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分子对接是药物发现与设计的重要方法,采用计算机优化和模式识别方法在三维结构数据库中搜索几何、化学特性与特定药物结合位点相匹配分子的计算机辅助药物筛选是当前分子对接的研究热点,这种问题可以归为参数优化问题。本文提出了一种基于改进的量子粒子群(quantum-behaved particle swarm optimization,QPSO)算法的分子对接方法,用于处理大自由度的分子对接计算,并与基于标准QPSO算法和经典拉马克遗传算法的分子对接方法进行了比较,实验结果表明新方法无论是在对接能量还是对接准确性上,明显优于其它2种方法,尤其是在配体复杂性不断增加的情况下,非常适用于高柔性分子对接问题。
Molecular docking is an important method of drug discovery and design. Computer-aided drug screening with three-dimensional structure database search for geometric and chemical properties and specific drug binding sites by computer optimization and pattern recognition is a hot research topic in molecular docking. This problem can be classified as a parameter optimization problem. In this paper, we propose a molecular docking method based on improved quantum-behaved particle swarm optimization (QPSO) algorithm, which is used to deal with large degree of freedom molecular docking and is compared with the standard QPSO algorithm and classical Ramak Genetic Algorithm The experimental results show that the new method is obviously superior to the other two methods in terms of docking energy or docking accuracy. Especially in the case of increasing complexity of the ligand, it is very suitable for high flexibility Molecular docking problem.