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Transducer Mechanism: Nuclear Receptors

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About 48 different soluble family members of nuclear receptors are identified that can be divided into two main classes:

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High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes

High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes

Published on: March 3, 2015

Mining a human transcriptome database for chemical modulators of NRF2.

John P Rooney^1,2, Brian Chorley¹, Steven Hiemstra³

¹Center for Computational Toxicology and Exposure, US-EPA, Research Triangle Park, NC, United States of America.

|September 28, 2020

Summary

We developed a computational tool to identify chemicals that affect Nuclear factor erythroid-2 related factor 2 (NRF2) activity. This NRF2 biomarker accurately predicts chemical effects on cells, discovering new modulators.

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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Area of Science:

Biochemistry
Molecular Biology
Toxicology

Background:

Nuclear factor erythroid-2 related factor 2 (NRF2) is a key transcription factor regulating cellular defense against oxidative stress.
Identifying chemical modulators of NRF2 is crucial for understanding cellular responses to xenobiotics and developing protective strategies.

Purpose of the Study:

To develop and validate a gene expression biomarker for identifying chemical modulators of NRF2 activity.
To screen a large chemical database for novel NRF2-activating and -suppressing compounds.

Main Methods:

Computational analysis of human microarray data to build a 143-gene NRF2 biomarker.
Statistical filtering and siRNA knockdown experiments to ensure biomarker specificity for NRF2.
Application of the Running Fisher algorithm to predict NRF2 activity across thousands of chemical treatments.

Main Results:

The NRF2 biomarker achieved 93% balanced accuracy in predicting chemical effects.
The biomarker identified 260 novel NRF2 activators and 43 novel NRF2 suppressors among ~2260 tested chemicals.
Reporter gene assays confirmed the predictive accuracy of the biomarker for selected compounds.

Conclusions:

A robust gene expression biomarker for NRF2 activity has been developed and validated.
This tool significantly expands the known landscape of chemical NRF2 modulators.
The biomarker is a valuable resource for future screening of environmentally relevant chemicals and drug discovery.