The novel design of a multi-epitope vaccine candidate against the dengue virus using advanced immunoinformatics and structural analysis.

IF 0.8 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Mohsen Karami Fath
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引用次数: 0

Abstract

Background: Dengue virus (DENV) remains a major public health challenge with limited vaccine options, and current licensed vaccines exhibit restricted efficacy and safety concerns in certain populations. Advanced immunoinformatics approaches offer opportunities for designing multi-epitope vaccines targeting conserved and immunogenic regions of viral proteins. Objective: To design and computationally evaluate a novel multi-epitope vaccine targeting the Envelope (E) and Non-Structural protein 1 (NSP1) of DENV-1 and DENV-2 using integrated immunoinformatics and structural bioinformatics. Methods: CTL, HTL, and B-cell epitopes were predicted from the E and NSP1 proteins and screened for antigenicity, non-allergenicity, and non-toxicity. High-affinity epitopes were linked with appropriate spacers and adjuvants (human [Formula: see text]-defensin-3 or 50S ribosomal protein L7/L12) to construct two vaccine candidates. Molecular docking with TLR2/TLR4, molecular dynamics (MD) simulations, MM/GBSA binding free energy analysis, population coverage assessment, codon optimization, and immune simulations were conducted. Control docking using scrambled peptides was included to evaluate binding specificity. Results: Both vaccine constructs were predicted to be stable, soluble, non-allergenic, and non-toxic. Vaccine 2 showed higher antigenicity (VaxiJen: 0.6127) and stronger TLR2 binding ([Formula: see text]: -110.37[Formula: see text]kcal/mol), whereas vaccine 1 demonstrated better solubility and TLR4 interaction stability. Control docking with scrambled peptides produced less favorable binding energies, supporting specificity. MD simulations confirmed structural stability, and immune simulations predicted robust humoral and cellular responses with high IFN-[Formula: see text] production. Population coverage exceeded 98% in most regions. Conclusion: The designed multi-epitope vaccines demonstrate promising immunogenic potential in silico. Experimental validation is required to confirm safety, efficacy, and protective capability against multiple DENV serotypes.

利用先进的免疫信息学和结构分析,设计了一种针对登革热病毒的多表位候选疫苗。
背景:登革热病毒(DENV)仍然是一个重大的公共卫生挑战,疫苗选择有限,目前许可的疫苗在某些人群中表现出有限的有效性和安全性问题。先进的免疫信息学方法为设计针对病毒蛋白保守区和免疫原区的多表位疫苗提供了机会。目的:利用综合免疫信息学和结构生物信息学设计并计算评价一种针对DENV-1和DENV-2包膜蛋白(E)和非结构蛋白1 (NSP1)的新型多表位疫苗。方法:从E和NSP1蛋白中预测CTL、HTL和b细胞表位,并进行抗原性、非过敏性和无毒性筛选。高亲和力表位与适当的间隔物和佐剂(人[配方:见文]-防御素-3或50S核糖体蛋白L7/L12)连接,构建两种候选疫苗。与TLR2/TLR4分子对接、分子动力学(MD)模拟、MM/GBSA结合自由能分析、种群覆盖率评估、密码子优化和免疫模拟。利用混乱肽进行对照对接以评估结合特异性。结果:两种疫苗结构都是稳定的、可溶的、无过敏性和无毒的。疫苗2表现出更高的抗原性(VaxiJen: 0.6127)和更强的TLR2结合([公式:见文]:-110.37 kcal/mol),而疫苗1表现出更好的溶解性和TLR4相互作用的稳定性。与混乱肽的控制对接产生不太有利的结合能,支持特异性。MD模拟证实了结构稳定性,免疫模拟预测了高IFN-产生的强大的体液和细胞反应。大多数地区人口覆盖率超过98%。结论:所设计的多表位疫苗在硅片上具有良好的免疫原性。需要进行实验验证,以确认安全性、有效性和针对多种DENV血清型的保护能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Bioinformatics and Computational Biology
Journal of Bioinformatics and Computational Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.10
自引率
0.00%
发文量
57
期刊介绍: The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.
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