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dc.contributor.authorXiong, Yeyueen
dc.contributor.authorOnufriev, Alexey V.en
dc.date.accessioned2020-08-06T17:58:51Zen
dc.date.available2020-08-06T17:58:51Zen
dc.date.issued2019-11-14en
dc.identifier.citationXiong Y, Onufriev AV (2019) Exploring optimization strategies for improving explicit water models: Rigid n-point model and polarizable model based on Drude oscillator. PLoS ONE 14(11): e0224991. https://doi.org/10.1371/journal. pone.0224991en
dc.identifier.urihttp://hdl.handle.net/10919/99588en
dc.description.abstractRigid n-point water models are widely used in atomistic simulations, but have known accuracy drawbacks. Increasing the number of point charges, as well as adding electronic polarizability, are two common strategies for accuracy improvements. Both strategies come at considerable computational cost, which weighs heavily against modest possible accuracy improvements in practical simulations. In an effort to provide guidance for model development, here we have explored the limiting accuracy of “electrostatically globally optimal” npoint water models in terms of their ability to reproduce properties of water dimer—a mimic of the condensed state of water. For a given n, each model is built upon a set of reference multipole moments (e.g. ab initio) and then optimized to reproduce water dimer total dipole moment. The models are then evaluated with respect to the accuracy of reproducing the geometry of the water dimer. We find that global optimization of the charge distribution alone can deliver high accuracy of the water model: for n = 4 or n = 5, the geometry of the resulting water dimer can be almost within 50 of the ab initio reference, which is half that of the experimental error margin. Thus, global optimization of the charge distribution of classical n-point water models can lead to high accuracy models. We also find that while the accuracy improvement in going from n = 3 to n = 4 is substantial, the additional accuracy increase in going from n = 4 to n = 5 is marginal. Next, we have explored accuracy limitations of the standard practice of adding electronic polarizability (via a Drude particle) to a “rigid base”—pre-optimization rigid n-point water model. The resulting model (n = 3) shows a relatively small improvement in accuracy, suggesting that the strategy of merely adding the polarizability to an inferior accuracy water model used as the base cannot fix the defects of the latter. An alternative strategy in which the parameters of the rigid base model are globally optimized along with the polarizability parameter is much more promising: the resulting 3-point polarizable model out-performs even the 5-point optimal rigid model by a large margin. We suggest that future development efforts consider 3- and 4-point polarizable models where global optimization of the “rigid base” is coupled to optimization of the polarizability to deliver globally optimal solutions.en
dc.format.extent22 pagesen
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherPLOSen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleExploring optimization strategies for improving explicit water models: Rigid n-point model and polarizable model based on Drude oscillatoren
dc.typeArticle - Refereeden
dc.contributor.departmentCenter for Soft Matter and Biological Physicsen
dc.contributor.departmentBiomedical Engineering and Mechanicsen
dc.contributor.departmentComputer Scienceen
dc.contributor.departmentPhysicsen
dc.title.serialPLOS Oneen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0224991en
dc.identifier.volume14en
dc.identifier.issue11en
dc.type.dcmitypeTexten


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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International