grand: A Python Module for Grand Canonical Water Sampling
in OpenMM
Posted on 2020-09-19 - 17:29
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.
CITE THIS COLLECTION
DataCite
3 Biotech
3D Printing in Medicine
3D Research
3D-Printed Materials and Systems
4OR
AAPG Bulletin
AAPS Open
AAPS PharmSciTech
Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg
ABI Technik (German)
Academic Medicine
Academic Pediatrics
Academic Psychiatry
Academic Questions
Academy of Management Discoveries
Academy of Management Journal
Academy of Management Learning and Education
Academy of Management Perspectives
Academy of Management Proceedings
Academy of Management Review
Samways, Marley
L.; Bruce Macdonald, Hannah E.; Essex, Jonathan W. (2020). grand: A Python Module for Grand Canonical Water Sampling
in OpenMM. ACS Publications. Collection. https://doi.org/10.1021/acs.jcim.0c00648
or
Select your citation style and then place your mouse over the citation text to select it.
SHARE
Usage metrics
Read the peer-reviewed publication
AUTHORS (3)
MS
Marley
L. Samways
HB
Hannah E. Bruce Macdonald
JE
Jonathan W. Essex