ArticlePLoS computational biology2009
Challenges predicting ligand-receptor interactions of promiscuous proteins: the nuclear receptor PXR.
Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
37 citing papers in PubMed, 107 citations in OpenAlex.
- Structure-based machine learning model for discovering pregnane X receptor (PXR) agonists and biological activity validation.Archives of toxicology · 2026Article
- Applications of artificial intelligence in drug discovery for neurological diseases.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Review
- Clinical Relevance of the Constitutive Androstane Receptor.Drug metabolism and disposition: the biological fate of chemicals · 2022Review
- Predicting the binding of small molecules to nuclear receptors using machine learning.Briefings in bioinformatics · 2022Article
- Article
- Discrepancy in interactions and conformational dynamics of pregnane X receptor (PXR) bound to an agonist and a novel competitive antagonist.Computational and structural biotechnology journal · 2022Article
- Overcoming the Pregnane X Receptor Liability: Rational Design to Eliminate PXR-Mediated CYP Induction.ACS medicinal chemistry letters · 2021Article
- Identification of novel pregnane X receptor (PXR) agonists by In silico and biological activity analyses and reversal of cigarette smoke-induced PXR downregulation.Biochemical and biophysical research communications · 2021Article
- Drug Mimicry: Promiscuous Receptors PXR and AhR, and Microbial Metabolite Interactions in the Intestine.Trends in pharmacological sciences · 2020Review
- In Silico Predictions of Endocrine Disruptors Properties.Endocrinology · 2019Review
- Back to the future: Advances in development of broad-spectrum capsid-binding inhibitors of enteroviruses.European journal of medicinal chemistry · 2019Review
- Repurposing Approved Drugs as Inhibitors of KPharmaceutical research · 2019Article
- New Aspects of Vitamin K Research with Synthetic Ligands: Transcriptional Activity via SXR and Neural Differentiation Activity.International journal of molecular sciences · 2019Review
- Exploring the PXR ligand binding mechanism with advanced Molecular Dynamics methods.Scientific reports · 2018Article
- The Roles of Xenobiotic Receptors: Beyond Chemical Disposition.Drug metabolism and disposition: the biological fate of chemicals · 2018Review
- SPA70 is a potent antagonist of human pregnane X receptor.Nature communications · 2017Article
- Predictive models for identifying the binding activity of structurally diverse chemicals to human pregnane X receptor.Environmental science and pollution research international · 2017Article
- Mechanisms of xenobiotic receptor activation: Direct vs. indirect.Biochimica et biophysica acta · 2016Review
- In silico investigation of agonist activity of a structurally diverse set of drugs to hPXR using HM-BSM and HM-PNN.Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban · 2016Article
- Alignment-independent technique for 3D QSAR analysis.Journal of computer-aided molecular design · 2016Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.