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Modes and models of GABAA receptor gating

机译:GABAA受体门控的模式和模型

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摘要

Upon activation by agonist, the type A γ-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 α1β1γ2S GABARs in HEK 293 cells and recorded single channel currents in the cell-attached configuration using various GABA concentrations (50–5000 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 μm−1 s−1 and k = 272 s−1 (KD = 91 μm).
机译:通过激动剂激活后,A型γ-氨基丁酸受体(GABAR)成为“门”,使氯离子渗透到膜上并快速抑制神经元。对于GABAR门控机制没有共识动力学模型。我们在HEK 293细胞中表达了人α1β1γ2SGABAR,并使用各种GABA浓度(50–5000μm)在细胞附着的配置中记录了单通道电流。封闭事件和开放事件分别发生在具有至少三种可通过开放概率(PO)区分的不同模式的集群中:高(PO = 0.73),中(PO = 0.50)和低(PO = 0.21)。我们用关键时间隔离了较短的开口,从而消除了长期存在的脱敏事件。所有这三种模式的爆发都包含三个封闭和三个开放成分。我们采用最大似然拟合,自相关分析和宏观电流模拟来区分动力学方案。大多数模型的“核心”门控方案都包含两个处于打开状态(C1⇌C2⇌O1)之前的闭合状态。这两个最合适的模型具有连接到C1的第三关闭状态和连接到C2的第二打开状态(O2)。占用率在模式之间变化很大的第三个打开状态可以连接到O2或C2。我们通过全局拟合跨50至1000μm的GABA浓度的数据,估算了两个相同的独立GABA结合步骤的速率常数。对于排名最高的模型,绑定速率常数为:k + = 3μm −1 s −1 和k = 272 s -1 (K D = 91μm)。

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