From ZikV genome to vaccine: in silico approach for the epitope-based peptide vaccine against Zika virus envelope glycoprotein

被引:64
|
作者
Alam, Aftab [1 ]
Ali, Shahnawaz [1 ]
Ahamad, Shahzaib [2 ]
Malik, Md. Zubbair [1 ]
Ishrat, Romana [1 ]
机构
[1] Jamia Millia Islamia, Ctr Interdisciplinary Res Basic Sci, New Delhi 110025, India
[2] IFTM, Coll Engn & Technol, Dept Biotechnol, Moradabad, India
关键词
artificial neural network; epitopes; Immune Epitope Database; immunogenomics; MHC class; Zika virus; T-CELL EPITOPES; CLASS-II; PREDICTION; DESIGN; ALIGNMENT; ANTIBODY; ELICITS; BINDING; HUMANS; SERVER;
D O I
10.1111/imm.12656
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Zika virus (ZikV) has emerged as a potential threat to human health worldwide. A member of the Flaviviridae, ZikV is transmitted to humans by mosquitoes. It is related to other pathogenic vector-borne flaviviruses including dengue, West Nile and Japanese encephalitis viruses, but produces a comparatively mild disease in humans. As a result of its epidemic outbreak and the lack of potential medication, there is a need for improved vaccine/drugs. Computational techniques will provide further information about this virus. Comparative analysis of ZikV genomes should lead to the identification of the core characteristics that define a virus family, as well as its unique properties, while phylogenetic analysis will show the evolutionary relationships and provide clues about the protein's ancestry. Envelope glycoprotein of ZikV was obtained from a protein database and the most immunogenic epitope for T cells and B cells involved in cell-mediated immunity, whereas B cells are primarily responsible for humoral immunity. We mainly focused on MHC class I potential peptides. YRIMLSVHG, VLIFLSTAV and MMLELDPPF, GLDFSDLYY are the most potent peptides predicted as epitopes for CD4(+) and CD8(+) T cells, respectively, whereas MMLELDPPF and GLDFSDLYY had the highest pMHC-I immunogenicity score and these are further tested for interaction against the HLA molecules, using in silico docking techniques to verify the binding cleft epitope. However, this is an introductory approach to design an epitope-based peptide vaccine against ZikV; we hope that this model will be helpful in designing and predicting novel vaccine candidates.
引用
收藏
页码:386 / 399
页数:14
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