Predição de novas variantes do SARS-CoV-2 a partir da análise in silico de subvariantes ômicron dominantes no Brasil

Abstract

COVID-19 affected the entire world, causing one of the most extensive pandemics in history, and due to its rapid spread, it allowed the emergence of mutations in the SARSCoV-2 genome, generating new variants of concern. Omicron is currently the dominant variant of concern globally, and Brazil is no exception. However, subvariants emerged from it and became strains that reached high rates of infections and prevalence in the country: BA.2 at the beginning of 2022 and soon after the appearance of BA.4 and BA.5. In this scenario, vaccine escape is a significant concern, so bioinformatic analyses of prediction and proteins have been conducted to detect new targets and regions of interest for developing new immunoprophylactic strategies. Thus, this study aimed to simulate and predict possible new Omicron variants through the dominant subvariants in Brazil. In silico analyses of structure, molecular similarity, mutation tracking, as well as conserved regions and epitopes, and molecular docking were performed. As a result of the analysis of the subvariants (BA.2, BA.4, BA.5, XAG), high genetic identity with the original variant, promising epitopes as vaccine candidates, and significant structural variation were observed. For docking, BA.5 showed higher affinity for the hACE2 receptor, suggesting greater transmission potential, and structurally, XAG exhibited the highest susceptibility to relevant mutations.