New Bioinformatics Tool to Aid Drug Design

The method was reported in The Pharmacogenomics Journal, a Nature publication.

This approach relates gene expression patterns to more than 27,000 substructures and chemical features within compounds that have been tested for their effect on tumor cell growth. This is designed to improve on other methods that correlate molecular data with the anticancer activity of compounds but not with the substructures within those compounds. The new approach can also be applied to protein profiles. The approach was developed by scientists at the US National Cancer Institute (NCI) and LeadScope, Inc. (Columbus, OH, USA).

The method links three databases of information on cells and chemical compounds, based on data from more than 80,000 chemical compounds and 60 human cancer cell lines. Since 1990, NCI researchers have tested them for their ability to inhibit nine different types of cancer, known collectively as NCI-60. These cells were derived from melanoma, leukemia, and cancers of the lung, colon, breast, prostate, kidney, ovary, and central nervous system.

The first of the new databases includes data on the inhibitory effect of the compounds against each of the cell lines. Gene expression patterns of each cell line, determined by cDNA microarrays, make up the second database. Software from LeadScope (LeadMiner) relates this information to the final database, which identifies which of the 27,000 structural features are present in each of the compounds.

"Someone who is trying to design or perfect cancer drugs would ideally like to relate a gene or protein profile directly to drug structure,” said John Weinstein, Ph.D., one of the authors of the article. The new system does that. Databases linking biologic activity and gene expression to the 60 NCI cell lines are available at an NCI website or on the LeadScope website.





Related Links:
LeadScope
NCI website