Bulletin of Mathematical Biology

, Volume 72, Issue 7, pp 1799–1819

Development of a Quantitative Model of Pregnane X Receptor (PXR) Mediated Xenobiotic Metabolizing Enzyme Induction

Authors

    • Department of MathematicsNorth Carolina Agricultural and Technical State University
  • Michael J. DeVito
    • National Toxicology ProgramNational Institute for Environmental Health Sciences
  • Imran Shah
    • National Center for Computational ToxicologyORD, U.S. EPA
  • Hisham A. El-Masri
    • Integrated Systems Toxicology DivisionNHEERL, ORD, U.S. EPA
Original Article

DOI: 10.1007/s11538-010-9508-5

Cite this article as:
Luke, N.S., DeVito, M.J., Shah, I. et al. Bull. Math. Biol. (2010) 72: 1799. doi:10.1007/s11538-010-9508-5

Abstract

The pregnane X receptor plays an integral role in the regulation of hepatic metabolism. It has been shown to regulate CYP3A4, which is the most abundant cytochrome P450 in the human liver. With its large and flexible ligand-binding domain, PXR can be activated by an enormous range of relatively small, hydrophobic, exogenous compounds. Upon activation, PXR partners with the retinoid X receptor (RXR) to form a heterodimer. The newly formed heterodimer binds to an appropriate DNA response element, causing increased transcription. This leads to an induction in the level of CYP3A4. These mechanistic steps are included into a biologically-based mathematical model. The quantitative model predicts fold level inductions of CYP3A4 mRNA and protein in response to PXR activation. Model parameter values have been taken from literature when appropriate. Unknown parameter values are estimated by optimizing the model results to published in vivo and in vitro data sets. A sensitivity analysis is performed to evaluate the model structure and identify future data needs which would be critical to revising the model.

Keywords

Nuclear receptorsMathematical modelGene induction

Supplementary material

11538_2010_9508_MOESM1_ESM.pdf (259 kb)
Below is the link to the electronic supplementary material. (PDF 285KB)

Copyright information

© Society for Mathematical Biology 2010