| Autor: |
Samways ML; School of Chemistry, University of Southampton, Southampton, SO17 1BJ, United Kingdom., Bruce Macdonald HE; Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States., Essex JW; School of Chemistry, University of Southampton, Southampton, SO17 1BJ, United Kingdom. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of chemical information and modeling [J Chem Inf Model] 2020 Oct 26; Vol. 60 (10), pp. 4436-4441. Date of Electronic Publication: 2020 Sep 19. |
| DOI: |
10.1021/acs.jcim.0c00648 |
| Abstrakt: |
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. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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