title: New structural concepts for predicting carcinogenicity in rodents: an artificial intelligence approach.
abstract: The Computer Automated Structure Evaluation (CASE) method for studying structure-activity relationships has been applied to a data base of rodent carcinogens. It has been demonstrated that CASE is able to identify determinants embedded in the molecular structure which, with a high probability, predict rodent carcinogenicity. CASE has also identified determinants associated with the activity of non-genotoxic carcinogens, thereby suggesting that there is a structural commonality in the activity of these molecules. The present study reveals that there are "universal" as well as species-specific structural determinants of carcinogenicity. CASE was able to predict the carcinogenicity in rodents of certain endogenous pesticides in edible plants.
authors.affiliation: Department of Environmental and Health Sciences, Case Western Reserve University, Cleveland, Ohio 44106.
authors.forename: H S
authors.initials: HS
authors.lastname: Rosenkranz
authors.forename: G
authors.initials: G
authors.lastname: Klopman
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D002273:Carcinogens; D007256:Information Systems; D012377:Rodentia; D012680:Sensitivity and Specificity; D013329:Structure-Activity Relationship
chemical_list: D002273:Carcinogens