title: Prediction of logP for Pt(II) and Pt(IV) complexes: Comparison of statistical and quantum-chemistry based approaches.
abstract: The octanol/water partition coefficient, logP, is one of the most important physico-chemical parameters for the development of new metal-based anticancer drugs with improved pharmacokinetic properties. This study addresses an issue with the absence of publicly available models to predict logP of Pt(IV) complexes. Following data collection and subsequent development of models based on 187 complexes from literature, we validate new and previously published models on a new set of 11 Pt(II) and 35 Pt(IV) complexes, which were kept blind during the model development step. The error of the consensus model, 0.65 for Pt(IV) and 0.37 for Pt(II) complexes, indicates its good accuracy of predictions. The lower accuracy for Pt(IV) complexes was attributed to experimental difficulties with logP measurements for some poorly-soluble compounds. This model was developed using general-purpose descriptors such as extended functional groups, molecular fragments and E-state indices. Surprisingly, models based on quantum-chemistry calculations provided lower prediction accuracy. We also found that all the developed models strongly overestimate logP values for the three complexes measured in the presence of DMSO. Considering that DMSO is frequently used as a solvent to store chemicals, its effect should not be overlooked when logP measurements by means of the shake flask method are performed. The final models are freely available at http://ochem.eu/article/76903.
authors.affiliation: Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Structural Biology, Ingolstaedter Landstrasse 1, b. 60w, D-85764 Neuherberg, Germany; BigChem GmbH, Ingolstaedter Landstrasse 1, b. 60w, D-85764 Neuherberg, Germany. Electronic address: itetko@vcclab.org.
authors.forename: Igor V
authors.initials: IV
authors.lastname: Tetko
authors.affiliation: Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland; Institute of Inorganic Chemistry, University of Vienna, Waehringer Strasse 42, A-1090 Vienna, Austria.
authors.forename: Hristo P
authors.initials: HP
authors.lastname: Varbanov
authors.affiliation: Institute of Inorganic Chemistry, University of Vienna, Waehringer Strasse 42, A-1090 Vienna, Austria.
authors.forename: Mathea S
authors.initials: MS
authors.lastname: Galanski
authors.affiliation: School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, UK; «Iuliu Haţieganu» University of Medicine and Pharmacy, Faculty of Pharmacy, Analytical Chemistry Department, Cluj-Napoca, Romania.
authors.forename: Mona
authors.initials: M
authors.lastname: Talmaciu
authors.affiliation: School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, UK.
authors.forename: James A
authors.initials: JA
authors.lastname: Platts
authors.affiliation: Dipartimento di Scienze e Innovazione Tecnologica, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy.
authors.forename: Mauro
authors.initials: M
authors.lastname: Ravera
authors.affiliation: Dipartimento di Scienze e Innovazione Tecnologica, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy.
authors.forename: Elisabetta
authors.initials: E
authors.lastname: Gabano
mesh_terms: D008024:Ligands; D008956:Models, Chemical; D010984:Platinum / Q000737:chemistry*; D011789:Quantum Theory
chemical_list: D008024:Ligands; D010984:Platinum
keywords: Linear regression; Lipophilicity; Neural networks; Pt(II)/Pt(IV) complexes; Quantum chemistry calculations; logP prediction