5种高危型HPVE7蛋白B细胞表位的预测

发布时间：2018-04-27 05:22

本文选题：人乳头瘤病毒 + E蛋白　；参考：《中国病原生物学杂志》2017年01期

【摘要】：目的预测并分析我国人群常见人乳头瘤病毒HPV16、18、33、52与58亚型E7蛋白的线性B细胞表位。方法在NCBI数据库中获取5种高危型HPVE7蛋白氨基酸序列,采用ClustalX2软件进行多序列比对;运用ExPASY服务器SOPMA和GOR4法预测二级结构,采用Kyte-Doolittle方案和Hopp-Wood方案预测亲水性;运用Bepipred和ABCpred软件预测B细胞表位,辅以抗原性指数,综合评判几率较大的B细胞优势表位。结果综合多参数分析,5种HPV亚型的B细胞表位均集中在蛋白质的N端2-50位附近,其中预测的HPV16与52亚型的第16-21位氨基酸序列一致性为100%,均为QPETTD;HPV16型第28-41位(LNDSSEEEDEIDGP)与HPV52型第28-38位(LGDSSDEEDTD)的氨基酸序列一致性为78%;HPV16型第42-50位(AGQADEPRA),HPV33型第31-46位(SSDEDEGLDRP),HPV52型第36-46位(DTDGVDRPDGQ)和HPV58型第73-78位(TTTDVR)为各自的特异B细胞表位。结论生物信息学方法预测5种HPV的B细胞表位均集中在蛋白质的N端2-50位附近,同时具有特异的B细胞表位(18型除外),可为宫颈癌的诊断、预防和新型疫苗的研制提供参考。
[Abstract]:Objective to predict and analyze the linear B cell epitopes of human papillomavirus (HPV16), HPV16, HPV16, HPV16, HPV16, and E7, subtype E7, which are common in human papillomavirus in China. Methods five kinds of high risk HPVE7 protein amino acid sequences were obtained from NCBI database, and the multiple sequence alignment was carried out by ClustalX2 software. The secondary structure was predicted by ExPASY server SOPMA and GOR4, and the hydrophilicity was predicted by Kyte-Doolittle and Hopp-Wood schemes. B cell epitopes were predicted by Bepipred and ABCpred software, supplemented by antigenicity index, and B cell dominant epitopes with higher probability were comprehensively evaluated. Results the B cell epitopes of five HPV subtypes were all located at the N-terminal 2-50 position of the protein. The predicted amino acid sequence of HPV16 and 52 subtype is 100, and the amino acid sequence of QPETTDV / HPV16 / LNDSSEEEDEIDGP) and HPV52 / 28-38 / GDSSDEEDTD) is 78-50 / 42-50 of AGQADEPRAPRACEN / HPV33 and 36-46 / 36-46 of HPV58 and 73-78 / 73-78 / 73-78, respectively. TTTDVR is their specific B cell epitopes. Conclusion the bioinformatics method for predicting the B cell epitopes of five kinds of HPV is concentrated near the N-terminal 2-50 position of the protein, and has a specific B-cell epitope type 18, which can be used as a reference for the diagnosis, prevention and development of new vaccines for cervical cancer.
【作者单位】：济南大学山东省医学科学院医学与生命科学学院;山东省医学科学院山东省医药生物技术研究中心;山东青岛正方元信公共卫生检测有限公司;
【分类号】：R737.33

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