ChemInform Abstract: A Fuzzy ARTMAP Based on Quantitative Structure-Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds

Quantitative structure−property relationships (QSPRs) for estimating aqueous solubility of organic compounds at 25 °C were developed based on a fuzzy ARTMAP and a back-propagation neural networks using a heterogeneous set of 515 organic compounds. A set of molecular descriptors, developed from PM3 semiempirical MO-theory and topological descriptors (first-, second-, third-, and fourth-order molecular connectivity indices), were used as input parameters to the neural networks. Quantum chemical input descriptors included average polarizability, dipole moment, resonance energy, exchange energy, electron−nuclear attraction energy, and nuclear−nuclear (core−core) repulsion energy. The fuzzy ARTMAP/QSPR correlated aqueous solubility (S, mol/L) for a range of −11.62 to 4.31 logS with average absolute errors of 0.02 and 0.14 logS units for the overall and validation data sets, respectively. The optimal 11−13−1 back-propagation/QSPR model was less accurate, for the same solubility range, and exhibited larger avera...