Identification of Potential Immunogenic Epitopes Against SARS-CoV-2 Using In-Silico Method: An Immunoinformatics Study

ABSTRACT

Background: Severe acute respiratory syndrome (SARS-CoV-2), a zoonotic virus, is the pathogenic causal agent for the ongoing pandemic. Despite the lethality of the disease, there are no therapeutic agents available to combat the disease outbreak, and the vaccines currently accessible are insufficient to control the widespread, fast-mutating virus infection. Objective(s) This research study focuses on determining potential epitopes by examining the entire proteome of the SARS-CoV-2 virus using an in-silico approach. Method(s) To develop a vaccine for the deadly virus, researchers screened the whole proteome of the SARS-CoV-2 virus for potential epitopes in order to find a powerful peptide candidate that is both unique and fulfils the vaccine's objective. It is mandatory to identify the suitable B-cell and T-cell epitopes of the observed SARS-CoV-2 surface glycoprotein (QKN61229.1). These epitopes were subjected to various tests, including antigenicity, allergenicity, and other physicochemical proper-ties. The T-cell epitopes that met the criteria were subjected to population coverage analysis. It helped in better understanding epitope responses to the target population, computing peptide con-servancy, and clustering epitopes based on sequence match, MHC binding, and T-cell restriction sites. Lastly, the interactions between the T-cell receptor (TCR) and a peptide-MHC were studied to thoroughly understand MHC restriction to design a peptide-vaccine. Result(s) The findings revealed that four B-cell epitopes, two MHC-I epitopes, and four MHC-II epitopes qualified for all of the tests and so have antigen affinity. Conclusion(s) Based on the results obtained from this study, the estimated peptides are promising candidates for peptide-vaccine design and development. Copyright © 2022 Bentham Science Publishers.