title: A data mining approach for the elucidation of the action of putative etiological agents: application to the non-genotoxic carcinogenicity of genistein.
abstract: A procedure designated "the virtual similarity index" (VSI) is described to determine the probability that two or more toxicants are related mechanistically. The approach is structure-activity relationship (SAR) based and generates the virtual toxicological profiles of the chemicals under investigation. It also determines the similarities between them. That commonality is compared to the frequency with which it is found among a population of 10,000 chemicals representing the "universe of chemicals". The similarities between the candidate chemicals and chemicals known to act by other recognized mechanisms are also determined. If the similarities between the candidate chemicals are significantly greater than for the non-related ones, the chemicals are assumed to act by a common mechanism. In that context, the putative non-genotoxic mechanism responsible for the carcinogenicity of genistein (GEN) and its relationship to the action of diethylstilbestrol is examined.
authors.affiliation: Department of Biomedical Sciences, Florida Atlantic University, 777 Glades Road, P.O. Box 3091, Boca Raton 33431, USA. rosenkra@fau.edu
authors.forename: Herbert S
authors.initials: HS
authors.lastname: Rosenkranz
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000494:pharmacology*; D015197:Carcinogenicity Tests; D002273:Carcinogens / Q000494:pharmacology*; D004054:Diethylstilbestrol / Q000494:pharmacology*; D019833:Genistein / Q000494:pharmacology*; D007256:Information Systems; D051379:Mice; D009152:Mutagenicity Tests; D009153:Mutagens / Q000494:pharmacology*; D009369:Neoplasms / Q000188:drug therapy* / Q000209:etiology; D051381:Rats; D013223:Statistics as Topic; D013329:Structure-Activity Relationship
chemical_list: D000970:Antineoplastic Agents; D002273:Carcinogens; D009153:Mutagens; D004054:Diethylstilbestrol; D019833:Genistein