马尔可夫模型的乐趣——通道选通和运输循环变得容易

G. Zifarelli, P. Zuccolini, S. Bertelli, M. Pusch
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引用次数: 3

摘要

离子通道和转运体的行为通常使用离散状态连续时间马尔可夫模型来建模。这些模型有助于解释实验数据,并可以通过测试特定的预测来指导实验设计。在这里,我们描述了一个计算工具,它允许我们创建选择复杂性的马尔可夫模型,并在宏观尺度上计算预测,以及在单分子尺度上。该程序计算稳态特性(电流,状态概率和周期频率),确定性宏观和随机时间过程,门控电流,驻留时间直方图,以及通道和转运体的功率谱。此外,视觉模拟模式允许我们跟踪单个通道或传输体随时间的随机行为。在对马尔可夫模型概念的基本介绍之后,讨论了现实生活中的例子,包括简单的K+通道模型,电压门控钠通道,3态配体门控通道和致电单输子。通过这种方式,本文具有模块化的体系结构,从基本主题到更高级的主题。这说明了markoveitor程序如何能够帮助学生在基本水平上探索马尔可夫模型,但也适合研究科学家测试和开发蛋白质功能机制的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Joy of Markov Models—Channel Gating and Transport Cycling Made Easy
The behavior of ion channels and transporters is often modeled using discrete state continuous-time Markov models. Such models are helpful for the interpretation of experimental data and can guide the design of experiments by testing specific predictions. Here, we describe a computational tool that allows us to create Markov models of chosen complexity and to calculate the predictions on a macroscopic scale, as well on a single-molecule scale. The program calculates steady-state properties (current, state probabilities, and cycle frequencies), deterministic macroscopic and stochastic time courses, gating currents, dwell-time histograms, and power spectra of channels and transporters. In addition, a visual simulation mode allows us to follow the time-dependent stochastic behavior of a single channel or transporter. After a basic introduction into the concept of Markov models, real-life examples are discussed, including a model of a simple K+ channel, a voltage-gated sodium channel, a 3-state ligand-gated channel, and an electrogenic uniporter. In this manner, the article has a modular architecture, progressing from basic to more advanced topics. This illustrates how the MarkovEditor program can serve students to explore Markov models at a basic level but is also suited for research scientists to test and develop models on the mechanisms of protein function.
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