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通过分子动力学模拟探索配体与蛋白质结合模式的稳定性:一项交叉对接研究。

Exploring the Stability of Ligand Binding Modes to Proteins by Molecular Dynamics Simulations: A Cross-docking Study.

作者信息

Liu Kai, Kokubo Hironori

机构信息

Drug Discovery Chemistry Laboratories, CNS Drug Discovery Unit, and ‡Partnership Research Center, Takeda Pharmaceutical Company Limited , 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-8555, Japan.

出版信息

J Chem Inf Model. 2017 Oct 23;57(10):2514-2522. doi: 10.1021/acs.jcim.7b00412. Epub 2017 Sep 29.

Abstract

Docking has become an indispensable approach in drug discovery research to predict the binding mode of a ligand. One great challenge in docking is to efficiently refine the correct pose from various putative docking poses through scoring functions. We recently examined the stability of self-docking poses under molecular dynamics (MD) simulations and showed that equilibrium MD simulations have some capability to discriminate between correct and decoy poses. Here, we have extended our previous work to cross-docking studies for practical applications. Three target proteins (thrombin, heat shock protein 90-alpha, and cyclin-dependent kinase 2) of pharmaceutical interest were selected. Three comparable poses (one correct pose and two decoys) for each ligand were then selected from the docking poses. To obtain the docking poses for the three target proteins, we used three different protocols, namely: normal docking, induced fit docking (IFD), and IFD against the homology model. Finally, five parallel MD equilibrium runs were performed on each pose for the statistical analysis. The results showed that the correct poses were generally more stable than the decoy poses under MD. The discrimination capability of MD depends on the strategy. The safest way was to judge a pose as being stable if any one run among five parallel runs was stable under MD. In this case, 95% of the correct poses were retained under MD, and about 25-44% of the decoys could be excluded by the simulations for all cases. On the other hand, if we judge a pose as being stable when any two or three runs were stable, with the risk of incorrectly excluding some correct poses, approximately 31-53% or 39-56% of the two decoys could be excluded by MD, respectively. Our results suggest that simple equilibrium simulations can serve as an effective filter to exclude decoy poses that cannot be distinguished by docking scores from the computationally expensive free-energy calculations.

摘要

对接已成为药物发现研究中预测配体结合模式不可或缺的方法。对接中的一个重大挑战是通过评分函数从各种假定的对接构象中有效地优化出正确构象。我们最近在分子动力学(MD)模拟下研究了自对接构象的稳定性,并表明平衡MD模拟具有一定区分正确构象和诱饵构象的能力。在此,我们将之前的工作扩展到交叉对接研究以用于实际应用。选择了三种具有药物研究意义的靶蛋白(凝血酶、热休克蛋白90-α和细胞周期蛋白依赖性激酶2)。然后从对接构象中为每个配体选择三种可比构象(一个正确构象和两个诱饵构象)。为了获得这三种靶蛋白的对接构象,我们使用了三种不同的方案,即:常规对接、诱导契合对接(IFD)以及针对同源模型的IFD。最后,对每个构象进行五次平行的MD平衡运行以进行统计分析。结果表明,在MD下正确构象通常比诱饵构象更稳定。MD的区分能力取决于策略。最稳妥的方法是如果五次平行运行中的任何一次在MD下是稳定的,就判断该构象是稳定的。在这种情况下,95%的正确构象在MD下得以保留,并且在所有情况下约25 - 44%的诱饵构象可被模拟排除。另一方面,如果当任何两次或三次运行稳定时我们就判断一个构象是稳定的,存在错误排除一些正确构象的风险,那么MD分别可排除约31 - 53%或39 - 56%的两种诱饵构象。我们的结果表明,简单的平衡模拟可以作为一种有效的筛选方法,以排除那些无法通过对接分数与计算成本高昂的自由能计算区分开的诱饵构象。

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