phbuilder : A Tool for Efficiently Setting up Constant pH Molecular Dynamics Simulations in GROMACS
Jansen, A., Aho, N., Groenhof, G., Buslaev, P., & Hess, B. (2024). phbuilder : A Tool for Efficiently Setting up Constant pH Molecular Dynamics Simulations in GROMACS. Journal of Chemical Information and Modeling, 64(3), 567-574. https://doi.org/10.1021/acs.jcim.3c01313
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Journal of Chemical Information and ModelingDate
2024Discipline
Orgaaninen kemiaNanoscience CenterFysikaalinen kemiaOrganic ChemistryNanoscience CenterPhysical ChemistryCopyright
© The Authors. Published by American Chemical Society
Constant pH molecular dynamics (MD) is a powerful technique that allows the protonation state of residues to change dynamically, thereby enabling the study of pH dependence in a manner that has not been possible before. Recently, a constant pH implementation was incorporated into the GROMACS MD package. Although this implementation provides good accuracy and performance, manual modification and the preparation of simulation input files are required, which can be complicated, tedious, and prone to errors. To simplify and automate the setup process, we present phbuilder, a tool that automatically prepares constant pH MD simulations for GROMACS by modifying the input structure and topology as well as generating the necessary parameter files. phbuilder can prepare constant pH simulations from both initial structures and existing simulation systems, and it also provides functionality for performing titrations and single-site parametrizations of new titratable group types. The tool is freely available at www.gitlab.com/gromacs-constantph. We anticipate that phbuilder will make constant pH simulations easier to set up, thereby making them more accessible to the GROMACS user community.
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American Chemical Society (ACS)ISSN Search the Publication Forum
1549-9596Keywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/197945475
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Research Council of FinlandFunding program(s)
Academy Project, AoF; Postdoctoral Researcher, AoFAdditional information about funding
This research was supported by the Swedish Research Council (Grant 2019-04477), the Academy of Finland (Grants 311031, 332743, and 342908), and the Bio Excel CoE (Grants H2020-INFRAEDI-02-2018-823830 and 101093290).License
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