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ClogPalk: a method for predicting alkane/water partition coefficient

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Abstract

Alkane/water partition coefficients (Palk) are less familiar to the molecular design community than their 1-octanol/water equivalents and access to both data and prediction tools is much more limited. A method for predicting alkane/water partition coefficient from molecular structure is introduced. The basis for the ClogPalk model is the strong (R2 = 0.987) relationship between alkane/water partition coefficient and molecular surface area (MSA) that was observed for saturated hydrocarbons. The model treats a molecule as a perturbation of a saturated hydrocarbon molecule with the same MSA and uses increments defined for functional groups to quantify the extent to which logPalk is perturbed by the introduction each functional group. Interactions between functional groups, such as intramolecular hydrogen bonds are also parameterized within a perturbation framework. The functional groups and interactions between them are specified substructurally in a transparent and reproducible manner using SMARTS notation. The ClogPalk model was parameterized using data measured for structurally prototypical compounds that dominate the literature on alkane/water partition coefficients and then validated using an external test set of 100 alkane/water logP measurements, the majority of which were for drugs.

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Acknowledgments

We are grateful to the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and the Conselho Nacional de Pesquisa (CNPq) for financial support. We also thank OpenEye Scientific Software for providing access to software and the anonymous reviewers of the manuscript for their constructive comments.

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Correspondence to Peter W. Kenny.

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Kenny, P.W., Montanari, C.A. & Prokopczyk, I.M. ClogPalk: a method for predicting alkane/water partition coefficient. J Comput Aided Mol Des 27, 389–402 (2013). https://doi.org/10.1007/s10822-013-9655-5

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