SARS-CoV-2 in silico binding affinity to human leukocyte antigen (HLA) Class II molecules predicts vaccine effectiveness across variants of concern (VOC)

Abstract

Abstract There is widespread concern about the clinical effectiveness of current vaccines in preventing Covid-19 caused by SARS-CoV-2 Variants of Concern (Williams in Lancet Respir Med 29:333–335, 2021; Hayawi in Vaccines 9:1305, 2021), including those identified at present (Alpha, Beta, Gamma, Delta, Omicron) and possibly new ones arising in the future. It would be valuable to be able to predict vaccine effectiveness for any variant. Here we offer such an estimate of predicted vaccine effectiveness for any SARS-CoV-2 variant based on the amount of overlap of in silico high binding affinity of the variant and Wildtype spike glycoproteins to a pool of frequent Human Leukocyte Antigen Class II molecules which are necessary for initiating antibody production (Blum et al. in Annu Rev Immunol 31:443–473, 2013). The predictive model was strong (r = 0.910) and statistically significant (P = 0.013).