Deciphering the immunogenic T-cell epitopes from spike protein of SARS-CoV-2 concerning the diverse population of India

Abstract

Scientists are rigorously looking for an efficient vaccine against the current pandemic due to the SARS-CoV-2 virus. The reverse vaccinology approach may provide us with significant therapeutic leads in this direction and further determination of T-cell/B-cell response to antigen. In the present study, we conducted a population coverage analysis referring to the diverse Indian population. From the Immune epitope database (IEDB), HLA- distribution analysis was performed to find the most promiscuous T-cell epitope out of In silico determined epitope of Spike protein from SARS-CoV-2. Epitopes were selected based on their binding affinity with the maximum number of HLA alleles belonging to the highest population coverage rate values for the chosen geographical area in India. 404 cleavage sites within the 1288 amino acids sequence of spike glycoprotein were determined by NetChop proteasomal cleavage prediction suggesting the presence of adequate sites in the protein sequence for cleaving into appropriate epitopes. For population coverage analysis, 179 selected epitopes present the projected population coverage up to 97.45% with 56.16 average hit and 15.07 pc90. 54 epitopes are found with the highest coverage among the Indian population and highly conserved within the given spike RBD domain sequence. Among all the predicted epitopes, 9-mer TRFASVYAW and RFDNPVLPF along with 12-mer LLAGTITSGWTF and VSQPFLMDLEGK epitopes are observed as the best due to their decent docking score and best binding affinity to corresponding HLA alleles during MD simulations. Outcomes from this study could be critical to design a vaccine against SARS-CoV-2 for a different set of populations within the country.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2
• population coverage
• HLA
• reverse vaccinology
• spike glycoprotein
• T-cell
• epitopes

Acknowledgement

MD thanks to the DST-INSPIRE Faculty award (2017), Govt. of India.

Disclosure statement

I, as the corresponding author, declare, on behalf of all authors of the paper, that no financial conflict of interest exists in relation to the work described.

Consent to participate

All authors have given their consent to participate in this work.

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All authors has given their consent to publish this work.

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Author’s contributions

MD has conceptualized and supervised the work. SD has performed the experiments. VK and KD have performed the MD simulation. MD and SD have analysed the data and written the manuscript.