Institute of Marine Drugs, Guangxi University of Chinese Medicine, No. 13, Wuhe Avenue, Nanning, 530200, Guangxi, People's Republic of China.
Chemistry, Research Division, Axcelead Drug Discovery Partners, Inc, 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-8555, Japan.
J Comput Aided Mol Des. 2020 Nov;34(11):1195-1205. doi: 10.1007/s10822-020-00340-y. Epub 2020 Sep 1.
We propose a method to identify the correct binding mode of a ligand with a protein among multiple predicted docking poses. Our method consists of two steps. First, five independent MD simulations with different initial velocities are performed for each docking pose, in order to evaluate its stability. If the root-mean-square deviations (RMSDs) of heavy atoms from the docking pose are larger than a given threshold (2.0 Å) in all five parallel runs, the pose is filtered out and discarded. Then, we perform accurate all-atom binding free energy calculations for the residual poses only. The pose with the lowest binding free energy is identified as the correct pose. As a test case, we applied our method to a previously built cross-docking test set, which included 104 complex systems. We found that the present method could successfully identify the correct ligand binding mode for 72% (75/104) of the complexes for current test set. The possible reasons for the failure of the method in the other cases were investigated in detail, to enable future improvements.
我们提出了一种方法,可用于在多个预测对接构象中识别配体与蛋白质的正确结合模式。我们的方法包括两个步骤。首先,对每个对接构象进行五次独立的具有不同初始速度的 MD 模拟,以评估其稳定性。如果所有五个平行运行中重原子相对于对接构象的均方根偏差(RMSD)都大于给定的阈值(2.0 Å),则会过滤并丢弃该构象。然后,我们仅对残差构象进行精确的全原子结合自由能计算。具有最低结合自由能的构象被确定为正确的构象。作为一个测试案例,我们将我们的方法应用于先前构建的交叉对接测试集,其中包括 104 个复杂系统。我们发现,对于当前测试集中的 72%(75/104)复合物,本方法可以成功识别正确的配体结合模式。我们详细研究了方法在其他情况下失败的可能原因,以便未来进行改进。