蛋白结合位点预测及基于GPU加速的反向对接研究

项目名称： 蛋白结合位点预测及基于GPU加速的反向对接研究

项目编号： No.61303099

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： 高军

作者单位： 上海海事大学

项目金额： 23万元

中文摘要： 反向对接以小分子为起点寻找潜在的结合对象，为药物靶点的发现和确认提供新的思路。以往的反向对接系统中存在着蛋白结合位点预测精度不够和高通量分析虚拟筛选耗时长等问题。我们前期研究表明:基于结构比对的结合位点预测算法在引入复合物稳定性校验及同源索引等约束后，其准确率和运算效率得到大幅提高。前期工作还表明，图形处理器(Graphics Processing Unit, GPU)技术是解决生物密集计算的有效手段。本课题将开发新的蛋白结合位点预测算法进而实现新的反向对接系统，并实现对接过程的GPU加速，最终整合成自动化执行的系统并提供web服务。本课题的实现将为分子靶点发现提供新方法，有望有效地解决当前药物研究中"多靶点"和"副作用"等关键问题。

中文关键词： 结合位点；反向对接；机器学习；图形处理器；

英文摘要： Inverse docking is a relatively new technique that has been used to identify potential receptor targets of small molecules. It provides new ideas for the discovery and validation of drug targets. However, there are still some limitations of current inverse docking system, such as, low accuracy of protein binding site prediction and time-consuming procedure for high-throughput analysis of virtual screening. Our previous studies have shown that the accuracy rate and efficiency in protein binding site prediction can be improved significantly when restrictions such as complex stability and homologous indexing are applied to the structure based alignment algorithm. Preliminary studies also have shown that the graphics processor (Graphics Processing Unit, GPU) technology is an effective means to solve the bio-intensive computing. In this work, we explore a new protein binding sites prediction method so as to realize a new inverse docking system with GPU accelerated. Eventually individual modules are integrated into an automated execution system and web services are provided for the end users. We believe the realization of this work will provide a new method for molecular target discovery, which is expected to effectively solve the "multi-target" and "side effects" and other key issues in the current drug research.

英文关键词： Bingding Site；Inverse Docking；Machine Learning；Graphics Processing Unit；