In Silico Identification of Human Pregnane X Receptor Activators
نویسنده
چکیده
The nuclear receptor member human pregnane X receptor (hPXR) regulates enzymes and transporters involved in xenobiotic detoxification as well as maintains homeostatic balance of bile acids, thyroid and steroid hormones. hPXR can be recognized and activated by a structurally diverse array of environmental chemicals and drug compounds to initiate adverse biological effects, such as perturbing normal physiological functions and causing dangerous drug–drug interactions and exhibiting a high promiscuity in its ligand spectrum. In the current study capabilities for structureactivity modeling incorporated in the platform QSAR Toolbox were employed for investigation the binding mode and structural basis of hPXR interactions with various activators and non-activators. A total of 348 molecules, representing a variety of chemical structures, constituted the training set of the model. Validation of the model showed a sensitivity of 70%, a specificity of 85%, and a concordance of 77%. The developed model provide knowledge about molecular descriptors that may influence the effect of molecules to hPXR.
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In silico prediction of pregnane X receptor activators by machine learning approaches.
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