Molecular dynamics (MD) simulation of biological processes has always been a challenging task due to the long timescales of the processes involved and the large amount of output data to handle. Markov state models (MSMs) have been introduced as a powerful tool in this area of research, as they provide a mechanistically comprehensible synthesis of the large amount of MD data and, at the same time, can be used to rapidly estimate experimental properties of biological processes. Herein, we propose a method for building MSMs of ion channel permeation from MD trajectories, which directly evaluates the current flowing through the channel from the model’s transition matrix (T), which is crucial for comparing simulations and experimental data. This is achieved by including in the model a flux matrix that summarizes information on the charge moving across the channel between each pair of states of the MSM and can be used in conjunction with T to predict the ion current. A procedure to drastically reduce the number of states in the MSM while preserving the estimated ion current is also proposed. Applying the method to the KcsA channel returned an MSM with five states with significant equilibrium occupancy, capable of accurately reproducing the single-channel ion current from microsecond MD trajectories.

中文翻译：

---

从分子动力学模拟中构建离子通道渗透的预测马尔可夫模型


生物过程的分子动力学 （MD） 模拟一直是一项具有挑战性的任务，因为所涉及的过程时间跨度很长，并且需要处理大量的输出数据。马尔可夫态模型 （MSM） 已被作为该研究领域的强大工具引入，因为它们提供了大量 MD 数据的机制上可理解的综合，同时可用于快速估计生物过程的实验特性。在此，我们提出了一种从 MD 轨迹构建离子通道渗透 MSM 的方法，该方法从模型的过渡矩阵 （T） 直接评估流过通道的电流，这对于比较模拟和实验数据至关重要。这是通过在模型中包含磁通量矩阵来实现的，该矩阵汇总了在 MSM 的每对状态之间通过通道移动的电荷的信息，并且可以与 T 结合使用来预测离子电流。还提出了一种在保留估计离子电流的同时大幅减少 MSM 中状态数的程序。将该方法应用于 KcsA 通道，返回具有 5 个状态且具有显著平衡占据率的 MSM，能够准确再现微秒 MD 轨迹的单通道离子电流。