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• W4200617498 abstract "Marburg, a RNA virus (MRV), is responsible for causing hemorrhagic fever that affects humans and non-human primates. World Health Organization (WHO), National Institutes of Health (NIH) and Centre of Disease Control and Prevention (CDC) considered this as an extremely dangerous virus, thus categorised as risk group 4, category A priority pathogen and category “A” bioterrorism agent, respectively. Despite of all these alarming concerns, no prophylaxis arrangements are available against this virus till date. In fact, the construction of immunogenic vaccine candidates by traditional molecular immunology methods is time consuming and very expensive. Considering these concerns, herein, we have designed CD4 + T Cell multiepitopes against MRV using in silico approach. The pin-point criteria of the screening and selection of potential epitopes are, non-mutagenic, antigenic, large HLAs coverage, non-toxic and high world population coverage. This kind of methodology and investigations can precisely reduce the expenditure and valuable time for experimental planning in development of vaccines in laboratories. In current scenario, researchers are frequently using in silico approaches to speed up their vaccine-based lab studies. The computational studies are highly valuable for the screening of large epitope dataset into smaller one prior to in vitro and in vivo confirmatory analyses." @default.
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• W4200617498 date "2022-02-01" @default.
• W4200617498 modified "2023-10-15" @default.
• W4200617498 title "In silico CD4 + T-cell multiepitope prediction and HLA distribution analysis for Marburg Virus—A strategy for vaccine designing" @default.
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• W4200617498 doi "https://doi.org/10.1016/j.jksus.2021.101751" @default.
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