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利用生物信息学方法预测内脏利什曼病的免疫原性肽组和多亚基疫苗。

Prediction of an immunogenic peptide ensemble and multi-subunit vaccine for Visceral leishmaniasis using bioinformatics approaches.

作者信息

Kupani Manu, Pandey Rajeev Kumar, Vashisht Sharad, Singh Satyendra, Prajapati Vijay Kumar, Mehrotra Sanjana

机构信息

Department of Human Genetics, Guru Nanak Dev University, Amritsar, 143005, Punjab, India.

Research & Development, Thermo Fisher Scientific, Bangalore, 560066, Karnataka, India.

出版信息

Heliyon. 2023 Nov 14;9(12):e22121. doi: 10.1016/j.heliyon.2023.e22121. eCollection 2023 Dec.

Abstract

Visceral Leishmaniasis (VL) is a neglected tropical disease of public health importance in the Indian subcontinent. Despite consistent elimination initiatives, the disease has not yet been eliminated and there is an increased risk of resurgence from active VL reservoirs including asymptomatic, post kala azar dermatitis leishmaniasis (PKDL) and HIV-VL co-infected individuals. To achieve complete elimination and sustain it in the long term, a prophylactic vaccine, which can elicit long lasting immunity, is desirable. In this study, we employed immunoinformatic tools to design a multi-subunit epitope vaccine for the Indian population by targeting antigenic secretory proteins screened from the proteome. Out of 8014 proteins, 277 secretory proteins were screened for their cellular location and proteomic evidence. Through NCBI BlastP, unique fragments of the proteins were cropped, and their antigenicity was evaluated. B-cell, HTL and CTL epitopes as well as IFN-ɣ, IL-17, and IL-10 inducers were predicted, manually mapped to the fragments and common regions were tabulated forming a peptide ensemble. The ensemble was evaluated for Class I MHC immunogenicity and toxicity. Further, immunogenic peptides were randomly selected and used to design vaccine constructs. Eight vaccine constructs were generated by linking random peptides with GS linkers. Synthetic TLR-4 agonist, RS09 was used as an adjuvant and linked with the constructs using EAAK linkers. The predicted population coverage of the constructs was ∼99.8 % in the Indian as well as South Asian populations. The most antigenic, nontoxic, non-allergic construct was chosen for the prediction of secondary and tertiary structures. The 3D structures were refined and analyzed using Ramachandran plot and Z-scores. The construct was docked with TLR-4 receptor. Molecular dynamic simulation was performed to check for the stability of the docked complex. Comparative immune simulation studies showed that the predicted construct elicited humoral and cell-mediated immunity in human host comparable to that elicited by Leish-F3, which is a promising vaccine candidate for human VL.

摘要

内脏利什曼病(VL)是印度次大陆一种具有公共卫生重要性的被忽视的热带病。尽管持续开展了消除行动,但该疾病尚未被消除,并且来自包括无症状、黑热病后皮肤利什曼病(PKDL)和HIV-VL合并感染个体在内的活跃VL储存库的复发风险有所增加。为了实现彻底消除并长期维持这一成果,一种能够引发持久免疫力的预防性疫苗是很有必要的。在本研究中,我们利用免疫信息学工具,通过靶向从蛋白质组中筛选出的抗原性分泌蛋白,为印度人群设计了一种多亚基表位疫苗。在8014种蛋白质中,筛选了277种分泌蛋白的细胞定位和蛋白质组学证据。通过NCBI BlastP对蛋白质的独特片段进行裁剪,并评估其抗原性。预测了B细胞、HTL和CTL表位以及IFN-γ、IL-17和IL-10诱导剂,手动将它们映射到片段上,并将共同区域制成表格,形成一个肽组。对该肽组进行了I类MHC免疫原性和毒性评估。此外,随机选择免疫原性肽并用于设计疫苗构建体。通过将随机肽与GS接头连接产生了8种疫苗构建体。合成的TLR-4激动剂RS09用作佐剂,并使用EAAK接头与构建体连接。这些构建体在印度以及南亚人群中的预测人群覆盖率约为99.8%。选择最具抗原性、无毒、无过敏的构建体来预测二级和三级结构。使用拉氏图和Z分数对3D结构进行优化和分析。将该构建体与TLR-4受体对接。进行分子动力学模拟以检查对接复合物的稳定性。比较免疫模拟研究表明,预测的构建体在人类宿主中引发的体液免疫和细胞介导免疫与Leish-F3相当,Leish-F3是一种有前景的人类VL疫苗候选物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6abf/10775901/f10d8be649f3/gr1.jpg

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