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Prediction of ligand binding mode among multiple cross-docking poses by molecular dynamics simulations

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Abstract

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.

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Acknowledgements

This study used computational resources of the HPCI system provided by the TSUBAME Grid Cluster at the Global Scientific Information and Computing Center of Tokyo Institute of Technology through the HPCI System Research Project (Project ID hp180007). K. L. is grateful for the financial support from Scientific Research Foundation (2019KY0326, 2018BS038, 2018ZD005-A16) and Qihuang Project of Guangxi University of Chinese Medicine and the Special Fund for Hundred Talents Program and Bagui Scholars of Guangxi.

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  1. Hironori Kokubo

    Present address: Discovery Chemistry Department, Chugai Pharmaceutical Co. Ltd., 200 Kajiwara, Kanagawa, Japan

Authors and Affiliations

  1. Institute of Marine Drugs, Guangxi University of Chinese Medicine, No. 13, Wuhe Avenue, Nanning, 530200, Guangxi, People’s Republic of China

    Kai Liu

  2. Chemistry, Research Division, Axcelead Drug Discovery Partners, Inc, 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-8555, Japan

    Hironori Kokubo

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KL and KH contributed equally.

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Liu, K., Kokubo, H. Prediction of ligand binding mode among multiple cross-docking poses by molecular dynamics simulations. J Comput Aided Mol Des 34, 1195–1205 (2020). https://doi.org/10.1007/s10822-020-00340-y

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