Epitope based vaccine prediction for SARS-COV-2 by deploying immuno-informatics approach

Amit Joshi; Bhuwan Chandra Joshi; M Amin-Ul Mannan; Vikas Kaushik

doi:10.1016/j.imu.2020.100338

Epitope based vaccine prediction for SARS-COV-2 by deploying immuno-informatics approach

Inform Med Unlocked. 2020:19:100338. doi: 10.1016/j.imu.2020.100338. Epub 2020 Apr 29.

Authors

Amit Joshi¹, Bhuwan Chandra Joshi², M Amin-Ul Mannan¹, Vikas Kaushik¹

Affiliations

¹ Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India.
² Department of Biological Sciences and Biotechnology, Surajmal Agarwal Private Girls PG Degree College Kiccha, Kumaun University, Nainital, Uttarakhand, India.

Abstract

A new virus termed SARS-COV-2 (causing COVID-19 disease) can exhibit a progressive, fatal impact on individuals. The World Health Organization (WHO) has declared the spread of the virus to be a global pandemic. Currently, there are over 1 million cases and over 100,000 confirmed deaths due to the virus. Hence, prophylactic and therapeutic strategies are promptly needed. In this study we report an epitope, ITLCFTLKR, which is biochemically fit to HLA allelic proteins. We propose that this could be used as a potential vaccine candidate against SARS-COV-2. A selected putative epitope and HLA-allelic complexes show not only better binding scores, but also RMSD values in the range of 0-1 Å. This epitope was found to have a 99.8% structural favorability as per Ramachandran-plot analysis. Similarly, a suitable range of IC₅₀ values and population coverage was obtained to represent greater validation of T-cell epitope analysis. Stability analysis using MDWeb and half-life analysis using the ProtParam tool has confirmed that this epitope is well-selected. This new methodology of epitope-based vaccine prediction is fundamental and fast in application, ad can be economically beneficial and viable.

Keywords: Epitope; HLA-Alleles; Immuno-informatics; SARS-COV-2; Simulation; Vaccine.