting; receiver operating characteristic; receptor binding; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; Spike Glycoprotein, Coronavirus; spike protein, SARS-CoV-2; virology; virus antibody; virus infectivity; virus neutralization; virus strain; X ray diffraction
• Online Access: View Fulltext in Publisher

 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. Copyright: © 2021 Yin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.