项目名称: 帕金森疾病相关蛋白质相互作用网络研究
项目编号: No.21205019
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 分析化学
项目作者: 李占潮
作者单位: 广东药学院
项目金额: 24万元
中文摘要: 本项目以帕金森疾病(PD)相关蛋白质相互作用网络(PPIN)的构建与分析为研究目的,建立基于盒计数法的PPIN分形维数计算方法,在蛋白质、模体和蛋白质复合物水平上,研究PD相关PPIN的分形特征。采用图论和分形理论,研究蛋白质复合物的拓扑结构性质与功能之间的关系。基于蛋白质复合物的拓扑结构等性质,建立改进型蚁群等仿生优化算法与支持向量机、随机森林的联用技术,从PD相关PPIN中挖掘潜在的蛋白质复合物,并预测其真实性。基于基因本体论、代谢路径等注释信息,研究与PD相关蛋白质、蛋白质复合物以及代谢路径,为致病机理的研究提供参考。本项目的研究不仅有助于从系统和网络水平上理解蛋白质复合物以及PPIN在PD致病机制中的作用,发现与PD相关的信号转导和代谢调控等路径,而且有助于研究PD的致病机理和寻找新的药物靶标,为疾病诊断和治疗,以及新药设计提供理论依据,具有重要的理论意义和实用价值。
中文关键词: 蛋白质相互作用网络;蛋白质复合物;随机森林;遗传算法;图论
英文摘要: The purpose of the project is to construct and study the Parkinson's disease (PD) associated protein-protein interaction network (PPIN). In the project, a novel fractal dimenson calculation method is proposed and used to research the topology strucure of the PPIN at the levels of protein, motif and protein complex. The relationships between topology structural of protein complex and function of protein complex are studied based on the graph theory and fractal geometry theory. The improved ant optimization algorithm, particle swarm optimziation algorithm and genetic algorithm are proposed and utilized to identify potential protein complex from the PPIN based on the topology structure and physicochemical property of the protein complex. Support vector machine and random forest algorithm are adopted to predict the authenticity of the potential protein complex. Based on the resources of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), chemometrics techniques and methods are used to study the PD associated metabolic pathway, protein and protein complex at the level of network. And new target for treatment of the PD are identified. The project will not only help the understanding of the pathogenesis of the PD at levels of system and network, but also help the finding of the new drug target. And,
英文关键词: Protein interaction network;Protein complexes;Random forest;Genetic algorithm;Graph theory