The dissociation of ligands from proteins and other biomacromolecules occurs over a wide range of timescales. For most pharmaceutically relevant inhibitors, these timescales are far beyond those that are accessible by conventional molecular dynamics (MD) simulation. Consequently, to explore ligand egress mechanisms and compute dissociation rates, it is necessary to enhance the sampling of ligand unbinding. Random Acceleration MD (RAMD) is a simple method to enhance ligand egress from a macromolecular binding site, which enables the exploration of ligand egress routes without prior knowledge of the reaction coordinates. Furthermore, the τRAMD procedure can be used to compute the relative residence times of ligands. When combined with a machine-learning analysis of protein–ligand interaction fingerprints (IFPs), molecular features that affect ligand unbinding kinetics can be identified. Here, we describe the implementation of RAMD in GROMACS 2020, which provides significantly improved computational performance, with scaling to large molecular systems. For the automated analysis of RAMD results, we developed MD-IFP, a set of tools for the generation of IFPs along unbinding trajectories and for their use in the exploration of ligand dynamics. We demonstrate that the analysis of ligand dissociation trajectories by mapping them onto the IFP space enables the characterization of ligand dissociation routes and metastable states. The combined implementation of RAMD and MD-IFP provides a computationally efficient and freely available workflow that can be applied to hundreds of compounds in a reasonable computational time and will facilitate the use of τRAMD in drug design.
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28 September 2020
Research Article|
September 25 2020
A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories
Daria B. Kokh
;
Daria B. Kokh
a)
1
Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies
, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
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Bernd Doser
;
Bernd Doser
2
Heidelberg Institute for Theoretical Studies
, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
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Stefan Richter
;
Stefan Richter
1
Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies
, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
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Fabian Ormersbach;
Fabian Ormersbach
1
Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies
, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
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Xingyi Cheng
;
Xingyi Cheng
1
Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies
, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
3
Molecular Biosciences, Heidelberg University
, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany
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Rebecca C. Wade
Rebecca C. Wade
a)
1
Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies
, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
4
Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University
, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany
5
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University
, Im Neuenheimer Feld 205, Heidelberg, Germany
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Note: This paper is part of the JCP Special Topic on Classical Molecular Dynamics (MD) Simulations: Codes, Algorithms, Force Fields, and Applications.
J. Chem. Phys. 153, 125102 (2020)
Article history
Received:
June 19 2020
Accepted:
August 31 2020
Citation
Daria B. Kokh, Bernd Doser, Stefan Richter, Fabian Ormersbach, Xingyi Cheng, Rebecca C. Wade; A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories. J. Chem. Phys. 28 September 2020; 153 (12): 125102. https://doi.org/10.1063/5.0019088
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