Solubility plays a very important role in the selection of compounds for drug screening. In this context, a QSAR model was developed for predicting water solubility of drug-like compounds. First, a set of relevant parameters for establishing a drug-like chemical space was defined. The comparison of chemical structures from the FDAMDD and PHYSPROP databases allowed the selection of properties that were more efficient in discriminating drug-like compounds from other chemicals. These filters were later on applied to the PHYSPROP database and 1174 chemicals fulfilling these criteria and with experimental solubility information available at 25°C were retained. Several QSAR solubility models were developed from this set of compounds, and the best one was selected based on the accuracy of correct classifications obtained for randomly chosen training and validation subsets. Further validation of the model was performed with a set of 102 drugs for which experimental solubility data have been recently reported. A good agreement between the predictions and the experimental values confirmed the reliability of the QSAR model.
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