Design and Structure-Based Study of New Potential FKBP12 Inhibitors

Sun, Fei; Li, Pengyun; Ding, Yi; Wang, Liwei; Bartlam, Mark; Shu, Cuilin; Shen, Beifen; Jiang, Hualiang; Song, Li; Rao, Zihe

doi:10.1016/s0006-3495(03)74737-7

Cited by 38 publications

(51 citation statements)

References 39 publications

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“…This synthetic compound interacts with FKBP12 but lacks immunosuppressive activity. 20,21 GPI-1046 increases the luciferase activity in Hep3B cells transfected For personal use only. on May 12, 2018.…”

Section: Drugs Targeting Fkbp12 Activate Hepcidin Through the Bmp-smamentioning

confidence: 99%

The immunophilin FKBP12 inhibits hepcidin expression by binding the BMP type I receptor ALK2 in hepatocytes

Colucci

Pagani

Pettinato

et al. 2017

Blood

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Key Points• FKBP12 suppresses hepcidin by interaction with the BMP receptor ALK2.• Disruption of FKBP12-ALK2 interaction increases hepcidin and renders the receptor responsive to the inflammatory ligand Activin A.The expression of the key regulator of iron homeostasis hepcidin is activated by the BMP-SMAD pathway in response to iron and inflammation and among drugs, by rapamycin, which inhibits mTOR in complex with the immunophilin FKBP12. FKBP12 interacts with BMP type I receptors to avoid uncontrolled signaling. By pharmacologic and genetic studies, we identify FKBP12 as a novel hepcidin regulator. Sequestration of FKBP12 by rapamycin or tacrolimus activates hepcidin both in vitro and in murine hepatocytes. Acute tacrolimus treatment transiently increases hepcidin in wild-type mice. FKBP12 preferentially targets the BMP receptor ALK2. ALK2 mutants defective in binding FKBP12 increase hepcidin expression in a ligand-independent manner, through BMP-SMAD signaling. ALK2 free of FKBP12 becomes responsive to the noncanonical inflammatory ligand Activin A. Our results identify a novel hepcidin regulator and a potential therapeutic target to increase defective BMP signaling in

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Section: Drugs Targeting Fkbp12 Activate Hepcidin Through the Bmp-smamentioning

confidence: 99%

The immunophilin FKBP12 inhibits hepcidin expression by binding the BMP type I receptor ALK2 in hepatocytes

Colucci

Pagani

Pettinato

et al. 2017

Blood

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“…binding free energies except for a constant G-offset of 3.2 kcal/mol. In comparison, a recent study on inhibitor design for FKBP concluded that ligand docking calculations alone could not correctly rank five inhibitors (one of which, FK506 was also considered in this study) according to their binding affinity [170].…”

Section: Absolute Binding Free Energies Of Diverse Pharmaceuticals Tomentioning

confidence: 72%

Towards Accurate Free Energy Calculations in Ligand Protein-Binding Studies

Steinbrecher¹,

Labahn²

2010

CMC

146

133

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Cells contain a multitude of different chemical reaction paths running simultaneously and quite independently next to each other. This amazing feat is enabled by molecular recognition, the ability of biomolecules to form stable and specific complexes with each other and with their substrates. A better understanding of this process, i.e. of the kinetics, structures and thermodynamic properties of biomolecule binding, would be invaluable in the study of biological systems. In addition, as the mode of action of many pharmaceuticals is based upon their inhibition or activation of biomolecule targets, predictive models of small molecule receptor binding are very helpful tools in rational drug design. Since the goal here is normally to design a new compound with a high inhibition strength, one of the most important thermodynamic properties is the binding free energy DeltaG(0). The prediction of binding constants has always been one of the major goals in the field of computational chemistry, because the ability to reliably assess a hypothetical compound's binding properties without having to synthesize it first would save a tremendous amount of work. The different approaches to this question range from fast and simple empirical descriptor methods to elaborate simulation protocols aimed at putting the computation of free energies onto a solid foundation of statistical thermodynamics. While the later methods are still not suited for the screenings of thousands of compounds that are routinely performed in computational drug design studies, they are increasingly put to use for the detailed study of protein ligand interactions. This review will focus on molecular mechanics force field based free energy calculations and their application to the study of protein ligand interactions. After a brief overview of other popular methods for the calculation of free energies, we will describe recent advances in methodology and a variety of exemplary studies of molecular dynamics simulation based free energy calculations.

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“…Compound 308 exhibits remarkable activity in many in vitro and in vivo neuroregeneration models and was chosen as the prime candidate for further evaluation. The co-crystal structure of compound 308 and FKBP12 was obtained and solved the key interaction between them (Sun et al, 2003). The complex shows that the 1,4-thiazine and sulfanilamide groups bind identically as the pipecolinyl ring and dicarbonyl groups do in FK506.…”

Section: Nonimmunosuppressant Neuroimmunophilin Ligandsmentioning

confidence: 99%