Solutions Case Studies
Download DocumentPredicting the carcinogenic potential of pharmaceuticals using molecular structural similarity and E-state indices
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.
Published by Elsevier Inc.
To read the complete case study, click the Download Document link near the top of the this article.
Joseph F. Contrera, Edwin J. Matthews and R. Daniel Benz
Reprinted from Regulatory Toxicology and Pharmacology, Volume 38, Issue 3, December 2003, Pages 243-259, Copyright © 2003, with permission from Elsevier.
