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arXiv 1111.1678physics.bio-phphysics.chem-phq-bio.QM
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光合复合物相互作用网络的拓扑结构和能量传递

Topology and energy transport in networks of interacting photosynthetic complexes

Michele Allegra, Paolo Giorda

摘要:

我们解决的作用,拓扑结构中发生在网络的光合复合物的能量传输过程。我们从紫色细菌中存在的光捕获网络中汲取灵感,并在更一般和抽象的网络上模拟不连贯的耗散能量传输过程,同时考虑规则结构(凯莱树和超支化分形)和随机生成的结构。我们专注于紫色细菌的两个主要捕光复合物,即,LH1和LH2,我们使用网络理论的中心性措施,以选择不同的LH1安排。我们发现,不同的选择导致显着差异的运输效率,并定期网络中心性措施允许确定安排,确保运输效率比随机配置的复杂。最佳安排强烈依赖于耗散性质的动力学和考虑的网络的拓扑性质,并取决于后者,他们是通过使用全球与本地的中心性措施。对于随机生成的网络,复合物的随机排列已经提供了有效的传输,这表明该过程相对于结构设计中的有限控制量和随机组装结构的构建中固有的无序是强大的。最后,我们将所考虑的网络与真实的生物网络进行比较,发现后者由于其更高的连通性而具有更好的性能,但前者具有最佳安排,可以模仿真实网络在特定范围内的传输参数的行为。这些结果表明,使用网络理论的概念可以是至关重要的表征和设计的有效的人工能源传输网络。

英文摘要:

We address the role of topology in the energy transport process that occurs in networks of photosynthetic complexes. We take inspiration from light harvesting networks present in purple bacteria and simulate an incoherent dissipative energy transport process on more general and abstract networks, considering both regular structures (Cayley trees and hyperbranched fractals) and randomly-generated ones. We focus on the the two primary light harvesting complexes of purple bacteria, i.e., the LH1 and LH2, and we use network-theoretical centrality measures in order to select different LH1 arrangements. We show that different choices cause significant differences in the transport efficiencies, and that for regular networks centrality measures allow to identify arrangements that ensure transport efficiencies which are better than those obtained with a random disposition of the complexes. The optimal arrangements strongly depend on the dissipative nature of the dynamics and on the topological properties of the networks considered, and depending on the latter they are achieved by using global vs. local centrality measures. For randomly-generated networks a random arrangement of the complexes already provides efficient transport, and this suggests the process is strong with respect to limited amount of control in the structure design and to the disorder inherent in the construction of randomly-assembled structures. Finally, we compare the networks considered with the real biological networks and find that the latter have in general better performances, due to their higher connectivity, but the former with optimal arrangements can mimic the real networks' behaviour for a specific range of transport parameters. These results show that the use of network-theoretical concepts can be crucial for the characterization and design of efficient artificial energy transport networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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