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Journal of chemical information and modeling DOI:10.1021/ci050495h

Using high-throughput screening data to discriminate compounds with single-target effects from those with side effects.

Publication TypeJournal Article
Year of Publication2006
AuthorsKlekota, J, Brauner, E, Roth, FP, Schreiber, SL
JournalJournal of chemical information and modeling
Date Published2006/05/18

The most desirable compound leads from high-throughput assays are those with novel biological activities resulting from their action on a single biological target. Valuable resources can be wasted on compound leads with significant 'side effects' on additional biological targets; therefore, technical refinements to identify compounds that primarily have effects resulting from a single target are needed. This study explores the use of multiple assays of a chemical library and a statistic based on entropy to identify lead compound classes that have patterns of assay activity resulting primarily from small molecule action on a single target. This statistic, called the coincidence score, discriminates with 88% accuracy compound classes known to act primarily on a single target from compound classes with significant side effects on nonhomologous targets. Furthermore, a significant number of the compound classes predicted to have primarily single-target effects contain known bioactive compounds. We also show that a compound's known biological target or mechanism of action can often be suggested by its pattern of activities in multiple assays.