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-logS (molL^-1) are built up for five random splits into the sub-training set (≈55%), the calibration set (≈25%), and the test set (≈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; rsub_train2=0.9211±0.0028; rcalib2=0.9555±0.0045; rtest2=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.