Volume 10, Issue 3 (12-2023)
jhbmi 2023, 10(3): 269-293 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Sarvmeili J, Baghban Kohnehrouz B, Gholizadeh A, Ofoghi H, Shanehbandi D. Introduction of an Efficient Multiepitopic Vaccine Against Different SARS-CoV-2 Strains: Reverse Vaccinology. jhbmi 2023; 10 (3) :269-293
URL: http://jhbmi.ir/article-1-796-en.html
URL: http://jhbmi.ir/article-1-796-en.html
Javad Sarvmeili 
, Bahram Baghban Kohnehrouz * , Ashraf Gholizadeh , Hamideh Ofoghi , Dariush Shanehbandi
, Bahram Baghban Kohnehrouz * , Ashraf Gholizadeh , Hamideh Ofoghi , Dariush Shanehbandi
PhD in Molecular Biology and Biotechnology, Associate Professor, Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
Abstract: (457 Views)
Introduction: In recent years, COVID-19 has been recognized as a health threat. Despite vaccination, people still get the disease because the new variants have mutations in their genomes that allow them to bind to host receptors and evade the immune system’s responses. Therefore, the main aim of this study was to use bioinformatics tools to introduce a rapid and practical vaccine to fight against these diverse mutations in different SARS-CoV-2 strains.
Method: To epitopes mapping, 32 different spike protein variants were retrieved. We then used the Immune Epitope Database (IEDB), NetCTL, and NetMHCIIpan to predict T and B cell epitopes. The vaccine based on protected epitopes was evaluated in terms of antigenicity, allergenicity, toxicity, solubility, physicochemical properties, population coverage, and secondary structure with relevant servers. Modeling using Robetta and docking with Toll-like receptor (TLR3) were performed using Cluspro, PatchDock, and FireDock, respectively.
Results: After detailed evaluations, all the results confirmed the optimal quality of the vaccine. According to further investigations, this structure is similar to native proteins and there is a stable and strong interaction between the vaccine and the receptor. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli.
Conclusion: Based on the obtained results, the designed multi-epitope vaccine can serve as a prophylactic candidate against SARS-CoV-2.
Method: To epitopes mapping, 32 different spike protein variants were retrieved. We then used the Immune Epitope Database (IEDB), NetCTL, and NetMHCIIpan to predict T and B cell epitopes. The vaccine based on protected epitopes was evaluated in terms of antigenicity, allergenicity, toxicity, solubility, physicochemical properties, population coverage, and secondary structure with relevant servers. Modeling using Robetta and docking with Toll-like receptor (TLR3) were performed using Cluspro, PatchDock, and FireDock, respectively.
Results: After detailed evaluations, all the results confirmed the optimal quality of the vaccine. According to further investigations, this structure is similar to native proteins and there is a stable and strong interaction between the vaccine and the receptor. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli.
Conclusion: Based on the obtained results, the designed multi-epitope vaccine can serve as a prophylactic candidate against SARS-CoV-2.
Keywords: Dynamic Simulation, Immunoinformatics, Immune Simulation, Molecular Docking, Multi-epitope Vaccine
Type of Study: Original Article |
Subject:
Bioinformatics
Received: 2023/07/6 | Accepted: 2023/11/25
Received: 2023/07/6 | Accepted: 2023/11/25
Audio File [MP3 975 KB] (14 Download)
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
