利用退火遗传算法求解分子结合中的全局能量最小化问题

Leuo-hong Wang, Cheng-Yan Kao, M. Ouhyoung, Wen-Chin Chen
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引用次数: 7

摘要

分子结合在药物设计中很重要,它探索分子之间的精确结合结构。这种探索可以被表述为一个全局优化问题。然而,分子结合的问题是搜索空间非常大,计算成本随着自由度的增加而急剧增加。本文采用一种新的退火遗传算法来解决分子结合中的全局优化问题。在模型中使用含有三种抗癌药物的蛋白质,我们的算法可以在几个小时内通过复杂的能量计算找到一个结合结构,实验结果表明我们的解决方案是合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using an annealing genetic algorithm to solve global energy minimization problem in molecular binding
Molecular binding, important in drug design, explores the accurate binding structures between molecules. This exploration can be formulated as a global optimization problem. However, the problem in molecular binding is that the search space is very large and the computational cost increases tremendously with the growth of the degrees of freedom. In this paper, we utilize a new algorithm called the annealing genetic algorithm to solve the global optimization problem in molecular binding. Using a protein with three anti-cancer drugs in our model, our algorithm can find a binding structure with a complicated energy computation within a couple of hours and the experimental results indicate that the solutions are reasonable.<>
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