Current Computer-Aided Drug DesignCurrent Computer-Aided Drug DesignCurrent Computer-Aided Drug Design1573-40991875-6697Bentham Science64399010.2174/1573409919666230612125440ChemistryResearch ArticleDesigning a Multi-epitope Vaccine against the SARS-CoV-2 Variant based on an Immunoinformatics ApproachFarhaniIbrahiminfo@benthamscience.netYamchiAhadinfo@benthamscience.netMadanchiHamidinfo@benthamscience.netKhazaeiVahidinfo@benthamscience.netBehrouzikhahMehdiinfo@benthamscience.netAbbasiHamidrezainfo@benthamscience.netSalehiMohammadinfo@benthamscience.netMoradiNilufarinfo@benthamscience.netSanamiSamirainfo@benthamscience.netDepartment of Medical Biotechnology, School of Advanced Technologies in Medicine, Golestan University of Medical SciencesDepartment of Plant Breeding and Biotechnology, Gorgan University of Agricultural Science and Natural ResourcesDrug Design and Bioinformatics Unit, Department of Medical Biotechnology,, Biotechnology Research Center, Pasteur Institute of IranDepartment of Medical Microbiology, School of Medicine, Golestan University of Medical SciencesDepartment of Medical Genetics, School of Advanced Technologies in Medicine, Golestan University of Medical SciencesDepartment of Medical Biotechnology, School of Advanced Technologies in Medicine,, Golestan University of Medical SciencesDepartment of Plant Breeding and Biotechnology, Shahrekord University of Medical Sciences0103202420327429007012025Copyright ©; 2024, Bentham Science Publishers2024Bentham Science Publishershttps://rjeid.com/1573-4099/article/view/643990

Background:SARS-CoV-2 is a life-threatening virus in the world. Scientific evidence indicates that this pathogen will emerge again in the future. Although the current vaccines have a pivotal role in the control of this pathogen, the emergence of new variants has a negative impact on their effectiveness.

Objective:Therefore, it is urgent to consider the protective and safe vaccine against all subcoronavirus species and variants based on the conserved region of the virus. Multi-epitope peptide vaccine (MEV), comprised of immune-dominant epitopes, is designed by immunoinformatic tools and it is a promising strategy against infectious diseases.

Methods:Spike glycoprotein and nucleocapsid proteins from all coronavirus species and variants were aligned and the conserved region was selected. Antigenicity, toxicity, and allergenicity of epitopes were checked by a proper server. To robust the immunity of the multi-epitope vaccine, cholera toxin b (CTB) and three HTL epitopes of tetanus toxin fragment C (TTFrC) were linked at the N-terminal and C-terminal of the construct, respectively. Selected epitopes with MHC molecules and the designed vaccines with Toll-like receptors (TLR-2 and TLR-4) were docked and analyzed. The immunological and physicochemical properties of the designed vaccine were evaluated. The immune responses to the designed vaccine were simulated. Furthermore, molecular dynamic simulations were performed to study the stability and interaction of the MEV-TLRs complexes during simulation time by NAMD (Nanoscale molecular dynamic) software. Finally, the codon of the designed vaccine was optimized according to Saccharomyces boulardii.

Results:The conserved regions of spike glycoprotein and nucleocapsid protein were gathered. Then, safe and antigenic epitopes were selected. The population coverage of the designed vaccine was 74.83%. The instability index indicated that the designed multi-epitope was stable (38.61). The binding affinity of the designed vaccine to TLR2 and TLR4 was -11.4 and -11.1, respectively. The designed vaccine could induce humoral and cellular immunity.

Conclusion:In silico analysis showed that the designed vaccine is a protective multi-epitope vaccine against SARS-CoV-2 variants.

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