Introduction of a Novel Poly-Epitope Vaccine Against Mycobacterium tuberculosis Infection; an Immunoinformatics Approach

Author:

Rashidian Ehsan,Forouharmehr Ali,Jaydari AminORCID

Abstract

Background: Tuberculosis is known as one of the most dangerous diseases caused by Mycobacterium tuberculosis. Although different strategies have been applied to prevent this disease, it is still considered a killer disease in the world. Objectives: This project was conducted to design a novel poly-epitope vaccine based on three antigenic proteins against tuberculosis. Methods: To design a poly-epitope vaccine, first, the antigenic proteins of Mycobacterium tuberculosis, including Dnak, FbpA, and katG were selected from the database. Then, B cell, MHCI, and MHCII epitopes of the antigenic proteins were predicted using reliable online tools. The best-predicted epitopes were applied to assemble a poly-epitope vaccine. The physicochemical features, the antigenicity of the whole vaccine, and the protein structures of the designed poly-epitope vaccine were evaluated by the most precise tools. Also, the coding DNA sequence of the vaccine was adapted for expression in the prokaryotic system, then, it was theoretically cloned in pET32a (+) vector. Results: The results revealed that the molecular weight and length of the designed poly-epitope vaccine were 32 kDa and 308 amino acids, respectively. The protein structure results demonstrated that the designed poly-epitope vaccine contained 19.48% alpha-helix and 73.05% random coil. Also, the results showed that 92.2% of amino acid residues were located in the favored region. Finally, it was clarified that the antigenicity of the designed poly-epitope vaccine was 12333. Conclusions: According to the results of the current project, it seems that the designed poly-epitope vaccine can be an appropriate candidate to control tuberculosis.

Publisher

Briefland

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3