Viral evolution prediction identifies broadly neutralizing antibodies against existing and prospective SARS-CoV-2 variants

Abstract

Abstract Monoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain (RBD) are used to treat and prevent COVID-19. However, the rapid evolution of SARS-CoV-2 drives continuous escape from therapeutic mAbs. Therefore, the ability to identify broadly neutralizing antibodies (bnAbs) against future variants is needed. Here, we use deep mutational scanning (DMS) to predict viral RBD evolution and to select for mAbs neutralizing both existing and prospective variants. A retrospective analysis of 1,103 SARS-CoV-2 wildtype-elicited mAbs shows that this method can increase the probability of identifying effective bnAbs against the XBB.1.5 strain from 1% to 40% in an early pandemic setup. Among these bnAbs, BD55-1205 exhibited potent activity against all tested variants. Cryo-EM structural analyses revealed the receptor mimicry of BD55-1205, explaining its broad reactivity. Delivery of mRNA-LNPs encoding BD55-1205-IgG in mice resulted in ~5,000 serum NT 50 against XBB.1.5, HK.3.1, and JN.1 variants. Combining bnAb identification using viral evolution prediction with the versatility of mRNA delivery technology can enable rapid development of next-generation antibody-based countermeasures against SARS-CoV-2 and potentially other pathogens with pandemic potential.