期刊
CURRENT DRUG METABOLISM
卷 10, 期 4, 页码 339-346出版社
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/138920009788499021
关键词
P-glycoprotein; MDR1; Multidrug resistance; Calcein AM assay; QSAR; decision trees
资金
- EU FP7 project OpenTox [F5-2008200787]
In silico classification of new compounds for certain properties is a useful tool to guide further experiments or compound selection. Interaction of new compounds with the efflux pump P-glycoprotein (P-gp) is an important drug property determining tissue distribution and the potential for drug-drug interactions. We present three datasets on substrate, inhibitor, and inducer activities for P-gp (n = 471) obtained from a literature search which we compared to an existing evaluation of the Prestwick Chemical Library with the calcein-AM assay ( retrieved from PubMed). Additionally, we present decision tree models of these activities with predictive accuracies of 77.7 % (substrates), 86.9% (inhibitors), and 90.3% (inducers) using three algorithms (CHAID, CART, and C4.5). We also present decision tree models of the calcein-AM assay (79.9%). Apart from a comprehensive dataset of P-gp interacting compounds, our study provides evidence of the efficacy of logD descriptors and of two algorithms not commonly used in pharmacological QSAR studies ( CART and CHAID).
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