Computational design of a broad-spectrum multi-epitope vaccine candidate against seven strains of human coronaviruses

Avinash Kumar, Ekta Rathi, Suvarna Ganesh Kini

Research output: Contribution to journalArticlepeer-review


Spike (S) proteins are an attractive target as it mediates the binding of the SARS-CoV-2 to the host through ACE-2 receptors. We hypothesize that the screening of the S protein sequences of all the seven known HCoVs would result in the identification of potential multi-epitope vaccine candidates capable of conferring immunity against various HCoVs. In the present study, several machine learning-based in-silico tools were employed to design a broad-spectrum multi-epitope vaccine candidate targeting the S protein of seven known strains of human coronaviruses. Herein, multiple B-cell epitopes and T-cell epitopes (CTL and HTL) were predicted from the S protein sequences of all seven known HCoVs. Post-prediction they were linked together with an adjuvant to construct a potential broad-spectrum vaccine candidate. Secondary and tertiary structures were predicted and validated, and the refined 3D-model was docked with an immune receptor. The vaccine candidate was evaluated for antigenicity, allergenicity, solubility, and its ability to achieve high-level expression in bacterial hosts. Finally, the immune simulation was carried out to evaluate the immune response after three vaccine doses. The designed vaccine is antigenic (with or without the adjuvant), non-allergenic, binds well with TLR-3 receptor and might elicit a diverse and strong immune response.

Original languageEnglish
Article number240
Journal3 Biotech
Issue number9
Publication statusPublished - 09-2022

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Environmental Science (miscellaneous)
  • Agricultural and Biological Sciences (miscellaneous)


Dive into the research topics of 'Computational design of a broad-spectrum multi-epitope vaccine candidate against seven strains of human coronaviruses'. Together they form a unique fingerprint.

Cite this