Amberg Alexander, Anger Lennart T, Bercu Joel, Bower David, Cross Kevin P, Custer Laura, Harvey James S, Hasselgren Catrin, Honma Masamitsu, Johnson Candice, Jolly Robert, Kenyon Michelle O, Kruhlak Naomi L, Leavitt Penny, Quigley Donald P, Miller Scott, Snodin David, Stavitskaya Lidiya, Teasdale Andrew, Trejo-Martin Alejandra, White Angela T, Wichard Joerg, Myatt Glenn J
Sanofi, R&D Preclinical Safety Frankfurt, Industriepark Höchst, Frankfurt am Main, Germany.
Gilead Sciences, Nonclinical Safety and Pathobiology, Foster City, CA, USA.
Mutagenesis. 2019 Mar 6;34(1):67-82. doi: 10.1093/mutage/gey020.
(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.
(定量)构效关系或(Q)SAR对DNA反应性致突变性的预测对于支持新化学品的设计以及杂质、降解产物、代谢物、可提取物和浸出物以及现有化学品的评估都很重要。芳香族N-氧化物是一类常被认为具有致突变性警示作用的化合物,但其这种结构警示的科学原理尚不清楚且受到质疑。由于含芳香族N-氧化物的化合物可能以杂质、降解产物和代谢物的形式出现,准确预测这类化学品的致突变性很重要。本文分析了一系列公开可用的芳香族N-氧化物数据以寻找支持信息。本文还使用了先前开发的构效关系(SAR)指纹方法,生成了一系列芳香族N-氧化物子结构,并与包括药物数据在内的公共和专有数据库进行匹配。通过评估所有来源中与每个子结构匹配的致突变和非致突变化合物的数量,来了解该类别或任何特定子类是否似乎会导致致突变性。该分析导致对一般芳香族N-氧化物警示的降级。然而,确定有足够的公共和专有数据将醌二噁英及相关化学品以及苯并[c][1,2,5]恶二唑1-氧化物子类指定为警示。该分析的总体结果被纳入Leadscope基于专家规则的模型中,以提高其预测准确性。