A statistical mechanics investigation of Unfolded Protein Response across organisms

Nicole Luchetti, Keith M. Smith, Margherita A. G. Matarrese, Alessandro Loppini, Simonetta Filippi, Letizia Chiodo
{"title":"A statistical mechanics investigation of Unfolded Protein Response across organisms","authors":"Nicole Luchetti, Keith M. Smith, Margherita A. G. Matarrese, Alessandro Loppini, Simonetta Filippi, Letizia Chiodo","doi":"arxiv-2407.12464","DOIUrl":null,"url":null,"abstract":"Living systems rely on coordinated molecular interactions, especially those\nrelated to gene expression and protein activity. The Unfolded Protein Response\nis a crucial mechanism in eukaryotic cells, activated when unfolded proteins\nexceed a critical threshold. It maintains cell homeostasis by enhancing protein\nfolding, initiating quality control, and activating degradation pathways when\ndamage is irreversible. This response functions as a dynamic signaling network,\nwith proteins as nodes and their interactions as edges. We analyze these\nprotein-protein networks across different organisms to understand their\nintricate intra-cellular interactions and behaviors. In this work, analyzing\ntwelve organisms, we assess how fundamental measures in network theory can\nindividuate seed-proteins and specific pathways across organisms. We employ\nnetwork robustness to evaluate and compare the strength of the investigated PPI\nnetworks, and the structural controllability of complex networks to find and\ncompare the sets of driver nodes necessary to control the overall networks. We\nfind that network measures are related to phylogenetics, and advanced network\nmethods can identify main pathways of significance in the complete Unfolded\nProtein Response mechanism.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Biological Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.12464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Living systems rely on coordinated molecular interactions, especially those related to gene expression and protein activity. The Unfolded Protein Response is a crucial mechanism in eukaryotic cells, activated when unfolded proteins exceed a critical threshold. It maintains cell homeostasis by enhancing protein folding, initiating quality control, and activating degradation pathways when damage is irreversible. This response functions as a dynamic signaling network, with proteins as nodes and their interactions as edges. We analyze these protein-protein networks across different organisms to understand their intricate intra-cellular interactions and behaviors. In this work, analyzing twelve organisms, we assess how fundamental measures in network theory can individuate seed-proteins and specific pathways across organisms. We employ network robustness to evaluate and compare the strength of the investigated PPI networks, and the structural controllability of complex networks to find and compare the sets of driver nodes necessary to control the overall networks. We find that network measures are related to phylogenetics, and advanced network methods can identify main pathways of significance in the complete Unfolded Protein Response mechanism.
跨生物体的折叠蛋白反应统计力学研究
生命系统依赖于协调的分子相互作用,尤其是与基因表达和蛋白质活性有关的相互作用。折叠蛋白反应是真核细胞中的一种重要机制,当折叠蛋白超过临界阈值时就会被激活。它通过加强蛋白质折叠、启动质量控制以及在损伤不可逆转时激活降解途径来维持细胞的平衡。这种反应就像一个动态信号网络,蛋白质是节点,它们之间的相互作用是边。我们分析了不同生物体的这些蛋白质-蛋白质网络,以了解它们错综复杂的细胞内相互作用和行为。在这项工作中,我们分析了十二种生物,评估了网络理论中的基本测量方法如何在不同生物间划分种子蛋白和特定通路。我们利用网络鲁棒性来评估和比较所研究的 PPInetworks 的强度,并利用复杂网络的结构可控性来寻找和比较控制整个网络所需的驱动节点集。我们发现,网络度量与系统发生学有关,先进的网络方法可以识别完整的蛋白折叠反应机制中重要的主要通路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信