基于表位的抗肺炎链球菌PspA疫苗设计的免疫信息学方法

IF 3.6 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Lincon Mazumder, Muhammad Shahab, Saidul Islam, Mahmuda Begum, Jonas Ivan Nobre Oliveira, Shamima Begum, Shahina Akter
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引用次数: 4

摘要

背景:肺炎链球菌(SPN)是导致呼吸道疾病(包括肺炎)的病原体,在全球范围内造成严重的健康危害和儿童死亡。抗生素是治疗SPN的一线药物,但目前SPN对几种抗生素出现耐药性。一种疫苗可以通过预防这种致命的病原体来克服这一全球性问题。湿实验室疫苗设计和开发的传统方法是一个紧张、漫长和昂贵的过程。相比之下,基于表位的硅疫苗设计可以节省时间、金钱和能源。本研究利用肺炎球菌表面蛋白A (PspA)作为SPN的主要毒力因子之一,设计了一种多表位疫苗。方法:检索PspA序列,进行系统发育分析,设计疫苗。利用多种生物信息学工具预测了PspA的CTL表位、HTL表位和LBL表位。通过对抗原原性、过敏原性和毒性评分的检测,选择最佳抗原表位构建疫苗,并对其理化和免疫学特性进行分析。随后,进行疫苗三维结构预测、优化和验证。通过分子对接、分子动力学模拟和免疫模拟,确保HLA与TLR4的结合。最后,进行密码子适配和芯片克隆,将其转移到合适的载体上。结果:构建的多表位疫苗与受体分子TLR4具有较强的结合亲和力。分子动力学模拟、c -免疫模拟、密码子自适应和芯片克隆分析验证了我们设计的疫苗是抗SPN的合适候选疫苗。结论:计算机分析证明该疫苗可作为抗肺炎链球菌的替代药物。指定的疫苗可以在湿实验室中进一步测试,并可以开发出新的疫苗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae.

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae.

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae.

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae.

Background: Streptococcus pneumoniae (SPN) is the agent responsible for causing respiratory diseases, including pneumonia, which causes severe health hazards and child deaths globally. Antibiotics are used to treat SPN as a first-line treatment, but nowadays, SPN is showing resistance to several antibiotics. A vaccine can overcome this global problem by preventing this deadly pathogen. The conventional methods of wet-laboratory vaccine design and development are an intense, lengthy, and costly procedure. In contrast, epitope-based in silico vaccine designing can save time, money, and energy. In this study, pneumococcal surface protein A (PspA), one of the major virulence factors of SPN, is used to design a multi-epitope vaccine.

Methods: For designing the vaccine, the sequence of PspA was retrieved, and then, phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes of PspA were all predicted by using several bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for the vaccine construction, and then, physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking, molecular dynamic simulation, and immune simulation were performed to ensure the binding between HLA and TLR4. Finally, codon adaptation and in silico cloning were performed to transfer into a suitable vector.

Results: The constructed multi-epitope vaccine showed a strong binding affinity with the receptor molecule TLR4. Analysis of molecular dynamic simulation, C-immune simulation, codon adaptation, and in silico cloning validated that our designed vaccine is a suitable candidate against SPN.

Conclusion: The in silico analysis has proven the vaccine as an alternative medication to combat against S. pneumoniae. The designated vaccine can be further tested in the wet lab, and a novel vaccine can be developed.

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