Objective: One of the effective approaches for the treatment of viral diseases is to use neutralizing antibodies. REGN10987 antibody (imdevimab) binds to the receptor-binding domain (RBD) of the SARS-CoV-2 S-protein, preventing the virus from binding to its receptor, angiotensin-converting enzyme 2, thereby blocking entry into cells. Although REGN10987 is effective against the Wuhan, Alpha, and Delta variants of the virus, it has lost potency against the Omicron BA.1 (B.1.1.529) and subsequent variants. This evasion is partially caused by the N440K mutation of the RBD, which is located at the interface with the light chain of REGN10987. We propose a variant of REGN10987 containing the N33D point mutation in the light chain, which should enhance interaction with the Omicron RBD by establishing an additional K440–D33 salt bridge. Methods: Structure and stability of complexes formed by the Wuhan and Omicron BA.1 RBD variants with REGN10987-FabN33D were investigated using molecular dynamics (MD) and dissociation free energy (ΔG) calculations for the RBD/Fab complexes, by umbrella sampling and potential of mean force analysis (US-PMF). Results and Discussion: Significant variations in the structure of RBD/Fab complexes during MD resulted in a wide range of calculated ΔG values. Nevertheless, the results suggest that the N33D substitution increases REGN10987-Fab affinity for the Omicron BA.1 RBD and complex’s stability, while preserving its affinity for the Wuhan RBD. Conclusions: The results suggest that computer-aided design could be used to create neutralizing antibodies to treat existing and emerging virus strains. However, new fast and reliable computational approaches are needed to quantitatively assess biomolecule affinity.
Nolde et al. (Mon,) studied this question.