Maximum likelihood estimation of ion channel kinetics from macroscopic currents
Maximum likelihood estimation of ion channel kinetics from macroscopic currents
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DOI：
10.1529/biophysj.104.053256
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发表时间：
2005-04-01
影响因子：
3.4
通讯作者：
Sachs, F
中科院分区：
文献类型：
--
作者：
Milescu, LS;Akk, G;Sachs, F
我们描述了一种最大似然方法，用于根据任意尺寸和拓扑的动力学模型的宏观离子通道数据直接估计速率常数。可以估计制备过程中的通道数量以及单位电流的平均值和标准偏差，并且可以对速率常数施加先验约束。该方法允许任意刺激方案，包括具有有限上升时间的刺激、配体序列或电压步骤以及全局刺激。适合不同的实验条件。初始状态占有率可以根据拟合动力学进行优化。利用任意刺激方案并使用电流的均值和方差可以减少或消除模型识别能力的问题（Kienker，1989）。该算法比最近使用完整自协方差矩阵的方法（Celentano 和 Hawkes，2004）更快，部分原因是似然梯度的分析计算。我们用模拟数据和来自乙酰胆碱受体的真实宏观电流测试了该方法，这些电流是响应卡巴胆碱的短暂脉冲而引起的。考虑到适当的刺激方案，我们的方法选择了合理的模型大小和拓扑。
We describe a maximum likelihood method for direct estimation of rate constants from macroscopic ion channel data for kinetic models of arbitrary size and topology. The number of channels in the preparation, and the mean and standard deviation of the unitary current can be estimated, and a priori constraints can be imposed on rate constants. The method allows for arbitrary stimulation protocols, including stimuli with finite rise time, trains of ligand or voltage steps, and global. fitting across different experimental conditions. The initial state occupancies can be optimized from the fit kinetics. Utilizing arbitrary stimulation protocols and using the mean and the variance of the current reduce or eliminate problems of model identify ability (Kienker, 1989). The algorithm is faster than a recent method that uses the full autocovariance matrix (Celentano and Hawkes, 2004), in part due to the analytical calculation of the likelihood gradients. We tested the method with simulated data and with real macroscopic currents from acetylcholine receptors, elicited in response to brief pulses of carbachol. Given appropriate stimulation protocols, our method chose a reasonable model size and topology.