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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.

Using the ADAPT and CHEMLAB-II systems for structure-activity analysis, computer-calculated electronic properties of molecules were used to derive structure-activity relationships for predicting the mutagenicity of a set of substituted acridines in strain TA1537 of the Ames Salmonella assay. A collection of 40 acridines, with a variety of substituents, was examined. A set of 4 electronic descriptors was found which could be used to correctly classify all but two of the compounds as mutagenic or nonmutagenic. A negative correlation was found between the sum of the Hammett aromatic substituent parameters and the level of mutagenicity of the structures, expressed as log(number of revertants/plate + 1) at a 20-micrograms dose. This correlation, however, was not high enough to allow precise estimation of the mutagenicity values.