Computational Modeling of Ion Channel Clustering in Cardiac Cellular Membrane

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2024-12

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The Ohio State University

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Abstract

Ion channels are found to group into clusters in the plasma membrane of cardiac myocytes. However, the mechanisms behind clustering especially under disease conditions are not known. Studies indicate a strong link between altered ion channel expression and vascular diseases. Clustering behavior was analyzed in a computational model simulating ion channel insertion, removal, and diffusion. Thousands of simulations were ran varying parameters involved in clustering. Simulations were analyzed using averages, variances, histograms analyzing cluster distributions, and through visible clustering behaviors generated from the model. Parameters involved in clustering and the effects on clustering behaviors were compared. The study found that simple channel interactions are the most important for determining cluster properties in a cardiac membrane using a stochastic, self-assembly process. The model has implications for ion channel modeling under disease conditions. Additionally, the model could provide insight into how clustering behavior changes and provide novel techniques for therapies.

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computational modeling, ion channels, cardiac physiology, clustering

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