Stouch T R, Jurs P C
Environ Health Perspect. 1985 Sep;61:329-43. doi: 10.1289/ehp.8561329.
Often a compound's biological activity is determined by complex relationships between its structural components. Such a relationship often can only be adequately described and exploited by multivariate structure-activity relationship (SAR) studies that can deal with many variables simultaneously. Pattern recognition (PR) is a multivariate technique that is well suited for the qualitative, active-inactive, data that is often supplied by biological assays. PR studies of compounds of known activity can yield information that will allow the prediction of the activity of untested compounds. ADAPT is a computerized system that was developed for such PR-SAR studies. A general introduction to this field is presented and the methodology used for such a study is described in the context of an actual study of mutagenic compounds. The data requirements, descriptor generation, and the details of a PR study are discussed. In addition, the example study was chosen to highlight the problems that may occur if a study is not well formulated and carefully executed. Current work and future plans for computerized mutagen screening are discussed.
通常,化合物的生物活性由其结构组分之间的复杂关系决定。这种关系往往只能通过能够同时处理多个变量的多变量构效关系(SAR)研究来充分描述和利用。模式识别(PR)是一种多变量技术,非常适合处理生物测定中经常提供的定性、活性-非活性数据。对已知活性化合物的PR研究可以产生信息,从而预测未测试化合物的活性。ADAPT是一个为此类PR-SAR研究而开发的计算机化系统。本文对该领域进行了概述,并结合对诱变化合物的实际研究描述了此类研究使用的方法。讨论了数据要求、描述符生成以及PR研究的细节。此外,选择该实例研究以突出如果研究设计不当且执行不仔细可能出现的问题。还讨论了计算机化诱变筛选的当前工作和未来计划。