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American Chemical Society's Weekly PressPac -- Nov. 14, 2007

Scientists in Indiana and Michigan have developed a better way of mining a vast computerized database for chemical nuggets that could become tomorrows cancer medications. The new data mining method pinpoints chemical structures with drug-like activity. It could speed the identification and development of new, more effective drugs against breast, prostate, lung and other cancers, according to a report scheduled for the Nov./Dec. issue of ACS Journal of Chemical Information and Modeling, a bi-monthly publication.

Computers have become a mainstay in the drug discovery process and have led to the identification of dozens of promising anticancer drugs. However, as the amount and complexity of information in a chemical

In the new report, David J. Wild and colleagues analyzed data from the National Cancer Institute Developmental Therapeutics Program, a database of 40,000 compounds that have been tested against 60 tumor cell lines. The researchers identified a set of common structural features that can be used to more accurately predict which compounds are most active against cancer cells. In a series of experiments, they showed that applying these new criteria significantly increased the accuracy rate of identifying drug-like molecules in comparison to standard screening methods.


Chemical Data Mining of the NCI Human Tumor Cell Line Database



David J. Wild, Ph.D.
Indiana Universi

Contact: Michael Woods
American Chemical Society  

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American Chemical Society's Weekly PressPac -- Nov. 14, 2007
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