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 B.1.1.7, P1, and B.1.351, 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.