基于氨基酸序列协同进化编码的蛋白质热点残基预测

项目名称： 基于氨基酸序列协同进化编码的蛋白质热点残基预测

项目编号： No.61300058

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 陈鹏

作者单位： 安徽大学

项目金额： 27万元

中文摘要： 蛋白质经常与其他蛋白质发生相互作用(PPI)以执行相关的功能,是蛋白质组学中亟待解决的关键问题。本项目提出PPI位点/Hotspots的形成与氨基酸的进化环境密切相关的假设，从蛋白质的一级序列出发，研究PPI位点/Hotspots在疏水力等物理化学环境上的进化关系，以探索PPI的规律与本质。首先，研究基于疏水作用力等理化特征的氨基酸残基的进化谱，并由此对蛋白质的氨基酸残基进行相关协同进化编码；然后，构建相互作用位点的motif进化库，在此motif进化库中BLAST搜索发现目标蛋白质可能的作用位点以及Hotspots；同时开发多核空间多输入均衡数据集的集成学习方法来预测PPI位点及Hotspots；最后融合两种预测结果，以达到更好的预测效果。本项目的成果可以为了解蛋白质生理功能的实现机制和治疗相关疾病的药物靶点设计提供理论上的依据。

中文关键词： 蛋白质相互作用；热点残基；集成分类器；蛋白质编码；系数表达和多核学习融合

英文摘要： Protein always interacts with other proteins (Protein-Protein Interaction, PPI) to help perform functions, which is almost a vital issue to be solved urgently in proteomics. The solution of the issue can be used to understand the essence of life acitivities and further push the development of whole bioinformatics. The proposal presents a hypotheses that there might have high relationship between evolutionary context of amino acid residues and the formation of PPI sites/Hotspots. The proposal is based on amino acid sequence only, investigates the evolutionary context of PPI sites with respect to hydrophobicity and other physicochemical properties of residues, and further discovers the essence of PPI. First, study the co-evolutionary profile of amino acid residues based on hydrophobicity and other physicochemical characters, and further encode amino acids in protein chain by the use of correlation methods. Second, construct the motif library for PPI sites/Hot spots and search for homology PPI sites/Hotspots of target protein in the motif library by running BLAST program. Further, develop ensemble method of multi-kernels with balanced multi-input datasets for predicting PPI sites/Hotspots. Finally, obtain better predictions by combining the two prediction results. As a result, the proposal can used to understanding

英文关键词： Protein interaction；Hotspots；Classifier ensemble；Protein encoding；Sparse representation and multi-kernel learning