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Using high-throughput screening data to discriminate compounds with single-target effects from those with side effects.
|Publication Type||Journal Article|
|Authors||Klekota, J., Brauner E., Roth FP, and Schreiber SL|
|Abstract||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.|
|Year of Publication||2006|
|Journal||Journal of chemical information and modeling|
|Date Published (YYYY/MM/DD)||2006/05/18|