Design of a Multi-epitope Peptide Vaccine against SARS-CoV-2 based on Immunoinformatics Data

Autor: Alireza Habibi, Amin Azizan, Yahya Ehteshaminia, Farhad Jadidi-Niaragh, Ehsan Enderami, Esmaeil Akbari, Saeid Abediankenari, Hadi Hassannia
Jazyk: English<br />Persian
Rok vydání: 2020
Předmět:
Zdroj: Journal of Mazandaran University of Medical Sciences, Vol 30, Iss 190, Pp 126-132 (2020)
Druh dokumentu: article
ISSN: 1735-9260
1735-9279
Popis: Background and purpose: In 2019, the world has witnessed the emergence of a virus that caused acute respiratory distress syndrome in human with high mortality rates (approximately 3.7%). So far, no effective treatment has been proven against COVID-19. This study aimed at designing a multi-epitope vaccine combining several T-cell and B-cell epitopes of the SARS-CoV-2. Materials and methods: Based on immunoinformatics strategies, B-cell and T-cell epitopes were predicted using immune Epitope Database and Analysis Resource (IEDB). Then, the appropriate predicted epitopes were joined to each other by suitable linkers, and the multi-epitope vaccine constructed was suggested as a vaccine candidate against SARS-CoV-2. Results: In this study, 28 B-cell epitopes and 33 T-cell epitopes were predicted. Then, to design the multi epitope vaccine, 5 epitopes were used from the virion surface of spike protein and one epitope was used from intravirion region of the Envelope, Membrane, and Nucleocapsid proteins that later on were joined with flexible glycine linker. Conclusion: Based on the immunoinformatics results obtained, it seems that different epitopes from SARS-CoV-2 structural proteins have high ability to stimulate humoral and cellular immune responses, so the multi-epitope vaccine designed with these epitopes, can help to accelerate the production of effective vaccines against COVID-19.
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