Dunn W J
Department of Medicinal Chemistry and Pharmacognosy, University of Illinois, Chicago 60612.
Toxicol Lett. 1988 Oct;43(1-3):277-83. doi: 10.1016/0378-4274(88)90033-1.
Due to the demands of time and the high cost of testing compounds for toxicity in test animals, it would be an advantage to be able to estimate the toxic response of chemical agents using theoretical approaches. Predicting whether a compound will be toxic or nontoxic is a classification problem and the methods of studying quantitative structure activity relationships (QSAR) can be used for this purpose [Hansch, C. (1969) Accounts Chem. Res., 2, 232]. It should be recognized, however, that formulating the QSAR problem as one of active vs. inactive makes it different from classical QSAR problems. This requires that methods be applied that can predict the category of a compound to be used, i.e., so-called methods of pattern recognition (Varmuza, K. (1983) J. Chem. Info. Comp. Sci. 23, 6) being required. There are several methods of pattern recognition that can be used with some being more suitable than others. The nature of this unique QSAR problem, the appropriate methods to apply, and some of the pitfalls of applying QSAR techniques to predicting toxicity are discussed.
由于时间的限制以及在实验动物身上测试化合物毒性的成本高昂，能够使用理论方法估计化学试剂的毒性反应将是一大优势。预测一种化合物是否有毒是一个分类问题，研究定量构效关系（QSAR）的方法可用于此目的[Hansch, C. (1969) Accounts Chem. Res., 2, 232]。然而，应该认识到，将QSAR问题表述为活性与非活性问题之一使其有别于经典的QSAR问题。这就需要应用能够预测所用化合物类别的方法，即所谓的模式识别方法（Varmuza, K. (1983) J. Chem. Info. Comp. Sci. 23, 6）。有几种模式识别方法可供使用，其中一些比其他方法更合适。本文讨论了这种独特的QSAR问题的性质、适用的适当方法以及将QSAR技术应用于预测毒性时的一些陷阱。
