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• W4200111549 endingPage "105358" @default.
• W4200111549 startingPage "105358" @default.
• W4200111549 abstract "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." @default.
• W4200111549 created "2021-12-31" @default.
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• W4200111549 date "2022-01-01" @default.
• W4200111549 modified "2023-09-27" @default.
• W4200111549 title "Immunoinformatics approach for designing a universal multiepitope vaccine against Chandipura Virus" @default.
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• W4200111549 doi "https://doi.org/10.1016/j.micpath.2021.105358" @default.
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