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Comparison of Grand Canonical and Conventional Molecular Dynamics Simulation Methods for Protein-Bound Water Networks
[Image: see text] Water molecules play important roles in all biochemical processes. Therefore, it is of key importance to obtain information of the structure, dynamics, and thermodynamics of water molecules around proteins. Numerous computational methods have been suggested with this aim. In this s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136951/ https://www.ncbi.nlm.nih.gov/pubmed/35637786 http://dx.doi.org/10.1021/acsphyschemau.1c00052 |
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author | Ekberg, Vilhelm Samways, Marley L. Misini Ignjatović, Majda Essex, Jonathan W. Ryde, Ulf |
author_facet | Ekberg, Vilhelm Samways, Marley L. Misini Ignjatović, Majda Essex, Jonathan W. Ryde, Ulf |
author_sort | Ekberg, Vilhelm |
collection | PubMed |
description | [Image: see text] Water molecules play important roles in all biochemical processes. Therefore, it is of key importance to obtain information of the structure, dynamics, and thermodynamics of water molecules around proteins. Numerous computational methods have been suggested with this aim. In this study, we compare the performance of conventional and grand-canonical Monte Carlo (GCMC) molecular dynamics (MD) simulations to sample the water structure, as well GCMC and grid-based inhomogeneous solvation theory (GIST) to describe the energetics of the water network. They are evaluated on two proteins: the buried ligand-binding site of a ferritin dimer and the solvent-exposed binding site of galectin-3. We show that GCMC/MD simulations significantly speed up the sampling and equilibration of water molecules in the buried binding site, thereby making the results more similar for simulations started from different states. Both GCMC/MD and conventional MD reproduce crystal-water molecules reasonably for the buried binding site. GIST analyses are normally based on restrained MD simulations. This improves the precision of the calculated energies, but the restraints also significantly affect both absolute and relative energies. Solvation free energies for individual water molecules calculated with and without restraints show a good correlation, but with large quantitative differences. Finally, we note that the solvation free energies calculated with GIST are ∼5 times larger than those estimated by GCMC owing to differences in the reference state. |
format | Online Article Text |
id | pubmed-9136951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-91369512022-05-28 Comparison of Grand Canonical and Conventional Molecular Dynamics Simulation Methods for Protein-Bound Water Networks Ekberg, Vilhelm Samways, Marley L. Misini Ignjatović, Majda Essex, Jonathan W. Ryde, Ulf ACS Phys Chem Au [Image: see text] Water molecules play important roles in all biochemical processes. Therefore, it is of key importance to obtain information of the structure, dynamics, and thermodynamics of water molecules around proteins. Numerous computational methods have been suggested with this aim. In this study, we compare the performance of conventional and grand-canonical Monte Carlo (GCMC) molecular dynamics (MD) simulations to sample the water structure, as well GCMC and grid-based inhomogeneous solvation theory (GIST) to describe the energetics of the water network. They are evaluated on two proteins: the buried ligand-binding site of a ferritin dimer and the solvent-exposed binding site of galectin-3. We show that GCMC/MD simulations significantly speed up the sampling and equilibration of water molecules in the buried binding site, thereby making the results more similar for simulations started from different states. Both GCMC/MD and conventional MD reproduce crystal-water molecules reasonably for the buried binding site. GIST analyses are normally based on restrained MD simulations. This improves the precision of the calculated energies, but the restraints also significantly affect both absolute and relative energies. Solvation free energies for individual water molecules calculated with and without restraints show a good correlation, but with large quantitative differences. Finally, we note that the solvation free energies calculated with GIST are ∼5 times larger than those estimated by GCMC owing to differences in the reference state. American Chemical Society 2022-02-11 /pmc/articles/PMC9136951/ /pubmed/35637786 http://dx.doi.org/10.1021/acsphyschemau.1c00052 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Ekberg, Vilhelm Samways, Marley L. Misini Ignjatović, Majda Essex, Jonathan W. Ryde, Ulf Comparison of Grand Canonical and Conventional Molecular Dynamics Simulation Methods for Protein-Bound Water Networks |
title | Comparison of Grand Canonical and Conventional Molecular
Dynamics Simulation Methods for Protein-Bound Water Networks |
title_full | Comparison of Grand Canonical and Conventional Molecular
Dynamics Simulation Methods for Protein-Bound Water Networks |
title_fullStr | Comparison of Grand Canonical and Conventional Molecular
Dynamics Simulation Methods for Protein-Bound Water Networks |
title_full_unstemmed | Comparison of Grand Canonical and Conventional Molecular
Dynamics Simulation Methods for Protein-Bound Water Networks |
title_short | Comparison of Grand Canonical and Conventional Molecular
Dynamics Simulation Methods for Protein-Bound Water Networks |
title_sort | comparison of grand canonical and conventional molecular
dynamics simulation methods for protein-bound water networks |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136951/ https://www.ncbi.nlm.nih.gov/pubmed/35637786 http://dx.doi.org/10.1021/acsphyschemau.1c00052 |
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