A Review of Quantitative Structure-Activity Relationship (QSAR) Models to Predict Thyroid Hormone System Disruption...

Area of Science:

• Toxicology
• Computational Chemistry
• Endocrinology

Background:

• Thyroid hormone (TH) system disruption by chemicals impacts metabolism, growth, and brain development.
• Traditional animal testing for chemical hazard assessment is resource-intensive and ethically challenging.
• New Approach Methodologies (NAMs), like QSAR, are needed to improve chemical safety evaluations.

Purpose of the Study:

• To review and map the development of quantitative structure-activity relationship (QSAR) models for predicting thyroid hormone system disruption.
• To focus on QSARs addressing molecular initiating events within the adverse outcome pathway for TH disruption.
• To identify existing models, gaps, and inform future research for non-animal-based chemical hazard assessment.

Main Methods:

• Systematic literature review of QSAR models for TH disruption from 2010 to 2024.
• Selection of thirty papers based on predefined criteria, yielding eighty-six distinct QSAR models.
• Analysis of endpoints, chemical classes, data sources, modeling approaches, and molecular descriptors with mechanistic interpretations.

Main Results:

• Eighty-six QSAR models for predicting TH system disruption were identified across thirty reviewed papers.
• The review details the endpoints, chemical classes, data sources, and modeling strategies employed.
• Mechanistic interpretations of selected molecular descriptors provide insights into QSAR model applicability.

Conclusions:

• This review provides a state-of-the-art overview of QSAR models for assessing chemical impacts on the TH system.
• Identified gaps highlight areas for future research to advance non-animal-based chemical safety testing.
• The findings support the development of robust QSAR tools to mitigate risks associated with TH disruptors.