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Chandipura vesiculovirus (CHPV) is a fast-emerging virus that causes acute encephalitis with a high death rate. Because of its extensive prevalence in African and Asian countries, this infection has become a global hazard, and there is an urgent need to create an effective and non-allergenic vaccine or appropriate treatment to combat it. A vaccine candidate is offered utilizing a computational technique in this study. To build a potential vaccine candidate, viral protein sequences were acquired from the National Center for Biotechnology Information database and evaluated with several bioinformatics techniques to identify B-cell and T-cell epitopes. V1 was shown to be superior in terms of various physicochemical qualities, as well as highly immunogenic and non-allergic. Molecular docking revealed that the CHPV vaccine construct had a greater binding affinity with human Toll-like receptors (TLR-3 and TLR-8) and that it was stable in molecular dynamics simulations. MEC-CHPV was in silico cloned in the pET28a (+) expression vector using codon optimization. The current research identifies potential antigenic epitopes that could be used as vaccine candidates to eradicate the CHPV. This in-silico development of a CHPV vaccine with multiple epitopes could open the path for future rapid laboratory tests. Copyright © 2021 Elsevier Ltd. All rights reserved.


Anik Banik, Shiuly Sinha, Sheikh Rashel Ahmed, Mohammed Mehadi Hassan Chowdhury, Shamsunnahar Mukta, Nadim Ahmed, Nurul Amin Rani. Immunoinformatics approach for designing a universal multiepitope vaccine against Chandipura Virus. Microbial pathogenesis. 2022 Jan;162:105358

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PMID: 34902539

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