Structure-Guided Design of Therapeutic Antibodies Targeting SARS-CoV-2 Omicron Variants.

The ongoing evolution of SARS-CoV-2, particularly the emergence of Omicron subvariants, compromised the effectiveness of many therapeutic antibodies. In this study, we employed a structure-guided computational design strategy to systematically optimize the COV2-2196 antibody for improved neutralization of Omicron variants. Through iterative rounds of computational design and experimental validation, we identified key paratope mutations that restored and enhanced antibody binding and neutralization potency against resistant viral strains. Cryo-EM structural analysis revealed the molecular basis for these improvements, highlighting how targeted modifications can accommodate epitope changes introduced by viral evolution. Our approach demonstrates that effective antibody optimization can be achieved using accessible computational resources, providing a practical framework for rapid therapeutic development. These findings underscore the potential of structure-based design to address challenges posed by viral antigenic drift and support the development of broadly effective antibody therapeutics for emerging infectious diseases.