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基于疫苗设计目标预测尼帕病毒的抗原表位:一项免疫信息学探索性研究

Anticipation of Antigenic Sites for the Goal of Vaccine Designing Against Nipah Virus: An Immunoinformatics Inquisitive Quest.

作者信息

Sharma Suraj Kumar, Srivastava Shivani, Kumar Ajay, Srivastava Vivek

机构信息

Department of Biotechnology, Rama University Uttar Pradesh, Kanpur, 209217 India.

出版信息

Int J Pept Res Ther. 2021;27(3):1899-1911. doi: 10.1007/s10989-021-10219-7. Epub 2021 May 11.

Abstract

With time, the Nipah virus has been proved as a fatal and dangerous pathogen for humanity. Nipah virus has its origin from bats and severely affects the respiratory as well as neurological organs. Regular outbreaks and unavailability of proper treatment for Nipah virus infection, demands the designing of vaccine for this disease. This prediction study was conducted to explore B cell epitopes from the Nipah virus's proteome using the immunoinformatics approach. In this curious quest of anticipation of antigenic sites for the peptide vaccine for the Nipah virus, nine NV-B strain proteins were retrieved for further series of investigations. After sequential refining through immunoinformatics approaches, a total of 26 epitopes was selected to perform molecular modeling and docking. PEPstrMOD and Swiss model, respectively performed 3D modeling of epitopes with their respective alleles. Based on minimum binding energy, four epitopes viz. LHLGNFVRR, LNLSPLIQR, YHNMSPINR and FRRNNAIAF were predicted as promiscuous B cell epitopes. Based on low binding affinity and high population coverage worldwide, epitope LHLGNFVRR was finally selected. Increased Stability of the LHLGNFVRR- HLA DRB_1301 complex during simulation studies exhibit it as the most promising vaccine bidder. So complex of LHLGNFVRR- HLA DRB_1301 has shown most significance result for vaccine and for further validation and confirmation, wet lab and clinical trials can provide the potential of predicted peptides for the subunit vaccine.

摘要

随着时间的推移,尼帕病毒已被证明是对人类致命且危险的病原体。尼帕病毒起源于蝙蝠,会严重影响呼吸和神经器官。由于尼帕病毒感染经常爆发且缺乏适当的治疗方法,因此需要设计针对这种疾病的疫苗。本预测研究采用免疫信息学方法,从尼帕病毒的蛋白质组中探索B细胞表位。在这一探寻尼帕病毒肽疫苗抗原位点的过程中,检索了9种NV-B株蛋白以进行进一步的系列研究。通过免疫信息学方法进行序列优化后,共选择了26个表位进行分子建模和对接。PEPstrMOD和瑞士模型分别对表位及其各自的等位基因进行了3D建模。基于最小结合能,预测了4个表位,即LHLGNFVRR、LNLSPLIQR、YHNMSPINR和FRRNNAIAF为混杂性B细胞表位。基于低结合亲和力和全球高人群覆盖率,最终选择了表位LHLGNFVRR。模拟研究中LHLGNFVRR - HLA DRB_1301复合物稳定性的增加表明它是最有前景的疫苗候选物。因此,LHLGNFVRR - HLA DRB_1301复合物在疫苗方面显示出最显著的结果,为进一步验证和确认,湿实验室和临床试验可以提供预测肽用于亚单位疫苗的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae41/8112743/640d842ac299/10989_2021_10219_Fig1_HTML.jpg

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