Challenges predicting ligand-receptor interactions of promiscuous proteins: the nuclear receptor PXR

Abstract

Transcriptional regulation of some genes involved in xenobiotic detoxification and apoptosis is performed via the human pregnane X receptor (PXR) which in turn is activated by structurally diverse agonists including steroid hormones. Activation of PXR has the potential to initiate adverse effects, altering drug pharmacokinetics or perturbing physiological processes. Reliable computational prediction of PXR agonists would be valuable for pharmaceutical and toxicological research. There has been limited success with structure-based modeling approaches to predict human PXR activators. Slightly better success has been achieved with ligand-based modeling methods including quantitative structure-activity relationship (QSAR) analysis, pharmacophore modeling and machine learning. In this study, we present a comprehensive analysis focused on prediction of 115 steroids for ligand binding activity towards human PXR. Six crystal structures were used as templates for docking and ligand-based modeling approaches (two-, three-, four- and five-dimensional analyses). The best success at external prediction was achieved with 5D-QSAR. Bayesian models with FCFP_6 descriptors were validated after leaving a large percentage of the dataset out and using an external test set. Docking of ligands to the PXR structure co-crystallized with hyperforin had the best statistics for this method. Sulfated steroids (which are activators) were consistently predicted as non-activators while, poorly predicted steroids were docked in a reverse mode compared to 5alpha-androstan-3beta-ol. Modeling of human PXR represents a complex challenge by virtue of the large, flexible ligand-binding cavity. This study emphasizes this aspect, illustrating modest success using the largest quantitative data set to date and multiple modeling approaches.

Figure 1. Schematic representation of the binding mode of A. 5α-Androstan-3β-ol B epitestosterone sulfate C lithocholic acid acetate and D levonorgestrol in the binding site of crystal structure of human PXR protein (PDB code: 1M13).

The binding site residues are colored by their nature, with hydrophobic residues in green and charged residues in purple. Blue spheres and contours indicate matching regions between ligand and receptors. The schematic representations were generated using the LIGX option in MOE.

Figure 2. Good and bad molecular features identified in the Bayesian model using FCFP_6 fingerprints.

A. Good features from FCFP_6 Bayesian model, B. Bad features from FCFP_6 Bayesian model. Asterisks can represent any atom. Numbers represent how many molecules out of the total number possessing the fingerprint are active (good) or inactive (bad).

Figure 3. Receptor model for PXR obtained using Raptor (beige-brown, hydrophobic properties; red, hydrogen bond acceptor; blue, hydrogen-bond donor; and green, hydrogen bond donor/acceptor).

The most active ligand of each of the four substrate classes aligned to each other is displayed as sticks. A: Inner shell is displayed in surface representation, outer shell in wireframe. B: The bulky right portion of the outer shell corresponds to the solvent exposed region of the ligand alignment. It is dominated by a mixed hydrogen bond donor/acceptor character in agreement with solvent exposure.