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  4. Prediction of logP for Pt(II) and Pt(IV) complexes: Comparison of statistical and quantum-chemistry based approaches
 
research article

Prediction of logP for Pt(II) and Pt(IV) complexes: Comparison of statistical and quantum-chemistry based approaches

Tetko, Igor V.
•
Varbanov, Hristo P.  
•
Galanski, Markus
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2016
Journal Of Inorganic Biochemistry

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. (C) 2015 Elsevier Inc. All rights reserved.

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Type
research article
DOI
10.1016/j.jinorgbio.2015.12.006
Web of Science ID

WOS:000370769400001

Author(s)
Tetko, Igor V.
Varbanov, Hristo P.  
Galanski, Markus
Talmaciu, Mona
Platts, James A.
Ravera, Mauro
Gabano, Elisabetta
Date Issued

2016

Publisher

Elsevier Science Inc

Published in
Journal Of Inorganic Biochemistry
Volume

156

Start page

1

End page

13

Subjects

Pt(II)/Pt(IV) complexes

•

Lipophilicity

•

logP prediction

•

Neural networks

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Linear regression

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Quantum chemistry calculations

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
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Available on Infoscience
April 1, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/125299
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