grand: A Python Module for Grand Canonical Water Sampling in OpenMM
Networks of water molecules can play a critical role at the protein-ligand interface and can directly influence drug-target interactions. Grand canonical methods aid in the sampling of these water molecules, where conventional molecular dynamics equilibration times are often long, by allowing waters...
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| Published in: | Journal of chemical information and modeling Vol. 60; no. 10; p. 4436 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
26.10.2020
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| ISSN: | 1549-960X, 1549-960X |
| Online Access: | Get more information |
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| Summary: | Networks of water molecules can play a critical role at the protein-ligand interface and can directly influence drug-target interactions. Grand canonical methods aid in the sampling of these water molecules, where conventional molecular dynamics equilibration times are often long, by allowing waters to be inserted and deleted from the system, according to the chemical potential. Here, we present our open source Python module,
(https://github.com/essex-lab/grand), which allows molecular dynamics simulations to be performed in conjunction with grand canonical Monte Carlo sampling, using the OpenMM simulation engine. We demonstrate the accuracy of this module by reproducing the density of bulk water observed from constant pressure simulations. Application of this code to the bovine pancreatic trypsin inhibitor protein reproduces three buried crystallographic water sites that are poorly sampled using conventional molecular dynamics. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1549-960X 1549-960X |
| DOI: | 10.1021/acs.jcim.0c00648 |