Alarms about structural alerts.
Alarms about structural alerts.
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DOI：
10.1039/c6gc01492e
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发表时间：
2016-08-21
期刊：
影响因子：
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通讯作者：
Tropsha A
中科院分区：
文献类型：
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作者：
Alves V;Muratov E;Capuzzi S;Politi R;Low Y;Braga R;Zakharov AV;Sedykh A;Mokshyna E;Farag S;Andrade C;Kuz'min V;Fourches D;Tropsha A
结构警报在化学毒理学和监管决策支持中被广泛接受，作为一种简单而透明的方法来标记潜在的化学危害或将化合物分组以供阅读。然而，人们越来越担心警报不成比例地将太多化学物质标记为有毒，这质疑它们作为毒性标记的可靠性。相反，经过严格开发和适当验证的统计 QSAR 模型可以准确可靠地预测化学品的毒性；然而，由于缺乏透明度和可解释性，它们在监管毒理学中的使用受到了阻碍。我们证明，与 QSAR 模型作为“黑匣子”的普遍看法相反，它们可用于识别影响毒性的具有统计意义的化学子结构（基于 QSAR 的警报）。然而，我们通过几个案例研究表明，无论采用何种推导方法（基于专家或基于 QSAR），化学品中仅存在结构警报都应仅被视为可能毒理学效应的假设。我们提出了一种新方法，将结构警报和经过严格验证的 QSAR 模型协同整合，以对新化学品进行更透明、更准确的安全评估。
Structural alerts are widely accepted in chemical toxicology and regulatory decision support as a simple and transparent means to flag potential chemical hazards or group compounds into categories for read-across. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. Conversely, the rigorously developed and properly validated statistical QSAR models can accurately and reliably predict the toxicity of a chemical; however, their use in regulatory toxicology has been hampered by the lack of transparency and interpretability. We demonstrate that contrary to the common perception of QSAR models as “black boxes” they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. We show through several case studies, however, that the mere presence of structural alerts in a chemical, irrespective of the derivation method (expert-based or QSAR-based), should be perceived only as hypotheses of possible toxicological effect. We propose a new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals.