Structure-activity considerations in risk assessment: a simulation study.

Abstract

The use of quantitative structure-activity relationships (QSAR) is considered with respect to estimating the carcinogenic risk of untested chemicals. SAR derived from a retrospective classification of a series of aromatic amines were used to study the estimation of carcinogenic risk by analogy. Using pattern recognition methods, a series of molecular descriptors were developed for a data set of aromatic amines that supported a linear discriminant function capable of separating compounds testing positively for carcinogenicity from those testing negatively. Linear discriminant analysis correctly categorized the compounds as positive or negative in 94.9% of the cases. For each aromatic amine within the subset of positive compounds, the most appropriate analogue was identified using physicochemical, topological, geometric and electronic molecular descriptors as variables. An upper-limit unit risk estimate was calculated for each compound that was a positive carcinogen within the data set using the linearized multistage model. The actual risk and the risk estimated by analogy to a congener were compared for each compound within the positive subset. The results support estimating both qualitative and quantitative carcinogenic risk by analogy for this particular data set.