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A New Approach for Flexible Molecular Docking Based on Swarm Intelligence

机译:基于群体智能的灵活分子对接的一种新方法

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摘要

Molecular docking methods play an important role in the field of computer-aided drug design. In the work, on the basis of the molecular docking program AutoDock, we present QLDock as a tool for flexible molecular docking. For the energy evaluation, the algorithm uses the binding free energy function that is provided by the AutoDock 4.2 tool. The new search algorithm combines the features of a quantum-behaved particle swarm optimization (QPSO) algorithm and local search method of Solis and Wets for solving the highly flexible protein-ligand docking problem. We compute the interaction of 23 protein-ligand complexes and compare the results with those of the QDock and AutoDock programs. The experimental results show that our approach leads to substantially lower docking energy and higher docking precision in comparison to Lamarckian genetic algorithm and QPSO algorithm alone. QPSO-ls algorithm was able to identify the correct binding mode of 74% of the complexes. In comparison, the accuracy of QPSO and LGA is 52% and 61%, respectively. This difference in performance rises with increasing complexity of the ligand. Thus, the novel algorithm QPSO-ls may be used to dock ligand with many rotatable bonds with high accuracy.
机译:分子对接方法在计算机辅助药物设计领域发挥着重要作用。在工作中,根据分子对接程序自动锁定,我们将Qldock作为柔性分子对接的工具。对于能量评估,该算法使用由Autodock 4.2工具提供的绑定自由能功能。新的搜索算法结合了量子行为粒子群优化(QPSO)算法和局部搜索方法的特征,用于求解高度柔性蛋白质配体对接问题。我们计算23蛋白 - 配体复合物的相互作用,并将结果与​​Qdock和Autodock程序的结果进行比较。实验结果表明,与单独的Lamarckian遗传算法和QPSO算法相比,我们的方法可以显着降低对接能量和更高的对接精度。 QPSO-LS算法能够识别74%的复合物的正确装订模式。相比之下,QPSO和LGA的准确性分别为52%和61%。这种性能的差异随着配体的复杂性的增加而上升。因此,新颖的算法QPSO-LS可用于停靠配体,其具有高精度具有许多可旋转键。

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