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Immunoinformatics aided-design of novel multi-epitope based peptide vaccine against Hendra henipavirus through proteome exploration

Informatics in Medicine Unlocked(2021)

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摘要
Hendra henipavirus (HeV) is an emerging zoonotic bat-borne paramyxovirus that is capable of causing severe public health complications in humans. It promotes both respiratory and neurological disorders in humans as well as in horses. Currently, there are no therapeutics or vaccines available against the deadly HeV. We aimed to design a potent and novel prophylactic chimeric vaccine against HeV through an immunoinformatics approach. A proteome-wide screening was performed to identify the antigenic proteins followed by cytotoxic T-lymphocyte (CTL), linear B-lymphocyte (LBL), and helper T-lymphocyte (HTL) epitopes identification, conservancy analysis, population coverage, molecular docking and in silico simulation of both cellular and humoral immune response. A total of 17 T and B-cell epitopes (7 CTL, 5 HTL, and 5 LBL) were identified for vaccine design from the highest antigenic proteins, namely glycoprotein, fusion protein, and nucleoprotein. The proposed vaccine was found to be highly immunogenic, antigenic, non-toxic, non-allergenic, and stable, and could be efficient against HeV. Moreover, disulfide engineering and codon adaptation were employed to escalate stability and efficient expression in E. coli. Molecular docking and dynamics simulation analysis revealed the stability and strong affinity of the proposed vaccine towards the TL4 receptor. The immune simulation data confirmed elevated response of both B and T-cells against the vaccine subunit. The designed vaccine according to our in silico data is potent enough to elucidate substantial immune response and therefore can be considered as a potential immunogenic agent to control HeV infection. However, further experimental validation and clinical trials are required to confirm its efficacy and safety.
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关键词
Hendra henipavirus,Multi-epitope vaccine,Immunoinformatics,Dynamics simulation
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