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Using independent open-to-closed transitions to simplify aggregated Markov models of ion channel gating kinetics

机译:使用独立的开到关转换来简化离子通道门控动力学的聚合马尔可夫模型

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Deducing plausible reaction schemes from single-channel current traces is time-consuming and difficult. The goal is to find the simplest scheme that fits the data, but there are many ways to connect even a small number of states ( >2 million schemes with four open and four closed states). Many schemes make identical predictions. An exhaustive search over model space does not address the many equivalent schemes that will result. We have found a canonical form that can express all reaction schemes for binary channels. This form has the minimal number of rate constants for any rank (number of independent open-closed transitions), unlike other canonical forms such as the well established "uncoupled" scheme. Because all of the inter-conductance transitions in the new form are independent, we refer to it as the manifest interconductance rank (MIR) form. In the case of four open and four closed states, there are four MIR form schemes, corresponding to ranks 1-4. For many models proposed in the literature for specific ion channels, the equivalent MIR form has dramatically fewer links than the uncoupled form. By using the MIR form we prove that all rank 1 topologies with a given number of open and closed states make identical predictions in steady state, thus narrowing the search space for simple models. Moreover, we prove that fitting to canonical form preserves detailed balance. We also propose an efficient hierarchical algorithm for searching for the simplest possible model consistent with a given data set.
机译:从单通道电流迹线推断出合理的反应方案既费时又困难。目标是找到适合数据的最简单方案,但是有很多方法可以连接很少的状态(> 200万个方案,其中有四个开放状态和四个封闭状态)。许多方案做出相同的预测。在模型空间上进行详尽的搜索并不能解决将导致的许多等效方案。我们发现一种规范形式可以表示二进制通道的所有反应方案。与其他规范形式(如已建立的“解耦”方案)不同,此形式在任何等级(独立的开闭转换数)下具有最少数量的速率常数。由于新形式中的所有电导间过渡都是独立的,因此我们将其称为清单电导间等级(MIR)形式。在四个打开状态和四个关闭状态的情况下,存在四种MIR格式方案,对应于等级1-4。对于文献中针对特定离子通道提出的许多模型,等效的MIR形式的链接大大少于非耦合形式。通过使用MIR形式,我们证明了具有给定数量的打开和关闭状态的所有等级1拓扑在稳态下都可以进行相同的预测,从而缩小了简单模型的搜索空间。此外,我们证明了对规范形式的拟合可以保持详细的平衡。我们还提出了一种有效的分层算法,用于搜索与给定数据集一致的最简单的可能模型。

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