Epitope‐based peptide vaccine design against spike protein (S) of novel coronavirus (2019-nCoV): an immunoinformatics approach

Abstract

Abstract Background Recently the global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated a significant need on identifying drugs or vaccines to prevent or reduce clinical infection of Coronavirus disease – 2019 (COVID-19). In this study, immuno-informatics tools were utilized to design a potential multi-epitopes vaccine against SARS-CoV-2 spike S protein. Structural analysis for SARS-CoV-2 spike S protein was also conducted. Method: SARS-CoV-2 spike S protein sequences were retrieved from the GeneBank of National Central Biotechnology Information (NCBI). Immune Epitope Database (IEDB) tools were used to predict B and T cell epitopes, to evaluate their allergenicity, toxicity and cross- reactivity and to calculate population coverage. Protparm sever was applied to determine protein characterization of spike protein and predicted epitopes. Molecular docking for the proposed MHCI epitopes were also achieved against Tall like Receptor (TLR8) receptors and HLA-B7 allele. Result Immuno-informatics analysis of S protein using IEDB identified only one B cell epitope 1054QSAPH1058 as linear, surface and antigenic. Although 1054QSAPH1058 was estimated as non-allergic and non-toxic, it showed protein instability. Moreover, around 45 discontinuous epitopes were also recognized as different exposed surface area. In MHCI methods, six conserved stable and safe epitopes (898FAMQMAYRF906, 258WTAGAAAYY266 and 2FVFLVLLPL10, 202 KIYSKHTPI210, 712IAIPTNFTI720 and 1060VVFLHVTYV1068) were identified. These epitopes showed strong interaction when docked with TLR8 and HLA-B7 allele especially 1060VVFLHVTYV1068 and 2FVFLVLLPL10 epitopes. Three epitopes were also predicted (898FAMQMAYRF906, 888FGAGAALQI896 and 342FNATRFASV350) using MHCII methods. Furthermore, the potential multi-epitopes were acquired by assessing allergenicity, toxicity and cross-reactivity to prevent autoimmunity. Conclusion The multi-epitopes vaccine was predicted based on Bioinformatics tools that may provide reliable results in a shorter time and at a lower cost. However, further in vivo and in vitro studies are required to validate their effectiveness.