免疫信息学方法预测针对中东呼吸综合征冠状病毒的T/B细胞抗原表位

doi:10.20047/j.issn1673-7210.2023.18.03

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摘要目的通过免疫信息学方法预测针对中东呼吸综合征冠状病毒（MERS-CoV）的T/B细胞抗原表位。方法从NCBI获取S蛋白序列后，运用MEGA11进行多序列比对及系统发育树构建，Expasy Protparam分析其理化性质，SOPMA预测其二级结构。随后对S蛋白建模并进行模型验证。再通过NetCTL-1.2、NetMHC pan EL 4.1和IEDB预测杀伤性T细胞（CTL）表位，NetMHCⅡpan-4.0、IFNepitope和IL-4pred预测辅助性T细胞表位（HTL），ABCpred和BepiPred-2.0预测线性B细胞表位（LBL），ElliPro工具预测构象B细胞表位（CBL）。最后对上述预测得到的线性表位进行抗原性、致敏性和毒性预测。结果 S蛋白序列保守性较高，且来自不同国家的100个MERS-CoV S蛋白可以装进同一系统进化枝。理化性质分析结果显示，S蛋白亲水性总平均值为-0.078，在哺乳动物网织红细胞中半衰期约为30 h。模型验证结果显示构建的S蛋白模型是合理的。从S蛋白中预测得到具有抗原性、无致敏性和无毒性的CTL表位2个、HTL表位2个，LBL表位15个。ElliPro工具预测得到的CBL表位5个。结论 MERS-CoV的S蛋白是亲水性的稳定蛋白；综合多种生物信息学方法可以预测得到T/B细胞抗原表位，对开发针对MERS-CoV的多肽疫苗具有重要借鉴意义。

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	黄转青1　　孙琦1　　杨森1　　李渊源1　　石浩源1　　张莹1　　龚辉2　　徐风华1

关键词 ：中东呼吸综合征冠状病毒, T/B细胞表位, 抗原表位, 生物信息学免疫表位预测

Abstract：Objective To predict the T/B cell epitopes against middle east respiratory syndrome coronavirus (MERS-CoV) by immunoinformatics methods. Methods After obtaining S protein sequence from NCBI, MEGA11 was used to compare multiple sequences and construct phylogenetic tree. The physicochemical properties of S protein were analyzed by Expasy Protparam and its secondary structure was predicted by SOPMA. Subsequently, S protein was modeled and verified. Killer T cell (CTL) epitopes were predicted by NetCTL-1.2, NetMHC pan EL 4.1, and IEDB, while helper T cell (HTL) epitopes were predicted by NetMHCⅡpan-4.0, IFNepitope, and IL-4pred. ABCpred and BepiPred-2.0 predict linear B cell epitopes (LBL), and the ElliPro tool predicts conformational B cell epitopes (CBL). Finally, the antigenicity, sensitization, and toxicity of the predicted linear epitopes were predicted. Results The S protein sequence was highly conserved, and 100 MERS-CoV S proteins from different countries could fit into the same phylogenetic clade. The results of physicochemical analysis showed that the total mean value of hydrophilicity of S protein was -0.078, and the half-life of S protein in mammalian reticulocytes was about 30 h. The model verification results showed that the model of S protein was reasonable. Two CTL epitopes, two HTL epitopes, and 15 LBL epitopes with antigenicity, non-allergenicity and non-toxicity were predicted from S protein. The ElliPro tool predicted five CBL epitopes. Conclusion The S protein of MERS-CoV is a hydrophilic stable protein. T/B cell antigen epitopes can be predicted by combining various bioinformatics methods, which has important reference significance for the development of polypeptide vaccine against MERS-CoV.

Key words： Middle east respiratory syndrome coronavirus T/B cell epitopes Bioinformatics Prediction of immune epitopes

基金资助:国家自然科学基金面上项目（82171814）。

通讯作者: 徐风华（1969.7-），女，博士，研究员；研究方向：多肽疫苗。

作者简介: 黄转青（1998.6-），女，解放军医学院2020级药学专业在读硕士研究生；研究方向：多肽疫苗。

引用本文:

黄转青1　　孙琦1　　杨森1　　李渊源1　　石浩源1　　张莹1　　龚辉2　　徐风华1. 免疫信息学方法预测针对中东呼吸综合征冠状病毒的T/B细胞抗原表位[J]. 中国医药导报, 2023, 20(18): 15-19.
HUANG Zhuanqing1 SUN Qi1 YANG Sen1 LI Yuanyuan1 SHI Haoyuan1 ZHANG Ying1 GONG Hui1 XU Fenghua1. Prediction of T/B cell epitopes specific to middle east respiratory syndrome coronavirus by immunoinformatics method. 中国医药导报, 2023, 20(18): 15-19.

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