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; pp. 4436 - 4441 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Chemical Society
26.10.2020
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| Subjects | |
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| Abstract | 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, grand (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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| AbstractList | 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, grand (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. 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. |
| Author | Essex, Jonathan W Samways, Marley L Bruce Macdonald, Hannah E |
| AuthorAffiliation | Computational and Systems Biology Program School of Chemistry Memorial Sloan Kettering Cancer Center |
| AuthorAffiliation_xml | – name: Computational and Systems Biology Program – name: Memorial Sloan Kettering Cancer Center – name: School of Chemistry |
| Author_xml | – sequence: 1 givenname: Marley L orcidid: 0000-0001-9431-8789 surname: Samways fullname: Samways, Marley L organization: School of Chemistry – sequence: 2 givenname: Hannah E orcidid: 0000-0002-5562-6866 surname: Bruce Macdonald fullname: Bruce Macdonald, Hannah E organization: Memorial Sloan Kettering Cancer Center – sequence: 3 givenname: Jonathan W orcidid: 0000-0003-2639-2746 surname: Essex fullname: Essex, Jonathan W email: j.w.essex@soton.ac.uk organization: School of Chemistry |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32835483$$D View this record in MEDLINE/PubMed |
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| Snippet | Networks of water molecules can play a critical role at the protein–ligand interface and can directly influence drug–target interactions. Grand canonical... Networks of water molecules can play a critical role at the protein-ligand interface and can directly influence drug-target interactions. Grand canonical... |
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| SubjectTerms | Bulk density Chemical potential Crystallography Modules Molecular dynamics Proteins Simulation Trypsin inhibitors Water chemistry Water sampling |
| Title | grand: A Python Module for Grand Canonical Water Sampling in OpenMM |
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