Allegra Michele, Giorda Paolo
Institute for Scientific Interchange Foundation (ISI), Via Alassio 11/c, I-10126 Torino, Italy.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 May;85(5 Pt 1):051917. doi: 10.1103/PhysRevE.85.051917. Epub 2012 May 25.
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 us 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 versus 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' behavior 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.
我们探讨了拓扑结构在光合复合体网络中能量传输过程中的作用。我们从紫细菌中存在的光捕获网络中获取灵感,并在更一般和抽象的网络上模拟非相干耗散能量传输过程,考虑了规则结构(凯莱树和超支化分形)以及随机生成的结构。我们聚焦于紫细菌的两种主要光捕获复合体,即LH1和LH2,并使用网络理论中心性度量来选择不同的LH1排列方式。我们表明,不同的选择会导致传输效率产生显著差异,并且对于规则网络,中心性度量使我们能够识别出能确保传输效率优于复合体随机排列所获得效率的排列方式。最优排列方式强烈依赖于动力学的耗散性质以及所考虑网络的拓扑性质,并且根据后者,通过使用全局与局部中心性度量来实现。对于随机生成的网络,复合体的随机排列已经能提供高效传输,这表明该过程对于结构设计中有限的控制量以及随机组装结构构建中固有的无序具有较强的耐受性。最后,我们将所考虑的网络与真实生物网络进行比较,发现由于其更高的连通性,真实生物网络总体上具有更好的性能,但具有最优排列方式的前者在特定的传输参数范围内可以模拟真实网络的行为。这些结果表明,网络理论概念的使用对于高效人工能量传输网络的表征和设计可能至关重要。