Benigni R
Dept. of Environment and Primary Prevention, Istituto Superiore di Sanita', Rome, Italy.
J Exp Clin Cancer Res. 2004 Mar;23(1):5-8.
Chemical carcinogenicity has been the target of numerous attempts to create predictive models alternative to the animal ones, ranging from short-term biological assays (e.g. mutagenicity tests) to theoretical models. Among the theoretical models, the application of the science of Structure-Activity Relationships (SAR) has earned special prominence. SAR has been applied both in a qualitative way (for example as simple recognition of suspected sub-structures or Structural Alerts), and in a quantitative way (Quantitative SAR, QSAR) to build mathematical models linking the physical chemical or structural properties of the molecules to the toxicological endpoints. This paper summarizes the contribution that the two approaches can provide in different situations. It concludes that the study of the structure of the chemicals generates predictions with limited reliability for the individual chemicals, however it has been demonstrated to be an extremely powerful tool for priority setting relative to large samples of chemicals.
化学致癌性一直是众多尝试建立替代动物模型的预测模型的目标,这些尝试涵盖了从短期生物学检测(如致突变性测试)到理论模型等多种方法。在理论模型中,构效关系(SAR)科学的应用尤为突出。SAR 已被用于定性(例如简单识别可疑子结构或结构警示)和定量(定量构效关系,QSAR)两种方式,以建立将分子的物理化学或结构性质与毒理学终点联系起来的数学模型。本文总结了这两种方法在不同情况下所能提供的贡献。结论是,对化学品结构的研究对于单个化学品产生的预测可靠性有限,然而,它已被证明是相对于大量化学品样本进行优先级设定的极其强大的工具。