Significance Analysis and Multiple Pharmacophore Models for Differentiating P-Glycoprotein Substrates

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• 作者：Wu-Xiong Li ; Leping Li ; John Eksterowicz ; Xuefeng Bruce Ling ; Mario Cardozo
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2007
• 出版时间：November 2007
• 年：2007
• 卷：47
• 期：6
• 页码：2429 - 2438
• 全文大小：159K
• 年卷期：v.47,no.6(November 2007)
• ISSN：1549-960X

文摘

P-glycoprotein (Pgp) mediated drug efflux affects the absorption, distribution, and clearance of a broadstructural variety of drugs. Early assessment of the potential of compounds to interact with Pgp can aid inthe selection and optimization of drug candidates. To differentiate nonsubstrates from substrates of Pgp, arobust predictive pharmacophore model was targeted in a supervised analysis of three-dimensional (3D)pharmacophores from 163 published compounds. A comprehensive set of pharmacophores has been generatedfrom conformers of whole molecules of both substrates and nonsubstrates of P-glycoprotein. Four-point 3Dpharmacophores were employed to increase the amount of shape information and resolution, including theability to distinguish chirality. A novel algorithm of the pharmacophore-specific t-statistic was applied tothe actual structure-activity data and 400 sets of artificial data (sampled by decorrelating the structure andPgp efflux activity). The optimal size of the significant pharmacophore set was determined through thisanalysis. A simple classification tree using nine distinct pharmacophores was constructed to distinguishnonsubstrates from substrates of Pgp. An overall accuracy of 87.7% was achieved for the training set and87.6% for the external independent test set. Furthermore, each of nine pharmacophores can be independentlyutilized as an accurate marker for potential Pgp substrates.