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  • Title: Identification of rodent carcinogens by an expert system.
    Author: Rosenkranz HS, Klopman G.
    Journal: Prog Clin Biol Res; 1990; 340B():23-48. PubMed ID: 2203007.
    Abstract:
    CASE, an artificial intelligence method for identifying structural determinants responsible for biological activity was applied to the U.S. National Toxicology Program (NTP) cancer bioassay results. CASE identified structures which were significantly associated with rodent carcinogenicity. On the basis of these structural determinants CASE exhibited a sensitivity of 0.98 and a specificity of 1.00. CASE showed a similarly remarkable performance in predicting the carcinogenicity, or lack thereof, of chemicals not in the NTP data base. A comparison between the activating structures (biophores) responsible for mutagenicity in Salmonella and rodent carcinogenicity showed a significant overlap, verifying that there are structural commonalities between the two phenomena. CASE also identified biophores significantly associated with the activity of non-genotoxic carcinogens, thereby suggesting the unexpected possibility that there is a structural commonality among the chemicals included in this group. A comparison between the biophores responsible for carcinogenicity in mice and rats resulted in the identification of common ("universal") biophores. It is suggested that agents which contain "universal" biophores are more likely to present a risk to human than carcinogens that do not possess such biophores. CASE also permitted the recognition of species-specific carcinogenic biophores. While the former are primarily electrophiles or potential electrophiles, the latter represent non-electrophilic structures.
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