遗传算法与RSNR对接的比较

Yong L. Xiao, Donald E. Williams
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引用次数: 1

摘要

比较了遗传算法(GA)与数值随机抽样牛顿-拉夫逊(RSNR)方法的分子对接计算结果。针对对接过程,采用遗传算法和数值算法寻找分子间相互作用能量的最小值。研究了一种抗癌药物的大分子复合物的分子间相互作用。讨论了GAs在分子对接计算中的性能,并与数值方法进行了比较。实现结果表明,当存在多个局部最小值和一个全局最小值时,遗传算法在能量最小化方面优于传统方法。遗传算法在计算上更适用于大型生物系统,为药物发现和新分子结构设计提供了一种合理的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comparison of GA and RSNR docking
Molecular docking calculations with genetic algorithms (GA) are compared with results calculated by a numeric random sampling Newton-Raphson (RSNR) method. The intermolecular interaction energy minimum is searched for using both a genetic algorithm approach and a numeric one for the docking process. Intermolecular interactions of a larger molecular complex of an anticancer drug have been investigated. The performance of GAs on molecular docking calculations is discussed and compared with the numerical method. The results of implementation indicate that the GA approach is superior to conventional methods used in energy minimization when there exist many local minima as well as a global minimum. The GA method, which is computationally more practical for applications to large biological systems, provides a rational approach to drug discovery and novel molecular structure design.<>
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