2009 November 12 | Michael J. Keiser, Vincent Setola, John J. Irwin, Christian Lagner, Atheir Abbas, Sandra J. Huheisen, Niels H. Jensen, Michael B. Kuijjer, Roberto C. Matos, Thuy B. Tran, Ryan Whaley, Richard A. Glennon, Jérôme Hert, Kelan L.H. Thomas, Douglas D. Edwards, Brian K. Shoichet, and Bryan L. Roth
The article presents a computational approach to predict new drug-target associations, known as the Similarity Ensemble Approach (SEA). The authors compared 3,665 FDA-approved and investigational drugs against hundreds of targets defined by their ligands, using chemical similarities between drugs and ligand sets to identify thousands of previously unknown associations. They tested 30 of these predictions experimentally, confirming 23 new drug-target associations, five of which had potent affinities (< 100 nM). The study highlights the systematic and comprehensive nature of the chemical similarity approach, which can suggest side effects and new indications for many drugs. The authors also discuss the biological relevance of these new off-targets, including their role in primary drug actions, side effects, and interactions across major protein boundaries. The findings underscore the importance of exploring drug polypharmacology to better understand drug effects and potential therapeutic opportunities.The article presents a computational approach to predict new drug-target associations, known as the Similarity Ensemble Approach (SEA). The authors compared 3,665 FDA-approved and investigational drugs against hundreds of targets defined by their ligands, using chemical similarities between drugs and ligand sets to identify thousands of previously unknown associations. They tested 30 of these predictions experimentally, confirming 23 new drug-target associations, five of which had potent affinities (< 100 nM). The study highlights the systematic and comprehensive nature of the chemical similarity approach, which can suggest side effects and new indications for many drugs. The authors also discuss the biological relevance of these new off-targets, including their role in primary drug actions, side effects, and interactions across major protein boundaries. The findings underscore the importance of exploring drug polypharmacology to better understand drug effects and potential therapeutic opportunities.