Abstract

Several organelles in eukaryotic cells, including mitochondria and the endoplasmic reticulum, form interconnected tubule networks extending throughout the cell. These tubular networks host many biochemical pathways that rely on proteins diffusively searching through the network to encounter binding partners or localized target regions. Predicting the behavior of such pathways requires a quantitative understanding of how confinement to a reticulated structure modulates reaction kinetics. In this work, we develop both exact analytical methods to compute mean first passage times and efficient kinetic Monte Carlo algorithms to simulate trajectories of particles diffusing in a tubular network. Our approach leverages exact propagator functions for the distribution of transition times between network nodes and allows large simulation time steps determined by the network structure. The methodology is applied to both synthetic planar networks and organelle network structures, demonstrating key general features such as the heterogeneity of search times in different network regions and the functional advantage of broadly distributing target sites throughout the network. The proposed algorithms pave the way for future exploration of the interrelationship between tubular network structure and biomolecular reaction kinetics.

Graphic Abstract

中文翻译：

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管状网络上的扩散搜索和轨迹：一种传播器方法

摘要

真核细胞中的几个细胞器，包括线粒体和内质网，形成贯穿整个细胞的相互连接的小管网络。这些管状网络承载着许多生化途径，这些途径依赖于通过网络扩散搜索的蛋白质，以遇到结合伙伴或局部目标区域。预测此类途径的行为需要对网状结构的限制如何调节反应动力学进行定量理解。在这项工作中，我们开发了精确的分析方法来计算平均首次通过时间和有效的动力学蒙特卡罗算法来模拟粒子在管状网络中扩散的轨迹。我们的方法利用精确的传播器函数来分配网络节点之间的过渡时间，并允许由网络结构确定的大型仿真时间步长。该方法应用于合成平面网络和细胞器网络结构，展示了关键的一般特征，例如不同网络区域中搜索时间的异质性以及在整个网络中广泛分布目标站点的功能优势。所提出的算法为未来探索管状网络结构与生物分子反应动力学之间的相互关系铺平了道路。展示了关键的一般特征，例如不同网络区域中搜索时间的异质性以及在整个网络中广泛分布目标站点的功能优势。所提出的算法为未来探索管状网络结构与生物分子反应动力学之间的相互关系铺平了道路。展示了关键的一般特征，例如不同网络区域中搜索时间的异质性以及在整个网络中广泛分布目标站点的功能优势。所提出的算法为未来探索管状网络结构与生物分子反应动力学之间的相互关系铺平了道路。

图形摘要