ArticleMutagenesis2019
Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: is aromatic N-oxide a structural alert for predicting DNA-reactive mutagenicity?
Article in Mutagenesis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The trial behind it
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Who cites it
4 citing papers in PubMed.
- Structure-mutagenicity relationships on quinoline and indole analogues in the Ames test.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2024Article
- Novel (Q)SAR models for prediction of reversible and time-dependent inhibition of cytochrome P450 enzymes.Frontiers in pharmacology · 2024Article
- A scheme to evaluate structural alerts to predict toxicity - Assessing confidence by characterising uncertainties.Regulatory toxicology and pharmacology : RTP · 2022Article
- Management of pharmaceutical ICH M7 (Q)SAR predictions - The impact of model updates.Regulatory toxicology and pharmacology : RTP · 2020Article
Corrections and comments
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Authors and funding
23 authors.
Funding
Abstract
(Quantitative) structure-activity relationship or (Q)SAR predictions of DNA-reactive mutagenicity are important to support both the design of new chemicals and the assessment of impurities, degradants, metabolites, extractables and leachables, as well as existing chemicals. Aromatic N-oxides represent a class of compounds that are often considered alerting for mutagenicity yet the scientific rationale of this structural alert is not clear and has been questioned. Because aromatic N-oxide-containing compounds may be encountered as impurities, degradants and metabolites, it is important to accurately predict mutagenicity of this chemical class. This article analysed a series of publicly available aromatic N-oxide data in search of supporting information. The article also used a previously developed structure-activity relationship (SAR) fingerprint methodology where a series of aromatic N-oxide substructures was generated and matched against public and proprietary databases, including pharmaceutical data. An assessment of the number of mutagenic and non-mutagenic compounds matching each substructure across all sources was used to understand whether the general class or any specific subclasses appear to lead to mutagenicity. This analysis resulted in a downgrade of the general aromatic N-oxide alert. However, it was determined there were enough public and proprietary data to assign the quindioxin and related chemicals as well as benzo[c][1,2,5]oxadiazole 1-oxide subclasses as alerts. The overall results of this analysis were incorporated into Leadscope's expert-rule-based model to enhance its predictive accuracy.
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Registered trials
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