VP1蛋白结构特征预测及功能分析

Structure prediction and function insight of viral protein 1

目的本文基于生物信息学方法对EV71VP1(enterovirus type71viral protein1)蛋白进行系统结构与功能预测分析。方法应用GOR4(Garnier-Osguthorpe-Robson方法)、HNN(Hierarchical人工神经网络预测法)、PHD(多重比对人工神经网络比对预测结构法)、Predator(单序列分析人工神经网络预测结构法)、SOPMA(改进型自我优化预测结构法)等方法预测EV71VP1外壳蛋白的二级结构,SWISSMODEL服务器的同源建模方法构建EV71VP1的三级结构模型,并分析亲水性、柔韧性、抗原指数、表面可能性。结果预测结果表明EV71VP1的二级结构以无规卷曲为主,其次为β-片层和α-螺旋,无β-转角。同源建模获得与VP1具有42%的序列一致性的已知结构的编号为1bev的蛋白质,进行VP1的同源建模并得到良好的建模评估效果;预测了可能的EV71VP1抗原性区域。结论综合多种策略预测EV71VP1的二级结构和三级结构,为进一步研究开发相关药品以防治EV71感染提供理论基础。

Objective To predict the tertiary structure of enterovirus type 71 viral protein 1 based on bioinformatics. Methods The secondary structure of enterovirus type 71 （ EV71 ） viral protein was analyzed using GOR4 （ Garnier-Osguthorpe-Robson method）, HNN （hierarchical neural network method）, PHD （predicting protein structure with multiple alignments by profile-based neural networks）, Predator（protein secondary structure prediction from single sequence or a set of sequences）, SOPMA （improved self-optimized prediction method）predictive program based on the web,and the tertiary structure was predicted by SWISS MODEL based on homology modeling, and hydrophilicity regions, flexible regions, antigen regions and surface regions were predicted by using various methods. Results The secondary structure of enterovirus type 71 viral protein predicted by GOR4, HNN,PHD, Predator, SOPMA predictive program showed that random coils, β-sheet and α-helix were the main structural type, but no β-turn. The homology modeling of VP1 was more than 90% of the residues in the favorable region. Potential antigen region of EV71 VP1 was predicted. Conclusion These results provide a theoretieal foundation and further evidence in support of predicting EV71 VP1 secondary structure and tertiary structure, and further studying and developing related drugs to EV71 infection control.