Scalable Constant pH Molecular Dynamics in GROMACS
Aho, N., Buslaev, P., Jansen, A., Bauer, P., Groenhof, G., & Hess, B. (2022). Scalable Constant pH Molecular Dynamics in GROMACS. Journal of Chemical Theory and Computation, 18(10), 6148-6160. https://doi.org/10.1021/acs.jctc.2c00516
Published inJournal of Chemical Theory and Computation
© 2022 the Authors
Molecular dynamics (MD) computer simulations are used routinely to compute atomistic trajectories of complex systems. Systems are simulated in various ensembles, depending on the experimental conditions one aims to mimic. While constant energy, temperature, volume, and pressure are rather straightforward to model, pH, which is an equally important parameter in experiments, is more difficult to account for in simulations. Although a constant pH algorithm based on the λ-dynamics approach by Brooks and co-workers [Kong, X.; Brooks III, C. L. J. Chem. Phys.1996, 105, 2414–2423] was implemented in a fork of the GROMACS molecular dynamics program, uptake has been rather limited, presumably due to the poor scaling of that code with respect to the number of titratable sites. To overcome this limitation, we implemented an alternative scheme for interpolating the Hamiltonians of the protonation states that makes the constant pH molecular dynamics simulations almost as fast as a normal MD simulation with GROMACS. In addition, we implemented a simpler scheme, called multisite representation, for modeling side chains with multiple titratable sites, such as imidazole rings. This scheme, which is based on constraining the sum of the λ-coordinates, not only reduces the complexity associated with parametrizing the intramolecular interactions between the sites but also is easily extendable to other molecules with multiple titratable sites. With the combination of a more efficient interpolation scheme and multisite representation of titratable groups, we anticipate a rapid uptake of constant pH molecular dynamics simulations within the GROMACS user community. ...
PublisherAmerican Chemical Society (ACS)
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Academy Project, AoF
Additional information about fundingThis research was supported by the Swedish Research Council (Grant 2019-04477), Academy of Finland (Grants 311031 and 332743), and the BioExcel CoE (Grant H2020-INFRAEDI-02- 2018-823830). The simulations were performed on resources provided by the CSC-IT Center for Science, Finland, and the Swedish National Infrastructure for Computing (SNIC 2021/1- 38).
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