| Literature DB >> 22694093 |
Xingyu Lin1, Xi-Ping Huang, Gang Chen, Ryan Whaley, Shiming Peng, Yanli Wang, Guoliang Zhang, Simon X Wang, Shaohui Wang, Bryan L Roth, Niu Huang.
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(2A) 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(2A) 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, K(i) = 1959, 56, and 417 nM against 5-HT(2A), 5-HT(2B), and 5-HT(2C), 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.Entities:
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Year: 2012 PMID: 22694093 PMCID: PMC3402552 DOI: 10.1021/jm300338m
Source DB: PubMed Journal: J Med Chem ISSN: 0022-2623 Impact factor: 7.446