Bebtelovimab-bound SARS-CoV-2 RBD mutants: resistance profiling and validation with escape mutations, clinical results, and viral genome sequences.

The dynamic evolution of SARS-CoV-2 variants necessitates ongoing advancements in therapeutic strategies. Despite the promise of monoclonal antibody (mAb) therapies like bebtelovimab, concerns persist regarding resistance mutations, particularly single-to-multipoint mutations in the receptor-binding domain (RBD). Our study addresses this by employing interface-guided computational protein design to predict potential bebtelovimab-resistance mutations. Through extensive physicochemical analysis, mutational preferences, precision-recall metrics, protein-protein docking, and energetic analyses, combined with all-atom, and coarse-grained molecular dynamics (MD) simulations, we elucidated the structural-dynamics-binding features of the bebtelovimab-RBD complexes. Identification of susceptible RBD residues under positive selection pressure, coupled with validation against bebtelovimab-escape mutations, clinically reported resistance mutations, and viral genomic sequences enhances the translational significance of our findings and contributes to a better understanding of the resistance mechanisms of SARS-CoV-2.