In silico analysis of the protein-protein interaction of the SARS-CoV-2 spike protein

Abstract

The pandemic caused by the SARS-CoV-2 virus has represented a global challenge with a significant impact on public health since its emergence in 2019. Understanding the interactions between this virus and the human immune system is essential for the development of new strategies more effective therapies and diagnoses. This study aimed to predict epitopes for SARS-CoV-2 T and B cells, as well as evaluate the interaction of the spike protein with other viral proteins, using bioinformatics methods. SARS-CoV-2 protein sequences were collected from UniProt. Epitopes for T cells were predicted in silico using specific HLA alleles from the Bahia population. Epitopes for B cells were predicted using the IEDB server with multiple methods based on amino acid features. Protein-protein interaction was analyzed using the STRING database. The result is 10,671 peptides related to various SARS-CoV-2 viral proteins, including the spike, essential for the infection and pathogenesis of COVID-19. In addition to spike, proteins such as ORF3a, ORF7a, and ORF8 showed significant immunogenic potential. Protein-protein interaction analysis revealed that proteases such as TMPRSS2 and TMPRSS11D are crucial for viral entry and are potential therapeutic targets. This study expands the understanding of the molecular interactions of SARS-CoV-2, highlighting new therapeutic targets and clinical complications associated with COVID-19. The results provide valuable insights for the development of targeted therapeutic strategies and improved diagnostics, contributing to the mitigation of the global pandemic.