Leveraging the immunoinformatics approach for designing the SARS-CoV-2 omicron-specific antigenic cassette of mRNA vaccine

Abstract

Emergence of SARS-CoV-2 Omicron variant has presented a significant challenge to global health, demanding rapid development of mRNA-based vaccines. The mRNA-guided vaccine platforms offer various advantages over traditional vaccine platforms. The mRNA by nature is a short-lived molecule that guides the cells to manufacture antigenic proteins. In the present work, we have created an omicron spike antigenic protein sequence characterized by base composition analysis, modeling, and docking with the ACE-2 receptor. Further, we predicted the B-cell and T-cell epitopes followed by antigenicity, toxicity, and allergenicity. Finally, the protein was reverse translated, codon-optimized, and encoding mRNA sequence was checked for its stability by predicting the secondary structures. A comprehensive examination of in-silico data revealed 628.2 as a potent antigenic candidate that was finally used in Gemcovac®-OM, a heterologous booster mRNA vaccine for COVID-19.