Computational design of a multi-epitope-based vaccine targeting the BF.7 Omicron variant of SARS-CoV-2

Abstract

In recent times, the SARS-CoV-2 virus has been observed to cause a serious threat to the world through its high permissive mutations by adapting itself to the host environment, which is a time to design an effective vaccine that could be able to produce immune response to fight against the virus. An Immunoinformatics approach was employed to conduct a high-throughput analysis aimed at developing a multi-epitope-based vaccine that specifically targets the BF.7 Omicron variant, which is currently a variant of concern. The essential aspect for the successful development of a vaccine lies in identifying B-cell and T-cell epitopes that exhibit both antigenic features, capable of eliciting a defensive immune response, while also possessing non-allergenic characteristics to prevent any harmful allergic reactions. These epitopes are essential for the development of vaccines because they aid in the immune system's ability to identify and attack certain infections without inducing unfavorable allergic reactions. The Docking and MD simulation studies have shown structural stability and Toll-like receptors with chosen vaccine architecture interact strongly. The in-silico immune simulation boosted the research study confirming the efficiency of the vaccination that has the potential to stimulate immunological responses by producing antibodies to not only targeting the specific VOC, BF.7 Omicron variant but also other omicron sublineages. Overall, the computational study have provided strong evidences to the designed vaccine construct which needs to be confirmed through the experiemental study.