Computer-assisted structure-activity studies of chemical carcinogens. Aromatic amines.
Studies of molecular structure-carcinogenicity relations for a set of 157 aromatic amines are reported. A computer-assisted approach using pattern-recognition methods was used to develop a series of discriminants for aromatic amino carcinogenic potential. The 157 compounds were divided into subsets according to tumor site, route of administration, and activity. Sets of calculated molecular structure descriptors were generated that could support linear discriminant functions able to separate sets of active carcinogens from inactive compounds. Prominent among the important structural descriptors were those coding sizes and shapes of the amines. The pattern-recognition results were not strongly affected by differences in active site, and the study showed that mixed data sets could be used in computer-assisted structure-carcinogenicity studies.
D000588:Amines / Q000633:toxicity*; D000818:Animals; D001665:Binding Sites; D002273:Carcinogens / Q000633:toxicity*; D003201:Computers; D010363:Pattern Recognition, Automated; D051381:Rats; D013329:Structure-Activity Relationship
D000588:Amines; D002273:Carcinogens