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 (AS), 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 AS-integrated ones. Comparisons with previous results were made.
|Journal||JOURNAL OF INORGANIC BIOCHEMISTRY|
|Publication status||Published - Apr 2021|
Bibliographical noteFunding Information:
The authors are grateful to the Natural Science Foundation of China (Project No. 21272211) and the Program of Science and Technology of Ningbo, China (2019C10083) for financial support.
The authors are grateful to the Natural Science Foundation of China (Project No. 21272211 ) and the Program of Science and Technology of Ningbo , China ( 2019C10083 ) for financial support.
© 2021 Elsevier Inc.
Copyright 2021 Elsevier B.V., All rights reserved.
- Electrostatic potential
- Hydrophobic index
- Nonlinear modeling
- Platinum complex
- Structural descriptor
ASJC Scopus subject areas
- Inorganic Chemistry