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Molecular and Genomic Physiology |
1 Center for Single Molecule Biophysics, Department of Physiology and Biophysics, State University of New York at Buffalo, 3435 Main Street, Buffalo, NY 14214, USA
Upon activation by agonist, the type A
-aminobutyric acid receptor (GABAR) gates, allowing chloride ions to permeate membranes and produce fast inhibition of neurons. There is no consensus kinetic model for the GABAR gating mechanism. We expressed human
1ß1
2S GABARs in HEK 293 cells and recorded single channel currents in the cell-attached configuration using various GABA concentrations (505000 µM). Closed and open events occurred individually and in clusters that had at least three different modes that were distinguishable by open probability (PO): High (PO= 0.73), Mid (PO= 0.50), and Low (PO= 0.21). We used a critical time to isolate shorter bursts of openings and to thus eliminate long-lived, desensitized events. Bursts from all three modes contained three closed and three open components. We employed maximum likelihood fitting, autocorrelation analysis and macroscopic current simulation to distinguish kinetic schemes. The core gating scheme for most models contained two closed states that preceded an open state (C1
C2
O1). The two best-fitting models had a third closed state connected to C1 and a second open state (O2) connected to C2. The third open state, whose occupancy varied greatly between modes, could be connected either to O2 or C2. We estimated rate constants for two identical, independent GABA binding steps by globally fitting data across GABA concentrations ranging from 50 to 1000 µM. For the most highly ranked model the binding rate constants were: k+= 3 µM1 s1 and k= 272 s1 (KD= 91 µM).
(Received 23 September 2005;
accepted after revision 23 January 2006;
first published online 2 February 2006)
Corresponding author A. Auerbach: Center for Single Molecule Biophysics, Department of Physiology and Biophysics, State University of New York at Buffalo, 3435 Main Street, Buffalo, NY 14214, USA. Email: auerbach{at}buffalo.edu
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