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dc.contributor.authorBorhani, Tohid N
dc.contributor.authorGarcía-Muñoz, Salvador
dc.contributor.authorVanesa Luciani, Carla
dc.contributor.authorGalindo, Amparo
dc.contributor.authorAdjiman, Claire S
dc.date.accessioned2021-05-27T13:29:09Z
dc.date.available2021-05-27T13:29:09Z
dc.date.issued2019-06-17
dc.identifier.citationBorhani, T.N., García-Muñoz, S., Vanesa Luciani, C., Galindo, A. and Adjiman, C.S. (2019) Hybrid QSPR models for the prediction of the free energy of solvation of organic solute/solvent pairs. Physical Chemistry Chemical Physics, 21, pp. 13706-13720.en
dc.identifier.issn1463-9076en
dc.identifier.doi10.1039/c8cp07562jen
dc.identifier.urihttp://hdl.handle.net/2436/624083
dc.description© 2019 The Authors. Published by the Royal Society of Chemistry. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1039/C8CP07562Jen
dc.description.abstractDue to the importance of the Gibbs free energy of solvation in understanding many physicochemical phenomena, including lipophilicity, phase equilibria and liquid-phase reaction equilibrium and kinetics, there is a need for predictive models that can be applied across large sets of solvents and solutes. In this paper, we propose two quantitative structure property relationships (QSPRs) to predict the Gibbs free energy of solvation, developed using partial least squares (PLS) and multivariate linear regression (MLR) methods for 295 solutes in 210 solvents with total number of data points of 1777. Unlike other QSPR models, the proposed models are not restricted to a specific solvent or solute. Furthermore, while most QSPR models include either experimental or quantum mechanical descriptors, the proposed models combine both, using experimental descriptors to represent the solvent and quantum mechanical descriptors to represent the solute. Up to twelve experimental descriptors and nine quantum mechanical descriptors are considered in the proposed models. Extensive internal and external validation is undertaken to assess model accuracy in predicting the Gibbs free energy of solvation for a large number of solute/solvent pairs. The best MLR model, which includes three solute descriptors and two solvent properties, yields a coefficient of determination (R2) of 0.88 and a root mean squared error (RMSE) of 0.59 kcal mol−1 for the training set. The best PLS model includes six latent variables, and has an R2 value of 0.91 and a RMSE of 0.52 kcal mol−1. The proposed models are compared to selected results based on continuum solvation quantum chemistry calculations. They enable the fast prediction of the Gibbs free energy of solvation of a wide range of solutes in different solvents.en
dc.description.sponsorshipFinancial support from Eli Lilly via the Lilly Research Award Program (LRAP) and from the UK Engineering and Physical Sciences Research Council (EPSRC) of the UK via a Leadership Fellowship (EP/J003840/1) is gratefully acknowledged.en
dc.formatapplication/pdfen
dc.languageen
dc.language.isoenen
dc.publisherRoyal Society of Chemistryen
dc.relation.urlhttps://doi.org/10.1039/C8CP07562Jen
dc.titleHybrid QSPR models for the prediction of the free energy of solvation of organic solute/solvent pairsen
dc.typeJournal articleen
dc.identifier.eissn1463-9084
dc.identifier.journalPhysical Chemistry Chemical Physicsen
dc.date.updated2021-05-25T12:33:34Z
dc.date.accepted2019-04-25
rioxxterms.funderLilly Research Award Program (LRAP) and the UK Engineering and Physical Sciences Research Council (EPSRC)en
rioxxterms.identifier.projectEP/J003840/1en
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/3.0/en
rioxxterms.licenseref.startdate2021-05-27en
dc.source.volume21
dc.source.issue25
dc.source.beginpage13706
dc.source.endpage13720
dc.description.versionPublished online
refterms.dateFCD2021-05-27T13:28:57Z
refterms.versionFCDVoR
refterms.dateFOA2021-05-27T13:29:10Z


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