Related Experiment Video
Updated: May 6, 2026

Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
Published on: November 15, 2013
A novel screening method for cytochrome P450 induction in early drug discovery using advanced biomimetic
Hiroko Okawa1, Satoru Kobayashi2, Toshio Taniguchi2
1Drug Metabolism and Pharmacokinetics Research Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., Osaka, Japan; Education and Research Center for Clinical Pharmacy, Osaka Medical and Pharmaceutical University, Takatsuki, Osaka 569-1094, Japan.
Abstract:
One of the main reasons for drug development failure is pharmacokinetics, specifically, the risk that Cytochrome P450 (CYP) induction potential may prevent drugs from achieving their expected efficacy due to a reduction in the blood concentration of concomitant drugs or the drug itself. It is therefore desirable to select compounds with a low induction potential, but HepaRG cell and other in vitro induction assays are not sufficient to evaluate induction potential due to throughput and evaluation system limitation. We therefore evaluated the predictivity of CYP induction using advanced biomimetic chromatography (aBMC) that applies biomimetic chromatography for assessing affinity to the pregnane X receptor (PXR). We prepared a PXR-immobilized column for the first time, and evaluated its performance in terms of immobilized efficiency, stability, and recovery ratio of the number of eluted to injected test compounds. Investigation of 42 different compounds including both CYP induction-positive and -negative compounds, suggested that the retention time difference (ΔRT) between the PXR and reference columns obtained from aBMC was significantly more related to CYP induction than LogD and LogK (HSA), which indicate affinity for albumin, and has practical predictivity for judging CYP induction (74 % accuracy, 83 % sensitivity, 67 % precision). This novel prediction method is expected to improve the quality of drug candidates and the probability of successful drug development.

