The nuclear receptor pregnane X receptor (PXR) is referred to as the �master� regulator of pathways involving the major
metabolic enzymes and can be activated by a wide range of structurally diverse endogenous and xenobiotic molecules.
In addition, the activation of PXR has significant impact on drug metabolism and efflux as well as drug-drug interactions.
Identification of PXR activators is of critical importance in analyzing metabolism and pharmacokinetic profiles and detecting
potential adverse drug-drug interactions in the process of drug discovery and development, which, however, cannot be accurately
modeled without taking into account the promiscuous nature of hPXR. A predictive model was derived to predict the activation
of hPXR using the novel pharmacophore ensemble/support vector machine (PhE/SVM) scheme. The derived PhE/SVM model is
an accurate and robust predictive model as manifested by those samples in the training set, test set, and outlier set. Furthermore,
the calculated results are consistent with the published hPXR-ligand cocomplex structure and the plasticity nature of hPXR is also
revealed when compared with crystal structures.
Max K. Leong received the Ph.D. degree in Chemical Physics from University of Texas at Austin, USA. Afterward, he worked as a post-doc associate at the College of Pharmacy, University of Texas at Austin, USA. His career started from in silico drug discovery and later expanded to in silico ADME/ Tox. Currently, he is an editorial board member of Journal of Bioanalysis & Biomedicine and Journal of Bioequivalence & Bioavailability.
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