Computational Identification of Novel Kir6 Channel Inhibitors

Publication date

2019-05-24

Authors

Chen, Xingyu
Garon, Arthur
Wieder, Marcus
Houtman, Marien J C
Zangerl-Plessl, Eva-Maria
Langer, Thierry
van der Heyden, MAGORCID 0000-0002-4225-7942ISNI 0000000391802748
Stary-Weinzinger, Anna

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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 in silico predictions were confirmed using inside/out patch-clamp analysis. Importantly, Cantú mutation C166S in Kir6.2 (equivalent to C176S in Kir6.1) and S1020P in SUR2A, retained high affinity toward the novel inhibitors. Summarizing, the inhibitors identified in this study might provide a starting point toward developing novel therapies for Cantú disease.

Keywords

Cantú syndrome, KATP channel, channelopathy, dynamic pharmacophone, electrophysiology, molecular dynamics simulation, Journal Article

Citation

Chen, X, Garon, A, Wieder, M, Houtman, M J C, Zangerl-Plessl, E-M, Langer, T, van der Heyden, M A G & Stary-Weinzinger, A 2019, 'Computational Identification of Novel Kir6 Channel Inhibitors', Frontiers in Pharmacology, vol. 10, no. MAY, 549. https://doi.org/10.3389/fphar.2019.00549