Dynamic Structural Modeling Revealed That Nilotinib Inhibits Smoothened Signaling. (1st September 2019)

• Record Type: Journal Article
• Authors: Chahal, Kirti Kandhwal; Li, Jie; Kufareva, Irina; Durden, Donald; Reya, Robert Wechsler; Abagyan, Ruben; Chen, Clark C
• Is Part Of: Neurosurgery. Volume 66(2010)Supplement 1
• Publication Date: 2019-09-01
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1093/neuros/nyz310_806
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: INTRODUCTION: Dysregulation of the 7-transmembrane receptors Smoothened (SMO) and other components of the Hedgehog (Hh) signaling pathway causes several cancers, including medulloblastoma (MB) and glioblastoma. However, SMO-specific antagonists produced mixed results in clinical trials, marked by a limited efficacy and a high rate of acquired resistance in tumors. METHODS: Computational modeling of protein docking sites, analytical configuration modeling of crystallographic data, and in Vitro and in Vivo xenograft experiments. RESULTS: Using computational modeling of SMO structure, we discovered that Nilotinib, an FDA-approved receptor tyrosine kinase inhibitor, directly binds to SMO. Furthermore, Nilotinib was more efficacious than the SMO-specific antagonist Vismodegib in inhibiting cell growth and Gli-1 mRNA and protein levels in Hh-dependent MB cells and glioblastoma cells. It also reduced tumor growth in the Hh-dependent MB and glioblastoma mouse xenograft models. These results indicate that in addition to its ability to inhibit several tyrosine kinase-mediated proliferative pathways, Nilotinib is active against the Hh pathway. CONCLUSION: The newly discovered extension of Nilotinib target profile holds promise for the treatment of Hh-dependent cancers. It also calls for comprehensive characterization of pharmacology for other drugs and incorporation of their multitarget profiles into drug-disease matching criteria for personalized medicine.