Prediction of the hydrophobicity of platinum(IV) complexes based on molecular surface properties

A quantitative structure-property relationship (QSPR) study was performed for predicting the hydrophobicity of Pt(IV) complexes. Two four-parameter equations, one based solely on structural descriptors derived from electrostatic potentials (ESPs) on molecular surface, and the other integrated ESP descriptors with molecular surface area (A_S), were firstly constructed. Mechanistic interpretations of the structural descriptors introduced were elucidated in terms of solute-solvent intermolecular interactions. Subsequently, several up-to-date modeling techniques, including support vector machine (SVM), least-squares support vector machine (LSSVM), random forest (RF) and Gaussian process (GP), were utilized to build the nonlinear models. Systematical validations including leave-one-out cross-validation, the validation for test set, as well as a more rigorous Monte Carlo cross-validation were performed to verify the reliability of the constructed models. The predictive performances of the four different nonlinear modeling methods follow the order of LSSVM≈GP > RF > SVM. The pure-ESP-based models are generally inferior to the A_S-integrated ones. Comparisons with previous results were made.