A statistical mechanics investigation of unfolded protein response across organisms
Luchetti, Nicole and Smith, Keith M. and Matarrese, Margherita A. G. and Loppini, Alessandro and Filippi, Simonetta and Chiodo, Letizia (2024) A statistical mechanics investigation of unfolded protein response across organisms. Scientific Reports, 14 (1). 27658. ISSN 2045-2322 (https://doi.org/10.1038/s41598-024-79086-8)
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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 protein-protein interaction 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.
ORCID iDs
Luchetti, Nicole, Smith, Keith M. ORCID: https://orcid.org/0000-0002-4615-9020, Matarrese, Margherita A. G., Loppini, Alessandro, Filippi, Simonetta and Chiodo, Letizia;-
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Item type: Article ID code: 91127 Dates: DateEvent12 November 2024Published6 November 2024AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 12 Nov 2024 10:34 Last modified: 20 Nov 2024 01:29 URI: https://strathprints.strath.ac.uk/id/eprint/91127