title: Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices.
abstract: MDL QSAR (formerly SciVision QSAR IS) software is one of the several software systems under evaluation by the Informatics and Computational Safety Analysis Staff (ICSAS) of the FDA Center for Drug Evaluation and Research for regulatory and scientific decision support applications. MDL QSAR software contains an integrated set of tools for similarity searching, compound clustering, and modeling molecular structure related parameters that includes 240 electrotopological E-state, connectivity, and other descriptors. These molecular descriptors can be statistically correlated with toxicological or biological endpoints. The goal of this research was to evaluate the feasibility of using MDL QSAR software to develop structure-activity relationship (SAR) models that can be used to predict the carcinogenic potential of pharmaceuticals and organic chemicals. A validation study of 108 compounds that include 86 pharmaceuticals and 22 chemicals that were not present in a control rodent carcinogenicity data set of 1275 compounds demonstrated that MDL QSAR models had excellent coverage (93%) and good sensitivity (72%) and specificity (72%) for rodent carcinogenicity. The software correctly predicted 72% of non-carcinogenic compounds and compounds with carcinogenic findings. E-state descriptors contributed to more than half of the SAR models used to predict carcinogenic activity. We believe that electrotopological E-state descriptors and QSAR IS (MDL QSAR) software are promising new in silico approaches for modeling and predicting rodent carcinogenicity and may have application for other toxicological endpoints.
authors: US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Pharmaceutical Science (HFD-901), Informatics and Computational Safety Analysis Staff (ICSAS), Rockville, MD 20857, USA. contrerajf@cder.fda.gov
authors: Joseph F
authors: JF
authors: Contrera
authors: Edwin J
authors: EJ
authors: Matthews
authors: R
authors: R
authors: Daniel Benz
mesh_terms: D000465:Algorithms; D000818:Animals; D015197:Carcinogenicity Tests / Q000379:methods; D002273:Carcinogens / Q000633:toxicity; D003201:Computers; D003628:Database Management Systems; D017277:Drug Approval; D004353:Drug Evaluation, Preclinical; D064420:Drug-Related Side Effects and Adverse Reactions; D005260:Female; D005544:Forecasting; D008297:Male; D008779:Methylthiouracil / Q000737:chemistry / Q000633:toxicity; D051379:Mice; D009930:Organic Chemicals / Q000633:toxicity*; D021281:Quantitative Structure-Activity Relationship; D051381:Rats; D015203:Reproducibility of Results; D012984:Software; D014481:United States
chemical_list: D002273:Carcinogens; D009930:Organic Chemicals; D008779:Methylthiouracil