Bai Fang, Pi Xiaoping, Li Ping, Zhou Pingzheng, Yang Huaiyu, Wang Xicheng, Li Min, Gao Zhaobing, Jiang Hualiang
Department of Engineering Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, and Faculty of Chemical, Environmental, and Biological Science and Technology, Dalian University of Technology, Dalian, China.
Drug Discovery and Design Center, State Key Laboratory of Drug Research, CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
Front Pharmacol. 2018 Mar 9;9:150. doi: 10.3389/fphar.2018.00150. eCollection 2018.
Ion channels are important therapeutic targets, and their pharmacology is becoming increasingly important. However, knowledge of the mechanism of interaction of the activators and ion channels is still limited due to the complexity of the mechanisms. A statistical thermodynamic model has been developed in this study to characterize the cooperative binding of activators to ion channels. By fitting experimental concentration-response data, the model gives eight parameters for revealing the mechanism of an activator potentiating an ion channel, i.e., the binding affinity ( ), the binding cooperative coefficients for two to four activator molecules interacting with one channel (γ, μ, and ν), and the channel conductance coefficients for four activator binding configurations of the channel (, and ). Values for the model parameters and the mechanism underlying the interaction of ztz240, a proven KCNQ2 activator, with the wild-type channel have been obtained and revealed by fitting the concentration-response data of this activator potentiating the outward current amplitudes of KCNQ2. With these parameters, our model predicted an unexpected bi-sigmoid concentration-response curve of ztz240 activation of the WT-F137A mutant heteromeric channel that was in good agreement with the experimental data determined in parallel in this study, lending credence to the assumptions on which the model is based and to the model itself. Our model can provide a better fit to the measured data than the Hill equation and estimates the binding affinity, as well as the cooperative coefficients for the binding of activators and conductance coefficients for binding states, which validates its use in studying ligand-channel interaction mechanisms.
离子通道是重要的治疗靶点，其药理学正变得越来越重要。然而，由于作用机制的复杂性，关于激活剂与离子通道相互作用机制的了解仍然有限。本研究开发了一种统计热力学模型来表征激活剂与离子通道的协同结合。通过拟合实验浓度-反应数据，该模型给出了八个参数以揭示激活剂增强离子通道的机制，即结合亲和力（ ）、两个至四个激活剂分子与一个通道相互作用的结合协同系数（γ、μ和ν）以及通道四种激活剂结合构型的通道电导系数（ 、 和 ）。通过拟合该激活剂增强KCNQ2外向电流幅度的浓度-反应数据，获得并揭示了已证实的KCNQ2激活剂ztz240与野生型通道相互作用的模型参数值及潜在机制。利用这些参数，我们的模型预测了ztz240激活WT-F137A突变异源通道的意外双S形浓度-反应曲线，该曲线与本研究中并行测定的实验数据高度吻合，这为该模型所基于的假设及模型本身提供了可信度。与希尔方程相比，我们的模型能更好地拟合测量数据，并估计结合亲和力以及激活剂结合的协同系数和结合状态的电导系数，这验证了其在研究配体-通道相互作用机制中的应用。
