Assessing genotoxicity, specifically gene mutations and chromosomal aberrations, is fundamental to chemical risk assessment. Notably, the early identification of an aneugenic mechanism is of crucial importance, allowing, in principle, for a threshold-based risk assessment approach. To investigate this issue while pushing towards innovation in risk assessment by leveraging New Approach Methodologies, in silico approaches stand out as a particularly promising avenue. Building on these premises and given the lack of QSAR models for aneuploidy in the public domain, the present study exploited the genotoxicity-relevant alert lists implemented in the OECD QSAR Toolbox to base the investigation of structure-activity relationships for aneuploidy. To address the lack of relevant structured data resources, a dataset of 65 confirmed aneugenic substances was specifically curated and designed for the study. The results highlighted widely differing performances among the various profilers, confirming a general limited discriminatory power for aneuploidy. On the other hand, a granular analysis of the results from individual structural alerts enabled the successful isolation of some features associated with the aneugenic mode of action. Moreover, a subset of tubulin-binding chemicals was investigated to determine whether targeting a specific protein improves the characterization of toxicological alerts. The findings provide a refined definition of specific toxicity determinants for tubulin binders and serve as a promising tool for early hazard assessment, potentially informing relevant AOPs. While the computational approach appears promising, the overarching challenge that emerges is the limited availability of well-curated experimental data. In fact, reliable data on aneuploidy are scarce and fragmented across the literature. Furthermore, existing compilations of micronucleus study results are often complicated by conflicting interpretations.
Ricci et al. (Fri,) studied this question.