Structural Alerts for Aneuploidy Prediction: Are We There Yet?

Area of Science:

• Toxicology
• Computational Chemistry
• Risk Assessment

Background:

• Genotoxicity assessment, including gene mutations and chromosomal aberrations, is vital for chemical risk assessment.
• Early identification of aneuploidy is crucial for adopting threshold-based risk assessment strategies.
• New Approach Methodologies, particularly in silico approaches, offer innovative pathways for risk assessment.

Purpose of the Study:

• To investigate structure-activity relationships for aneuploidy using computational tools.
• To address the lack of quantitative structure-activity relationship (QSAR) models for aneuploidy in the public domain.
• To curate a dataset of confirmed aneugenic substances for in silico analysis.

Main Methods:

• Utilized genotoxicity-relevant alert lists from the OECD QSAR Toolbox.
• Curated a dataset of 65 confirmed aneugenic substances.
• Analyzed structural alerts and investigated tubulin-binding chemicals for improved toxicological alert characterization.

Main Results:

• Evaluated the performance of various computational profilers, noting generally limited discriminatory power for aneuploidy.
• Identified specific structural alerts associated with the aneugenic mode of action through granular analysis.
• Refined the definition of toxicity determinants for tubulin binders, enhancing early hazard assessment.

Conclusions:

• Computational approaches show promise for early hazard assessment and informing Adverse Outcome Pathways (AOPs).
• A significant challenge remains the limited availability of well-curated experimental data on aneuploidy.
• Existing data on aneuploidy are scarce, fragmented, and often subject to conflicting interpretations, hindering model development.