Binding of ArgTX-636 in the NMDA receptor ion channel

Mette H. Poulsen, Jacob Andersen, Rune Christensen, Kasper B. Hansen, Stephen F. Traynelis, Kristian Strømgaard, Anders Skov Kristensen

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

The N-methyl-d-aspartate receptors (NMDARs) constitute an important class of ligand-gated cation channels that are involved in the majority of excitatory neurotransmission in the human brain. Compounds that bind in the NMDAR ion channel and act as blockers are use- and voltage-dependent inhibitors of NMDAR activity and have therapeutic potential for treatment of a variety of brain diseases or as pharmacological tools for studies of the neurobiological role of NMDARs. We have performed a kinetic analysis of the blocking mechanism of the prototypical polyamine toxin NMDAR ion channel blocker argiotoxin-636 (ArgTX-636) at recombinant GluN1/2A receptors to provide detailed information on the mechanism of block. The predicted binding site of ArgTX-636 is in the pore region of the NMDAR ion channel formed by residues in the transmembrane M3 and the M2 pore-loop segments of the GluN1 and GluN2A subunits. To assess the predicted binding mode in further detail, we performed an alanine- and glycine-scanning mutational analysis of this pore-loop segment to systematically probe the role of pore-lining M2 residues in GluN1 and GluN2A in the channel block by ArgTX-636. Comparison of M2 positions in GluN1 and GluN2A where mutation influences ArgTX-636 potency suggests differential contribution of the M2-loops of GluN1 and GluN2A to binding of ArgTX-636. The results of the mutational analysis are highly relevant for the future structure-based development of argiotoxin-derived NMDAR channel blockers.

Original languageEnglish
Pages (from-to)176-189
Number of pages14
JournalJournal of Molecular Biology
Volume427
Issue number1
DOIs
StatePublished - Jan 16 2015

Keywords

  • NMDA receptor
  • channel block
  • electrophysiology
  • glutamate receptor
  • mutational analysis

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