Department of Physics, University of California, San Diego, San Diego, California, 92093, USA.
Department of Chemistry and Biochemistry, Calvin College, Grand Rapids, Michigan, 49546, USA.
Sci Rep. 2020 Mar 18;10(1):4984. doi: 10.1038/s41598-020-61598-8.
We investigate diffusive search on planar networks, motivated by tubular organelle networks in cell biology that contain molecules searching for reaction partners and binding sites. Exact calculation of the diffusive mean first-passage time on a spatial network is used to characterize the typical search time as a function of network connectivity. We find that global structural properties - the total edge length and number of loops - are sufficient to largely determine network exploration times for a variety of both synthetic planar networks and organelle morphologies extracted from living cells. For synthetic networks on a lattice, we predict the search time dependence on these global structural parameters by connecting with percolation theory, providing a bridge from irregular real-world networks to a simpler physical model. The dependence of search time on global network structural properties suggests that network architecture can be designed for efficient search without controlling the precise arrangement of connections. Specifically, increasing the number of loops substantially decreases search times, pointing to a potential physical mechanism for regulating reaction rates within organelle network structures.
我们研究了平面网络上的扩散搜索，这一研究受到细胞生物学中管状细胞器网络的启发，此类网络中包含了寻找反应伙伴和结合位点的分子。我们利用空间网络上扩散平均首次通过时间的精确计算来描述网络连接性对典型搜索时间的影响。我们发现，对于各种合成平面网络和从活细胞中提取的细胞器形态，全局结构属性（总边长度和环数）足以在很大程度上确定网络探索时间。对于晶格上的合成网络，我们通过与渗流理论连接来预测搜索时间对这些全局结构参数的依赖性，从而为不规则的真实世界网络与更简单的物理模型之间建立了桥梁。搜索时间对全局网络结构属性的依赖性表明，无需控制连接的精确排列，就可以设计出用于有效搜索的网络架构。具体而言，增加环数会大大减少搜索时间，这为调节细胞器网络结构内的反应速率提供了一种潜在的物理机制。
