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-HT2A 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-HT2A 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, Ki = 1959, 56 and 417 nM against 5-HT2A, 5-HT2B and 5-HT2C, 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.