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机构地区:[1]大连理工大学工业装备结构分析国家重点实验室,辽宁大连116024
出 处:《大连理工大学学报》2006年第5期760-764,共5页Journal of Dalian University of Technology
基 金:国家"九七三"高技术研究发展资助项目(G1999032805);国家自然科学基金资助项目(10272030)
摘 要:药物分子对接所涉及的搜索空间非常巨大,需要耗费大量的时间,并且对计算环境也有较高的要求.将网格技术应用于药物分子对接中,能有效解决上述问题.通过应用改进的遗传算法多种群竞争机制的对接演化模型GAD ock,以信息熵控制设计空间的收缩,增强了进化的有效性,显著地提高了对接效率.利用网格数据传输和网格任务调度等网格技术对分子对接过程进行了优化,有效利用了网格节点资源,并降低了药物分子的对接时间.实例测试表明了药物分子对接与网格技术相结合的合理性及有效性.Rigid conditions such as searching space, spending time and computing environment are required by drug molecular docking design, which can be satisfied through combining drug molecular docking design with grid techniques. An improved genetic algorithm docking method, GADock, is presented, which is based on multi-species competition mechanism. And this informational entropy will be used to control the design space narrowing down, so the evolutional reasonability and docking efficiency are all improved greatly. Then two correlative grid techniques, grid data transferring and grid task scheduling, are introduced, through which the docking time is reduced and the grid resources are used more efficiently. The results of example tests have shown that the combination of drug molecular docking design and grid techniques is efficient and reasonable.
分 类 号:TP391.75[自动化与计算机技术—计算机应用技术]
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