Rough Set Theory as an Interpretable Method for Predicting the Inhibition of Cytochrome P450 1A2 and 2D6

Julien Burton; Joachim Petit; Emeric Danloy; Gerald M Maggiora; Daniel P Vercauteren

doi:10.1002/minf.201300009

Rough Set Theory as an Interpretable Method for Predicting the Inhibition of Cytochrome P450 1A2 and 2D6

Mol Inform. 2013 Jul;32(7):579-89. doi: 10.1002/minf.201300009. Epub 2013 Jul 8.

Authors

Julien Burton¹, Joachim Petit^{2

3}, Emeric Danloy¹, Gerald M Maggiora², Daniel P Vercauteren⁴

Affiliations

¹ Laboratoire de Physico-Chimie Informatique, Groupe de Chimie Physique Théorique et Structurale, University of Namur (FUNDP), 61 rue de Bruxelles, B-5000 Namur, Belgium phone: +32 (0)81 72 45 34; fax:+32 (0)81 72 54 66.
² Department of Pharmacology & Toxicology, College of Pharmacy, University of Arizona, 1703 E. Mabel Street, Tucson, AZ, 85721-0207, USA.
³ Department of Research, Mayo Clinic Cancer Center, 13400 E. Shea Boulevard, Scottsdale, AZ 85259, USA.
⁴ Laboratoire de Physico-Chimie Informatique, Groupe de Chimie Physique Théorique et Structurale, University of Namur (FUNDP), 61 rue de Bruxelles, B-5000 Namur, Belgium phone: +32 (0)81 72 45 34; fax:+32 (0)81 72 54 66. daniel.vercauteren@fundp.ac.be.

PMID: 27481766
DOI: 10.1002/minf.201300009

Abstract

Early prediction of ADME properties such as the cytochrome P450 (CYP) mediated drug-drug interactions is an important challenge in the drug discovery area. In this study, we propose to couple an original data mining approach based on Rough Set Theory (RST) to a structural description of molecules. The latter was achieved by using two types of structural keys: (1) the MACCS keys and (2) a set of five in-house fingerprints based on properties of the electron density distributions of chemical groups. The compounds considered are involved in the inhibition of CYP1A2 and CYP2D6. RST allowed the extraction of rules further used as classifiers to predict the inhibitory profile of an independent set of molecules. The results reached prediction accuracies of 90.6 and 88.2 % for CYP1A2 and CYP2D6, respectively. In addition, these classifiers were analyzed to determine which structural fragments were most used for building the rules, revealing relationships between the occurrence of particular molecular fragments and CYP inhibition. The results assessed RST as a suitable tool to build strongly predictive models and infer structure-activity rules associated with potency.

Keywords: Chemoinformatics; Cytochromes P450; Electron density; Rough set theory; Structural fragments.