Designing a Multi-Epitope Vaccine Candidate to MERS-CoV: An in silico Approach

Abstract

Background. Middle East Respiratory Syndrome Coronavirus (MERS-CoV), associated with severe respiratory illness, originates from the Middle East region. The virus is transmitted from animals to humans, with the dromedary camel serving as a significant reservoir. The virus's high fatality rate has spurred research into vaccine development and therapeutics. Objective. This study aimed to employ an in silico approach to design a potential vaccine candidate against MERS-CoV, focusing on the M protein as an antigen. Methods. The FASTA sequence of M protein was used to predict B cell and major histocompatibility complex class I and class II epitopes. The best epitopes were selected from these predicted epitopes. The vaccine candi­date's construct consisted of epitopes, linkers, and a tag. The sequence of the vaccine candidate's construct, consisting of 390 amino acids, was back-translated, optimized, and then inserted into a plasmid for cloning and expression using SnapGene. The 3D structure of the vaccine candidate is docked with TLR-4 receptor. Molecular dynamics simulation was run for this docked complex using GROMACS gmx, version 2021.4. Results. Through computational modeling and analysis, we developed a novel vaccine candidate with pro­mising structural and functional properties. Our results suggest that the designed vaccine candidate has the potential to induce a robust immune response. Conclusions. This in silico approach presents a promising MERS-CoV vaccine candidate designed to trigger both humoral and cellular immune responses. This candidate holds the potential to provide broad-spectrum protection against MERS-CoV.

Keywords

• MERS-CoV
• vaccine candidate's
• molecular docking
• molecular dynamics simulation
• bioinformatics approaches