Robust Prediction of Relative Binding Energies for Protein-Protein Complex Mutations Using Free Energy Perturbation Calculations.

Computational free energy-based methods have the potential to significantly improve throughput and decrease costs of protein design efforts. Such methods must reach a high level of reliability, accuracy, and automation to be effectively deployed in practical industrial settings in a way that impacts protein design projects. Here, we present a benchmark study for the calculation of relative changes in protein-protein binding affinity for single point mutations across a variety of systems from the literature, using free energy perturbation (FEP+) calculations.

Modular basis for potent SARS-CoV-2 neutralization by a prevalent VH1-2-derived antibody class.

Antibodies with heavy chains that derive from the VH1-2 gene constitute some of the most potent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies yet identified. To provide insight into whether these genetic similarities inform common modes of recognition, we determine the structures of the SARS-CoV-2 spike in complex with three VH1-2-derived antibodies: 2-15, 2-43, and H4. All three use VH1-2-encoded motifs to recognize the receptor-binding domain (RBD), with heavy-chain N53I-enhancing binding and light-chain tyrosines recognizing F486.