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利用免疫信息学、分子建模和 QM:MM 方法鉴定马亚罗病毒结构蛋白上的混杂 T 细胞表位。

Identification of promiscuous T cell epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches.

机构信息

Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, 59072-970 Natal, RN, Brazil.

Departamento de Microbiologia e Parasitologia, Universidade Federal do Rio Grande do Norte, 59072-970 Natal, RN, Brazil.

出版信息

Infect Genet Evol. 2021 Jul;91:104826. doi: 10.1016/j.meegid.2021.104826. Epub 2021 Mar 27.

DOI:10.1016/j.meegid.2021.104826
PMID:33781966
Abstract

The Mayaro virus (MAYV) belongs to genus Alphavirus (family Togaviridae) and has been reported in several countries, especially in tropical regions of America. Due to its outbreaks and potential lack of medication, an effective vaccine formulation is strongly required. This study aimed to predict promiscuous T cell epitopes from structural polyproteins of MAYV using an immunoinformatics approach. For this purpose, consensus sequences were used to identify short protein sequences capable of binding to MHC class I and class II alleles. Our analysis pointed out 4 MHC-I/TCD8+ and 21 MHC-II/TCD4+ epitopes on capside (1;3), E1 (2;5), E2 (1;10), E3 (0;2), and 6 K (0;1) proteins. These predicted epitopes were characterized by high antigenicity, immunogenicity, conservancy, non-allergenic, non-toxic, and good population coverage rate values for North and South American geographical areas. Afterwards, we used the crystal structure of human toll-like receptor 3 (TLR3) ectodomain as a template to predict, through docking essays, the placement of a vaccine prototype at the TLR3 receptor binding site. Finally, classical and quantum mechanics/molecular mechanics (QM:MM) computations were employed to improve the quality of docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. These results provide important insights into the advancement of diagnostic platforms, the development of vaccines, and immunotherapeutic interventions.

摘要

马亚罗病毒(MAYV)属于甲病毒属(黄病毒科),已在多个国家报告,特别是在美洲的热带地区。由于其爆发和潜在缺乏药物治疗,强烈需要一种有效的疫苗制剂。本研究旨在使用免疫信息学方法从 MAYV 的结构多蛋白中预测广谱 T 细胞表位。为此,使用共识序列来鉴定能够与 MHC Ⅰ类和Ⅱ类等位基因结合的短蛋白序列。我们的分析指出了衣壳蛋白(1;3)、E1 蛋白(2;5)、E2 蛋白(1;10)、E3 蛋白(0;2)和 6K 蛋白(0;1)上的 4 个 MHC-I/TCD8+和 21 个 MHC-II/TCD4+表位。这些预测的表位具有高抗原性、免疫原性、保守性、非变应原性、非毒性和对北美和南美的高人群覆盖率值。之后,我们使用人 toll 样受体 3(TLR3)胞外域的晶体结构作为模板,通过对接研究预测疫苗原型在 TLR3 受体结合位点的位置。最后,我们使用经典和量子力学/分子力学(QM:MM)计算来提高对接计算的质量,模拟的 QM 部分通过使用密度泛函理论(DFT)形式完成。这些结果为诊断平台的发展、疫苗的开发和免疫治疗干预提供了重要的见解。

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