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Pitfalls of the Martini Model

dc.contributor.authorAlessandri, Riccardo
dc.contributor.authorSouza, Paulo C.T.
dc.contributor.authorThallmair, Sebastian
dc.contributor.authorMelo, Manuel N.
dc.contributor.authorDe Vries, Alex H.
dc.contributor.authorMarrink, Siewert J.
dc.contributor.institutionInstituto de Tecnologia Química e Biológica António Xavier (ITQB)
dc.contributor.pblACS - American Chemical Society
dc.date.accessioned2020-04-22T22:34:42Z
dc.date.available2020-04-22T22:34:42Z
dc.date.issued2019-10-08
dc.descriptionR.A. thanks The Netherlands Organisation for Scientific Research NWO (Graduate Programme Advanced Materials, No. 022.005.006) for financial support. S.T. thanks the European Commission for financial support via a Marie Skłodowska-Curie Actions Individual Fellowship (MicroMod-PSII, grant agreement 748895).
dc.description.abstractThe computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent13
dc.format.extent2093320
dc.identifier.doi10.1021/acs.jctc.9b00473
dc.identifier.issn1549-9618
dc.identifier.otherPURE: 16765944
dc.identifier.otherPURE UUID: 7aefb17e-b6ec-4463-b583-68df88e6b12f
dc.identifier.otherScopus: 85072992707
dc.identifier.otherPubMed: 31498621
dc.identifier.urihttp://hdl.handle.net/10362/96649
dc.identifier.urlhttps://www.scopus.com/pages/publications/85072992707
dc.language.isoeng
dc.peerreviewedyes
dc.relation748895
dc.subjectComputer Science Applications
dc.subjectPhysical and Theoretical Chemistry
dc.titlePitfalls of the Martini Modelen
dc.typejournal article
degois.publication.firstPage5448
degois.publication.issue10
degois.publication.lastPage5460
degois.publication.titleJournal Of Chemical Theory And Computation
degois.publication.volume15
dspace.entity.typePublication
rcaap.rightsopenAccess

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