Machine learning methods and docking for predicting human pregnane X receptor activation.

The pregnane X receptor (PXR) regulates the expression of genes involved in xenobiotic metabolism and transport. In vitro methods to screen for PXR agonists are used widely. In the current study, computational models for human PXR activators and PXR nonactivators were developed using recursive partitioning (RP), random forest (RF), and support vector machine (SVM) algorithms with VolSurf descriptors. Following 10-fold randomization, the models correctly predicted 82.6-98.9% of activators and 62.0-88.6% of nonactivators. The models were validated using separate test sets. The overall ( n = 15) test set prediction accuracy for PXR activators with RP, RF, and SVM PXR models is 80-93.3%, representing an improvement over models previously reported. All models were tested with a second test set ( n = 145), and the prediction accuracy ranged from 63 to 67% overall. These test set molecules were found to cover the same area in a principal component analysis plot as the training set, suggesting that the predictions were within the applicability domain. The FlexX docking method combined with logistic regression performed poorly in classifying this PXR test set as compared with RP, RF, and SVM but may be useful for qualitative interpretion of interactions within the LBD. From this analysis, VolSurf descriptors and machine learning methods had good classification accuracy and made reliable predictions within the model applicability domain. These methods could be used for high throughput virtual screening to assess for PXR activation, prior to in vitro testing to predict potential drug-drug interactions.

Functional evolution of the pregnane X receptor.

The pregnane X receptor (PXR; NR1I2) is a nuclear hormone receptor (NR) that transcriptionally regulates genes encoding transporters and drug-metabolising enzymes in the liver and intestine. PXR activation leads to enhanced metabolism and elimination of xenobiotics and endogenous compounds such as hormones and bile salts. Relative to other vertebrate NRs, PXR has the broadest specificity for ligand activators by virtue of a large, flexible ligand-binding cavity. In addition, PXR has the most extensive sequence diversity across vertebrate species in the ligand-binding domain of any NR, with significant pharmacological differences between human and rodent PXRs, and especially marked divergence between mammalian and nonmammalian PXRs. The unusual properties of PXR complicate the use of in silico and animal models to predict in vivo human PXR pharmacology. Research into the evolutionary history of the PXR gene has also provided insight into the function of PXR in humans and other animals.

Apolipoprotein A-I alpha -helices 7 and 8 modulate high density lipoprotein subclass distribution.

Mice have a monodisperse high density lipoprotein (HDL) profile, whereas humans have two major subfractions designated HDL(2) and HDL(3). Human apoA-I transgenic mice exhibit a human-like HDL profile, indicating that the amino acid sequence of apoA-I is a determinant of the HDL profile. Comparison of the primary sequence of mouse and human apoA-I and the previously designated "hinge" domain of apoA-I led us to hypothesize that alpha-helices 7 and 8 (7/8) are determinants of HDL subclass distribution. The following proteins were expressed in Escherichia coli: human apoA-I, T7-hAI; mouse apoA-I, T7-mAI; chimeric human apoA-I containing murine helices 7/8 in place of human helices 7/8, T7-hAI(m7/8); and the reciprocal chimera, T7-mAI(h7/8). The recombinant proteins were examined for their association with human plasma HDL subclasses. The results demonstrated that T7-hAI bound HDL(2) and HDL(3) equally well, whereas T7-mAI bound to HDL(2) preferentially. T7-hAI(m7/8) behaved like T7-mAI, and T7-mAI(h7/8) behaved like T7-hAI. Thus, alpha-helices 7/8 are strong contributors to the pattern of HDL subclass association. Self-association, alpha-helicity, cholesterol efflux, and lecithin-cholesterol acyltransferase activity of the recombinant proteins were also assessed. Human apoA-I self-associates more and activates human lecithin-cholesterol acyltransferase better than mouse apoA-I. These differential characteristics of human and mouse apoA-I are not dependent on helices 7/8.