Display options
Share it on

Front Pharmacol. 2019 May 24;10:549. doi: 10.3389/fphar.2019.00549. eCollection 2019.

Computational Identification of Novel Kir6 Channel Inhibitors.

Frontiers in pharmacology

Xingyu Chen, Arthur Garon, Marcus Wieder, Marien J C Houtman, Eva-Maria Zangerl-Plessl, Thierry Langer, Marcel A G van der Heyden, Anna Stary-Weinzinger

Affiliations

  1. Department of Pharmacology and Toxicology, University of Vienna, Vienna, Austria.
  2. Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria.
  3. Department of Medical Physiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands.

PMID: 31178728 PMCID: PMC6543810 DOI: 10.3389/fphar.2019.00549

Abstract

KATP channels consist of four Kir6.x pore-forming subunits and four regulatory sulfonylurea receptor (SUR) subunits. These channels couple the metabolic state of the cell to membrane excitability and play a key role in physiological processes such as insulin secretion in the pancreas, protection of cardiac muscle during ischemia and hypoxic vasodilation of arterial smooth muscle cells. Abnormal channel function resulting from inherited gain or loss-of-function mutations in either the Kir6.x and/or SUR subunits are associated with severe diseases such as neonatal diabetes, congenital hyperinsulinism, or Cantú syndrome (CS). CS is an ultra-rare genetic autosomal dominant disorder, caused by dominant gain-of-function mutations in SUR2A or Kir6.1 subunits. No specific pharmacotherapeutic treatment options are currently available for CS. Kir6 specific inhibitors could be beneficial for the development of novel drug therapies for CS, particular for mutations, which lack high affinity for sulfonylurea inhibitor glibenclamide. By applying a combination of computational methods including atomistic MD simulations, free energy calculations and pharmacophore modeling, we identified several novel Kir6.1 inhibitors, which might be possible candidates for drug repurposing. The

Keywords: Cantú syndrome; KATP channel; channelopathy; dynamic pharmacophore; electrophysiology; molecular dynamics simulation

References

  1. Nat Cell Biol. 1999 Jul;1(3):183-8 - PubMed
  2. J Biol Chem. 1999 Dec 24;274(52):37479-82 - PubMed
  3. Drug Metab Dispos. 2000 Jul;28(7):772-80 - PubMed
  4. J Biol Chem. 2000 Sep 15;275(37):28757-63 - PubMed
  5. Annu Rev Biophys Biomol Struct. 2000;29:291-325 - PubMed
  6. J Biol Chem. 2001 Sep 28;276(39):36673-80 - PubMed
  7. Proc Natl Acad Sci U S A. 2002 Mar 5;99(5):2726-31 - PubMed
  8. J Biol Chem. 2002 Jun 28;277(26):23260-70 - PubMed
  9. EMBO J. 2002 Aug 1;21(15):3936-48 - PubMed
  10. Diabetologia. 2003 Jul;46(7):875-91 - PubMed
  11. J Gen Physiol. 2003 Aug;122(2):225-37 - PubMed
  12. J Comput Chem. 2004 Jul 15;25(9):1157-74 - PubMed
  13. J Chem Inf Model. 2005 Jan-Feb;45(1):160-9 - PubMed
  14. J Clin Invest. 2005 Aug;115(8):2047-58 - PubMed
  15. Eur J Pharmacol. 2006 Jan 4;529(1-3):47-54 - PubMed
  16. J Mol Graph Model. 2006 Oct;25(2):247-60 - PubMed
  17. N Engl J Med. 2006 Aug 3;355(5):467-77 - PubMed
  18. Proteins. 2006 Nov 15;65(3):712-25 - PubMed
  19. J Chem Phys. 2007 Jan 7;126(1):014101 - PubMed
  20. Circulation. 2007 Jan 30;115(4):518-33 - PubMed
  21. Am J Physiol. 1991 Dec;261(6 Pt 2):H1675-86 - PubMed
  22. J Appl Physiol (1985). 2007 Nov;103(5):1888-93 - PubMed
  23. Science. 1994 Aug 26;265(5176):1219-21 - PubMed
  24. Diabetologia. 2008 Apr;51(4):675-85 - PubMed
  25. Arq Bras Endocrinol Metabol. 2008 Nov;52(8):1350-5 - PubMed
  26. Cell Metab. 2009 Dec;10(6):442-53 - PubMed
  27. Mol Syst Biol. 2010;6:343 - PubMed
  28. Br J Pharmacol. 2010 Apr;159(7):1532-41 - PubMed
  29. Br J Pharmacol. 2011 Jun;163(3):510-20 - PubMed
  30. Br J Pharmacol. 2011 Jun;163(3):499-509 - PubMed
  31. Am J Med Genet A. 2011 Mar;155A(3):508-18 - PubMed
  32. Br J Pharmacol. 2011 Jun;163(3):496-8 - PubMed
  33. Eur J Pharmacol. 2011 Oct 1;668(1-2):72-7 - PubMed
  34. Br J Pharmacol. 2011 Dec;164(8):2064-72 - PubMed
  35. Cell. 2011 Sep 30;147(1):199-208 - PubMed
  36. Br J Pharmacol. 2012 Sep;167(1):26-36 - PubMed
  37. Am J Hum Genet. 2012 Jun 8;90(6):1094-101 - PubMed
  38. Nat Genet. 2012 May 18;44(7):793-6 - PubMed
  39. Curr Mol Med. 2013 Sep;13(8):1284-98 - PubMed
  40. Circ Res. 2013 Mar 29;112(7):1059-72 - PubMed
  41. Cardiovasc Res. 2013 Jul 1;99(1):203-14 - PubMed
  42. Eur J Med Genet. 2013 Dec;56(12):678-82 - PubMed
  43. Nucleic Acids Res. 2014 Jan;42(Database issue):D1091-7 - PubMed
  44. Hum Mutat. 2014 Jul;35(7):809-13 - PubMed
  45. J Biol Chem. 2015 Jun 19;290(25):15450-61 - PubMed
  46. J Neurochem. 2015 Sep;134(6):1026-39 - PubMed
  47. Nucleic Acids Res. 2016 Jan 4;44(D1):D1075-9 - PubMed
  48. Diabetologia. 2016 Jun;59(6):1162-6 - PubMed
  49. Future Med Chem. 2016 May;8(7):789-802 - PubMed
  50. J Gen Physiol. 2016 Sep;148(3):227-37 - PubMed
  51. J Gen Physiol. 2017 Jan;149(1):75-84 - PubMed
  52. J Chem Inf Model. 2017 Feb 27;57(2):365-385 - PubMed
  53. Cell. 2017 Jan 12;168(1-2):101-110.e10 - PubMed
  54. Elife. 2017 Jan 16;6: - PubMed
  55. Naunyn Schmiedebergs Arch Pharmacol. 2017 Jul;390(7):701-710 - PubMed
  56. J Gen Physiol. 2017 May 1;149(5):561-576 - PubMed
  57. J Physiol. 2017 Sep 1;595(17):5895-5912 - PubMed
  58. J Biol Chem. 2017 Oct 20;292(42):17387-17398 - PubMed
  59. Elife. 2017 Oct 24;6: - PubMed
  60. Elife. 2017 Dec 29;6: - PubMed
  61. Protein Cell. 2018 Jun;9(6):553-567 - PubMed
  62. J Cell Mol Med. 2019 May 22;:null - PubMed
  63. Hum Genet. 1982;60(1):36-41 - PubMed
  64. J Physiol. 1995 Feb 15;483 ( Pt 1):29-39 - PubMed
  65. J Mol Biol. 1997 Apr 4;267(3):727-48 - PubMed
  66. Biophys J. 1997 May;72(5):2002-13 - PubMed
  67. Nature. 1998 Feb 19;391(6669):803-6 - PubMed
  68. Electrophoresis. 1997 Dec;18(15):2714-23 - PubMed
  69. J Gen Physiol. 1998 Sep;112(3):333-49 - PubMed
  70. Science. 1998 Nov 6;282(5391):1138-41 - PubMed
  71. J Biol Chem. 1999 Feb 12;274(7):3931-3 - PubMed
  72. Proc Natl Acad Sci U S A. 1999 Feb 16;96(4):1268-72 - PubMed

Publication Types

Grant support