Spun out of the University of California San Francisco (UCSF), SeaChange uses a novel computational technology, the similarity ensemble approach, to discover opportunities in off-target drug binding. The Similarity Ensemble Approach (SEA) is a new method to predict drug side effects and target opportunities. This technology is motivated by two ideas: that proteins can be related by the ligands that bind to them, and that one can exploit these relationships to discover new targets for established drugs. The company has used SEA to predict new targets for 22 marketed drugs against 32 targets; 25 of them were confirmed in experiments. Examples include the Ã-blocking activity of Prozac and Paxil, consistent with two of the established, but unexplained, side effects of these drugs, the anti-serotonergic activity of Fabahistin, an anti-histamine now being advanced for Alzheimerâs, but whose primary targets are controversial, and the H4 histaminergic activity of the NNRTI AIDS drug Rescriptor. None of these off-target effects were previously known; all emerge quantitatively from the SEA calculation
