Structural modeling and conserved epitopes prediction against SARS-COV-2 structural proteins for vaccine development

Abstract Background: Coronavirus disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Corona virus 2 (SARS-COV-2) was first diagnosed in December 2019, Wuhan, China. Little is known about this new virus and it has the potential to cause severe illness and pneumonia in some people, therefore the development of an effective vaccine is highly desired.Methods: Immunoinformatics and statistical approaches were used in this study to forecast B- and T- cell epitopes for the SARS-COV-2 structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) that may play a key role in eliciting immune response against COVID-19. Different types of B cell epitopes (linear as well as discontinuous) and T cell (MHC class I and MHC class II) were determined. Moreover, their antigenicity and allergenicity were also estimated.Results: The antigenic B-cell epitopes exposed to the outer surface were screened out and 23 linear B cell epitopes were selected. “SPTKLNDLCFTNVY” had the highest antigenicity score among B cell epitopes. The T-cell epitopes bound to multiple alleles, antigenic, non-allergen, non-toxic, and conserved in the protein sequence were shortlisted. In total, 16 epitopes (9 from MHC class I and 7 from MHC class II) were selected. Among the T-cell epitopes, MHC class I (IPFAMQMAYRFN) and MHC class II (VTLACFVLAAVYRIN) were classified as strongly antigenic. Digestion analysis verified the safety and stability of the peptides predicted during this study. Furthermore, docking analyses of predicted peptides showed significant interactions with the HLA-B7 allele.Conclusion: The putative antigen epitopes identified in this study may serve as vaccine candidates and can help to eliminate/control growing health threat of COVID-19.