Weckel-Dahman Hannah, Carlsen Ryan, Daum Alexander, He Maxwell, Southam Tyler G, Swanson Jessica M J
Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States.
Department of Computer Science, Northeastern University, Boston, Massachusetts 02115, United States.
J Chem Theory Comput. 2025 Apr 8;21(7):3700-3711. doi: 10.1021/acs.jctc.4c01569. Epub 2025 Mar 18.
The transport of ions through channels involves multiple rare-event transitions through a web of interconnected intermediates. Extracting open channel mechanisms generally requires quantifying the relative flux through these intermediates in response to a range of electrochemical gradients. Although this is ideally suited to network-based representations like Markov state models (MSMs), the relative contributions from different pathways and the importance of network resolution remain open areas of research. Herein, we use a complementary approach called multiscale responsive kinetic modeling (MsRKM) to explore how the screening of ionic interactions and the competition between multiple mechanistic pathways contribute to channel mechanisms and current profiles of ion channels. We find that explicitly optimizing screened ionic interactions in the MsRKM framework vastly reduces the solution search space, enabling more efficient identification of physically robust solutions. Using a model of the Shaker Kv channel, we demonstrate that even when systems are well described by a single dominant flux pathway, the remaining contributing pathways and off-pathway flux play multiple essential roles, including shifting current profiles and mechanisms in response to different electrochemical gradients. We additionally discover that the current continues to change above the experimentally predicted saturation point. Model systems explain how the degree of dielectric screening influences channel occupancy, the number of contributing pathways, and why current increases or decreases above its experimental saturation point. Our findings emphasize the importance of retaining a full network description to identify and understand ion channel mechanisms.
离子通过通道的运输涉及通过相互连接的中间体网络的多个罕见事件转变。提取开放通道机制通常需要量化这些中间体在一系列电化学梯度作用下的相对通量。尽管这非常适合基于网络的表示，如马尔可夫状态模型（MSM），但不同途径的相对贡献以及网络分辨率的重要性仍是有待研究的领域。在此，我们使用一种称为多尺度响应动力学建模（MsRKM）的互补方法，来探索离子相互作用的筛选以及多种机制途径之间的竞争如何影响离子通道的通道机制和电流分布。我们发现，在MsRKM框架中明确优化筛选的离子相互作用可大幅减少解搜索空间，从而更有效地识别物理上稳健的解。使用Shaker Kv通道模型，我们证明即使系统由单一主导通量途径很好地描述，其余的贡献途径和非通量途径也起着多种重要作用，包括响应不同电化学梯度改变电流分布和机制。我们还发现，在实验预测的饱和点以上电流仍会继续变化。模型系统解释了介电筛选程度如何影响通道占有率、贡献途径的数量，以及电流在其实验饱和点以上增加或减少的原因。我们的研究结果强调了保留完整网络描述以识别和理解离子通道机制的重要性。
