sb-269970 and zolmitriptan

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.

Topics: Algorithms; Animals; Clinical Trials as Topic; Female; Gene Expression; Gene Expression Profiling; Humans; Hyperesthesia; Male; Mice; Oxazolidinones; Pharmacogenetics; Phenols; Predictive Value of Tests; Receptors, Serotonin; Serotonin 5-HT1 Receptor Agonists; Serotonin 5-HT1 Receptor Antagonists; Sulfonamides; Tryptamines