gmXtal : Cooking Crystals with GROMACS

Abstract
Molecular dynamics (MD) simulations are routinely performed of biomolecules in solution, because this is their native environment. However, the structures used in such simulations are often obtained with X-ray crystallography, which provides the atomic coordinates of the biomolecule in a crystal environment. With the advent of free electron lasers and time-resolved techniques, X-ray crystallography can now also access metastable states that are intermediates in a biochemical process. Such experiments provide additional data, which can be used, for example, to optimize MD force fields. Doing so requires that the simulation of the biomolecule is also performed in the crystal environment. However, in contrast to simulations of biomolecules in solution, setting up a crystal is challenging. In particular, because not all solvent molecules are resolved in X-ray crystallography, adding a suitable number of solvent molecules, such that the properties of the crystallographic unit cell are preserved in the simulation, can be difficult and typically is a trial-and-error based procedure requiring manual interventions. Such interventions preclude high throughput applications. To overcome this bottleneck, we introduce gmXtal, a tool for setting up crystal simulations for MD simulations with GROMACS. With the information from the protein data bank (rcsb.org) gmXtal automatically (i) builds the crystallographic unit cell; (ii) sets the protonation of titratable residues; (iii) builds missing residues that were not resolved experimentally; and (iv) adds an appropriate number of solvent molecules to the system. gmXtal is available as a standalone tool https://gitlab.com/pbuslaev/gmxtal.
Main Authors
Format
Articles Research article
Published
2023
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202309064935Use this for linking
Review status
Peer reviewed
ISSN
1572-3887
DOI
https://doi.org/10.1007/s10930-023-10141-5
Language
English
Published in
Protein Journal
Citation
License
CC BY 4.0Open Access
Funder(s)
Research Council of Finland
Research Council of Finland
Funding program(s)
Postdoctoral Researcher, AoF
Academy Project, AoF
Tutkijatohtori, SA
Akatemiahanke, SA
Research Council of Finland
Additional information about funding
This work was supported by the Academy of Finland (Grant 342908, 332743). The simulations were performed on resources provided by the CSC-IT Center for Science, Finland. Open Access funding provided by University of Jyväskylä (JYU).
Copyright© The Author(s) 2023

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