CTIS, 69140 Rillieux La Pape, France.
SAR QSAR Environ Res. 2009 Jul;20(5-6):467-500. doi: 10.1080/10629360903278651.
With the ever-growing number of xenobiotics that can potentially contaminate the environment, the determination of their mammalian toxicity is of prime importance. In this context, LD50 tests on rats and mice have been used for a long time to express the relative hazard associated with the acute toxicity of inorganic and organic chemicals. However, these laboratory tests encounter important hurdles. They are costly, time consuming and actively opposed by animal rights activists. Moreover, new legislation policies, such as REACH (Registration, Evaluation, Authorization and Restriction of Chemicals), aim at reducing the use of toxicity tests on vertebrates. Consequently, there is a need to find alternative methods for estimating the acute mammalian toxicity of chemicals. The quantitative structure-activity relationships (QSARs) and interspecies correlations appear particularly suited to reaching this goal. In this context, this paper reviews more than 150 models aiming at predicting rat and mouse LD50 values from molecular descriptors or (and) ecotoxicity data. The interest of these computational tools is discussed.
随着越来越多的可能污染环境的外来化合物，确定它们对哺乳动物的毒性变得尤为重要。在这种情况下，大鼠和小鼠的 LD50 测试长期以来一直用于表达与无机和有机化学品急性毒性相关的相对危害。然而，这些实验室测试遇到了重要的障碍。它们成本高、耗时且受到动物权利活动家的强烈反对。此外，新的立法政策，如 REACH（化学品注册、评估、授权和限制），旨在减少对脊椎动物毒性测试的使用。因此，有必要寻找替代方法来估计化学品的急性哺乳动物毒性。定量构效关系（QSAR）和种间相关性似乎特别适合实现这一目标。在这种情况下，本文综述了 150 多个模型，这些模型旨在从分子描述符或（和）生态毒性数据预测大鼠和小鼠的 LD50 值。讨论了这些计算工具的意义。
