McManus O B, Weiss D S, Spivak C E, Blatz A L, Magleby K L
Department of Physiology and Biophysics, University of Miami School of Medicine, Florida 33101.
Biophys J. 1988 Nov;54(5):859-70. doi: 10.1016/S0006-3495(88)83022-4.
The gating kinetics of single ion channels have been well described by models which assume that channels exist in a number of discrete kinetic states, with the rate constants for transitions among the states remaining constant in time. In contrast to such discrete Markov models, it has recently been considered whether gating might arise from transitions among a continuum of states, with the effective rate constants for leaving the collections of states given by a fractal scaling equation (Liebovitch, L.S., J. Fischbarg, J.P. Koniarek, I. Todorova, and M. Wang. 1987. Biochim. Biophys. Acta. 896:173-180; Liebovitch, L.S., and J.M. Sullivan. 1987. Biophys. J. 52:979-988). The present study compares discrete Markov with fractal continuum models to determine which best describes the gating kinetics of four different ion channels: GABA-activated Cl channels, ACh-activated end-plate channels, large conductance Ca-activated K (BK) channels, and fast Cl channels. Discrete Markov models always gave excellent descriptions of the distributions of open and shut times for all four channels. Fractal continuum models typically gave very poor descriptions of the shut times for all four channels, and also of the open times from end-plate and BK channels. The descriptions of the open times from GABA-activated and fast Cl channels by the fractal and Markov models were usually not significantly different. If the same model accounts for gating motions in proteins for both the open and shut states, then the Markov model ranked above the fractal model in 35 of 36 data sets of combined open and shut intervals, with the Markov model being tens to thousands of orders of magnitude more probable. We suggest that the examined fractal continuum model is unlikely to serve as a general mechanism for the gating of these four ion channels.
单离子通道的门控动力学已被一些模型很好地描述,这些模型假定通道存在于多个离散的动力学状态中,各状态间转换的速率常数在时间上保持恒定。与这种离散马尔可夫模型不同,最近有人考虑门控是否可能源于连续状态间的转换,离开这些状态集合的有效速率常数由分形标度方程给出(Liebovitch, L.S., J. Fischbarg, J.P. Koniarek, I. Todorova, and M. Wang. 1987. Biochim. Biophys. Acta. 896:173 - 180; Liebovitch, L.S., and J.M. Sullivan. 1987. Biophys. J. 52:979 - 988)。本研究比较了离散马尔可夫模型和分形连续体模型,以确定哪种模型能最好地描述四种不同离子通道的门控动力学:γ-氨基丁酸(GABA)激活的氯离子通道、乙酰胆碱(ACh)激活的终板通道、大电导钙激活钾(BK)通道和快速氯离子通道。离散马尔可夫模型总是能很好地描述所有四种通道的开放时间和关闭时间分布。分形连续体模型通常对所有四种通道的关闭时间以及终板通道和BK通道的开放时间描述得非常差。分形模型和马尔可夫模型对GABA激活的氯离子通道和快速氯离子通道开放时间的描述通常没有显著差异。如果同一模型能解释蛋白质在开放和关闭状态下的门控运动,那么在36个开放和关闭间隔组合的数据集中,有35个数据集的马尔可夫模型排名高于分形模型,马尔可夫模型的可能性比分形模型高数十到数千个数量级。我们认为,所研究的分形连续体模型不太可能作为这四种离子通道门控的一般机制。