Immunoinformatics approach in designing SARS-CoV-2 vaccine from experimentally determined SARS-CoV T-cell epitopes

Abstract

The rapid transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resulted in the coronavirus disease 2019 pandemic. This has caused a global health emergency that warrants accelerated vaccine development. Herein, immunoinformatics was utilized in evaluating experimentally validated SARS-CoV CD4+ and CD8+ epitopes retrieved from the database as a potential vaccine against SARS-CoV-2. The protein sequences of SARS-CoV-2 were retrieved. Then, multiple sequence alignments and protein variability analysis of retrieved were conducted to obtain highly conserved sequences. SARS-CoV epitopes having a 100% overlap with the highly conserved protein sequence of SARS-CoV-2 were further analyzed to identify major histocompatibility complex (MHC) allele binders. Epitopes with significant matches to known human protein sequences were excluded to avoid cross-reactivity. Population coverage (PC) for an optimized set of CD4+ and CD8+ epitopes was also estimated. SARS-CoV-2 epitopes were docked with structures of identified MHC alleles. Binding energy and dissociation constant were calculated to analyze the stability of the epitope-MHC complex. To further evaluate the stability of interaction, the root mean square deviation plot was obtained using molecular dynamics simulation. This work identified a highly conserved potential SARS-CoV-2 vaccine comprising three CD4+ epitopes GAALQIPFAMQMAYRF, MAYRFNGIGVTQNVLY, and QALNTLVKQLSSNFGAI with worldwide PC of 81.81% and seven CD8+ epitopes RLNEVAKNL, VLNDILSRL, GMSRIGMEV, LLLDRLNQL, MEVTPSGTWL, RRPQGLPNNTASWFT, and LQLPQGTTL with global PC of 89.49%.