CORAL: QSPR model of water solubility based on local and global SMILES attributes

Water solubility is an important characteristic of a chemical in many aspects. However experimental definition of the endpoint for all substances is impossible. In this study quantitative structure-property relationships (QSPRs) for negative logarithm of water solubility-log S (mol L-1) are built up for five random splits into the sub-training set (approximate to 55%), the calibration set (approximate to 25%), and the test set (approximate to 20%). Simplified molecular input-line entry system (SMILES) is used as the representation of the molecular structure. Optimal SMILES-based descriptors are calculated by means of the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). These one-variable models for water solubility are characterized by the following average values of the statistical characteristics: n(sub_train) = 725-763: n(calib) = 312-343; n(test) = 231-261; r(sub_train)(2) = 0.9211 +/- 0.0028; r(calib)(2) = 0.9555 +/- 0.0045; r(test)(2) = 0.9365 +/- 0.0073; S-sub_train = 0.561 +/- 0.0086; S-calib = 0.453 +/- 0.0209: s(test) = 0.520 +/- 0.0205. Thus, the reproducibility of statistical quality of suggested models for water solubility confirmed for five various splits. (C) 2012 Elsevier Ltd. All rights reserved.