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dc.contributor.authorAho, Noora
dc.contributor.authorBuslaev, Pavel
dc.contributor.authorJansen, Anton
dc.contributor.authorBauer, Paul
dc.contributor.authorGroenhof, Gerrit
dc.contributor.authorHess, Berk
dc.date.accessioned2022-09-29T11:12:20Z
dc.date.available2022-09-29T11:12:20Z
dc.date.issued2022
dc.identifier.citationAho, N., Buslaev, P., Jansen, A., Bauer, P., Groenhof, G., & Hess, B. (2022). Scalable Constant pH Molecular Dynamics in GROMACS. <i>Journal of Chemical Theory and Computation</i>, <i>18</i>(10), 6148-6160. <a href="https://doi.org/10.1021/acs.jctc.2c00516" target="_blank">https://doi.org/10.1021/acs.jctc.2c00516</a>
dc.identifier.otherCONVID_156677434
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/83385
dc.description.abstractMolecular 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.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherAmerican Chemical Society (ACS)
dc.relation.ispartofseriesJournal of Chemical Theory and Computation
dc.rightsCC BY 4.0
dc.subject.othermolecular mechanics
dc.subject.othermonomers
dc.subject.otherpeptides and proteins
dc.subject.otherpotential energy
dc.subject.otherreaction mechanisms
dc.titleScalable Constant pH Molecular Dynamics in GROMACS
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202209294738
dc.contributor.laitosKemian laitosfi
dc.contributor.laitosDepartment of Chemistryen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange6148-6160
dc.relation.issn1549-9618
dc.relation.numberinseries10
dc.relation.volume18
dc.type.versionpublishedVersion
dc.rights.copyright© 2022 the Authors
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.relation.grantnumber332743
dc.relation.grantnumber311031
dc.subject.ysomolekyylit
dc.subject.ysomolekyylidynamiikka
dc.subject.ysopeptidit
dc.subject.ysopotentiaalienergia
dc.subject.ysoproteiinit
dc.subject.ysoreaktiomekanismit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p2984
jyx.subject.urihttp://www.yso.fi/onto/yso/p29332
jyx.subject.urihttp://www.yso.fi/onto/yso/p15258
jyx.subject.urihttp://www.yso.fi/onto/yso/p17455
jyx.subject.urihttp://www.yso.fi/onto/yso/p4332
jyx.subject.urihttp://www.yso.fi/onto/yso/p21536
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1021/acs.jctc.2c00516
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundinginformationThis 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).
dc.type.okmA1


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