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PDFOpen Access (License Unspecified), Open Access
Journal article
Evaluation of Computational Docking to Identify Pregnane X Receptor Agonists in the ToxCast Database
Environmental health perspectives, v 118(10), pp 1412-1417
2010
PMID: 20558333
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Background: The pregnane X receptor (PXR) is a key transcriptional regulator of many genes
[e.g., cytochrome P450s (CYP2C9, CYP3A4, CYP2B6), MDR1] involved in xenobiotic metabolism
and excretion.
Objectives: As part of an evaluation of different approaches to predict compound affinity for nuclear
hormone receptors, we used the molecular docking program GOLD and a hybrid scoring scheme
based on similarity weighted GoldScores to predict potential PXR agonists in the ToxCast database
of pesticides and other industrial chemicals. We present some of the limitations of different in vitro
systems, as well as docking and ligand-based computational models.
Methods: Each ToxCast compound was docked into the five published crystallographic structures
of human PXR (hPXR), and 15 compounds were selected based on their consensus docking scores
for testing. In addition, we used a Bayesian model to classify the ToxCast compounds into PXR
agonists and nonagonists. hPXR activation was determined by luciferase-based reporter assays in
the HepG2 and DPX-2 human liver cell lines.
Results: We tested 11 compounds, of which 6 were strong agonists and 2 had weak agonist activity.
Docking results of additional compounds were compared with data reported in the literature. The
prediction sensitivity of PXR agonists in our sample ToxCast data set (n = 28) using docking and the
GoldScore was higher than with the hybrid score at 66.7%. The prediction sensitivity for PXR agonists using GoldScore for the entire ToxCast data set (n = 308) compared with data from the NIH
(National Institutes of Health) Chemical Genomics Center data was 73.8%.
Conclusions: Docking and the GoldScore may be useful for prioritizing large data sets prior to
in vitro testing with good sensitivity across the sample and entire ToxCast data set for hPXR agonists
Metrics
Details
- Title
- Evaluation of Computational Docking to Identify Pregnane X Receptor Agonists in the ToxCast Database
- Creators
- Sandhya KORTAGERE - Drexel UniversityMatthew D KRASOWSKI - University of PittsburghErica J RESCHLY - University of PittsburghMadhukumar VENKATESH - Albert Einstein College of MedicineSridhar MANI - Albert Einstein College of MedicineSean EKINS - Collaborations in Chemistry, Jenkintown, Pennsylvania, United States
- Publication Details
- Environmental health perspectives, v 118(10), pp 1412-1417
- Publisher
- US Department of Health and Human Services; Research Triangle Park, NC
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Microbiology and Immunology
- Web of Science ID
- WOS:000282376900033
- Scopus ID
- 2-s2.0-77957903965
- Other Identifier
- 991014877680804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Environmental Sciences
- Public, Environmental & Occupational Health
- Toxicology