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DOI 10.1080/07391102.2021.1947381

Медицинская библиотека · Journal of biomolecular structure & dynamics · 2021

In silico design of epitope-based peptide vaccine against non-typhoidal Salmonella through immunoinformatic approaches.

Ali Md Chayan, Khatun Mst Shanzeda, Jahan Sultana Israt, Das Raju, Munni Yeasmin Akter, Rahman Md Mafizur, Dash Raju

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Non-typhoidal Salmonella (NTS) is one of the leading bacterial causes of many invasive human infections with a high antibiotic resistance profile. With this concern, the current study aimed to design an effective epitope-based peptide vaccine against NTS species as a successive and substitutive protective measure of invasive NTS disease. To design rationally, the current study considered a comprehensive in silico workflow combination of both immunoinformatics and molecular modeling approaches, including molecular docking and molecular dynamics (MD) simulation. We identified the two most promising T cell epitopes KVLYGIFAI and YGIFAITAL, and three B cell epitopes AAPVQVGEAAGS, TGGGDGSNT, and TGGGDGSNTGTTTT, in the outer membrane of NTS. Using these epitopes, a multiepitope vaccine was subsequently constructed along with appropriate adjuvant and linkers, which showed a good binding affinity and stability with toll-like receptor 2 (TLR2) in both molecular docking and MD simulation. Furthermore, in silico immune simulation described a strong immune response with a high number of antibodies, interferon-γ, and activated B and T cells. This study collectively suggests that predicted vaccine constructs could be considered potential vaccine candidates against common NTS species.Communicated by Ramaswamy H. Sarma.

Для цитирования: Ali Md Chayan, Khatun Mst Shanzeda, Jahan Sultana Israt, Das Raju, Munni Yeasmin Akter, Rahman Md Mafizur, Dash Raju. In silico design of epitope-based peptide vaccine against non-typhoidal Salmonella through immunoinformatic approaches.. Journal of biomolecular structure & dynamics. 2021. DOI: 10.1080/07391102.2021.1947381.

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