Abstract

Of great interest in recent years has been computationally predicting the novel polypharmacology of drug molecules. Here, we applied an “induced-fit” protocol to improve the homology models of 5-HT<sub>2A</sub> receptor, and we assessed the quality of these models in retrospective virtual screening. Subsequently, we computationally screened the FDA approved drug molecules against the best induced-fit 5-HT<sub>2A</sub> models and chose six top scoring hits for experimental assays. Surprisingly, one well-known kinase inhibitor, sorafenib, has shown unexpected promiscuous 5-HTRs binding affinities, <i>K</i><sub>i</sub> = 1959, 56, and 417 nM against 5-HT<sub>2A</sub>, 5-HT<sub>2B</sub>, and 5-HT<sub>2C</sub>, respectively. Our preliminary SAR exploration supports the predicted binding mode and further suggests sorafenib to be a novel lead compound for 5HTR ligand discovery. Although it has been well-known that sorafenib produces anticancer effects through targeting multiple kinases, carefully designed experimental studies are desirable to fully understand whether its “off-target” 5-HTR binding activities contribute to its therapeutic efficacy or otherwise undesirable side effects

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