arrow
返回

Modelling photosystem I as a complex interacting network

delete2020-11-11
delete5
delete
OA
AI
D
Daniele Montepietra
M
Michele Bellingeri *
A
Aaron M. Ross
F
Francesco Scotognella
D
Davide Cassi
DOI:10.1098/rsif.2020.0813delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
In this paper, we model the excitation energy transfer (EET) of photosystem I (PSI) of the common pea plant Pisum sativum as a complex interacting network. The magnitude of the link energy transfer between nodes/chromophores is computed by Forster resonant energy transfer (FRET) using the pairwise physical distances between chromophores from the PDB 5L8R (Protein Data Bank). We measure the global PSI network EET efficiency adopting well-known network theory indicators: the network efficiency (Eff) and the largest connected component (LCC). We also account the number of connected nodes/chromophores to P700 (CN), a new ad hoc measure we introduce here to indicate how many nodes in the network can actually transfer energy to the P700 reaction centre. We find that when progressively removing the weak links of lower EET, the Eff decreases, while the EET paths integrity (LCC and CN) is still preserved. This finding would show that the PSI is a resilient system owning a large window of functioning feasibility and it is completely impaired only when removing most of the network links. From the study of different types of chromophore, we propose different primary functions within the PSI system: chlorophyll a (CLA) molecules are the central nodes in the EET process, while other chromophore types have different primary functions. Furthermore, we perform nodes removal simulations to understand how the nodes/chromophores malfunctioning may affect PSI functioning. We discover that the removal of the CLA triggers the fastest decrease in the Eff, confirming that CAL is the main contributors to the high EET efficiency. Our outcomes open new perspectives of research, such comparing the PSI energy transfer efficiency of different natural and agricultural plant species and investigating the light-harvesting mechanisms of artificial photosynthesis both in plant agriculture and in the field of solar energy applications.
Keyword:
complex network
photosystem I
photosynthetic network
biological network
network robustness
network attack
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Journal of the Royal Society Interface 封面图
Journal of the Royal Society Interface
IF:
3.5
论文数:
4.8K
被引数:
1.7W

机构

U
universita di modena e reggio emilia
学者数:
1.6W
论文数: 1.2W
被引数: 12
U
University of Parma
学者数:
1.7W
论文数: 1.3W
被引数: 1.3W
I
istituto nanoscienze (nano-cnr)
学者数:
1.1K
论文数: 733
被引数: 0
学者 查看更多机构
引用论文

引用论文

Rapid responses of permafrost and vegetation to experimentally increased snow cover in sub-arctic Sweden
err2013-08-05
err128
errOAAI
errJohansson, Margareta; Callaghan, Terry V.; Bosio, Julia; Akerman, H. Jonas; Jackowicz-Korczynski, Marcin; Christensen, Torben R.
err分享
err收藏
err分享
err收藏
The architecture of complex weighted networks
err2004-03-08
err3.2K
errOAAI
errBarrat, A; Barthélemy, M; Pastor-Satorras, R; Vespignani, A
err分享
err收藏
学者 查看更多内容