New Database Screening Criteria Improves Identification Of Anticancer Drugs

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.

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 increases, new analysis methods need to keep pace.

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.

The journal article"Chemical Data Mining of the NCI Human Tumor Cell Line Database" is scheduled for publication in the Nov./Dec. issue of ACS' Journal of Chemical Information and Modeling.