Abstract
A SAR based carcinogenic toxicity prediction system, CISOC-PSCT, was developed. It consisted of two principal phases: the construction of relationships between structural descriptors and carcinogenic toxicity indices, and prediction of the toxicity from the SAR model. The training set included 2738 carcinogenic and 4130 non-carcinogenic compounds. Three predefined topological types of substructures termed Star, Path and Ring were used to generate the descriptors for each structure in the training set. In this system, the defined carcinogenic toxicity index (CTI) was obtained from the probability of a structural descriptor to either belong to the carcinogenic or non-carcinogenic compounds. Based on these structural descriptors and their CTI, a SAR model was derived. Then the carcinogenic possibility (CP) and the carcinogenic impossibility (CIP) of compounds were predicted. The model was tested from a testing set of 304 carcinogenic compounds (MDL toxicity database), 460 non-carcinogenic compounds (CMC database) and 94 compounds extracted from two traditional Chinese medicine herbs.
Acknowledgements
Chemical structures of active compounds in “BAI SHAO” (“White Peony Root” or “Radix paeoniae alba”) and “DANG GUI” (“Angelica sinensis delis”) were provided by Shanghai Innovative Research Center of Traditional Chinese Medicine (SIRC/TCM). We gratefully acknowledge financial support from the Ministry of Science and Technology of China work for two projects (2002AA231011) and (2003CB114401), the Science and Technology Committee of Shanghai (02DJ14013), the Chinese Academy of Sciences and the National Center of Scientific Research in France Cooperation Program (CNRS/CAS No 14916).
Notes
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