Bifunctional enzyme action as a source of robustness in biochemical reaction networks: a novel hypergraph approach

Fuente: arXiv
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Autores principales: Joshi, Badal, Nguyen, Tung D.
Formato: Preprint
Publicado: 2025
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author Joshi, Badal
Nguyen, Tung D.
author_facet Joshi, Badal
Nguyen, Tung D.
contents Substrate modification networks are ubiquitous in living, biochemical systems. A higher-level hypergraph "skeleton" captures key information about which substrates are transformed in the presence of modification-specific enzymes. Many different detailed models can be associated to the same skeleton, however uncertainty related to model fitting increases with the level of detail. We show that essential dynamical properties such as existence of positive steady states and concentration robustness can be extracted directly from the skeleton independent of the detailed model. The novel formalism of directed hypergraphs is used to prove that bifunctional enzyme action plays a key role in generating robustness. Moreover, we use another novel concept of "current" on a directed hypergraph to establish a link between potentially remote network components. Current is an essential notion required for existence of positive steady states, and furthermore, current-matching combined with bifunctionality generates concentration robustness.
format Preprint
id arxiv_https___arxiv_org_abs_2504_21011
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bifunctional enzyme action as a source of robustness in biochemical reaction networks: a novel hypergraph approach
Joshi, Badal
Nguyen, Tung D.
Molecular Networks
92C40, 37N25, 05C65
Substrate modification networks are ubiquitous in living, biochemical systems. A higher-level hypergraph "skeleton" captures key information about which substrates are transformed in the presence of modification-specific enzymes. Many different detailed models can be associated to the same skeleton, however uncertainty related to model fitting increases with the level of detail. We show that essential dynamical properties such as existence of positive steady states and concentration robustness can be extracted directly from the skeleton independent of the detailed model. The novel formalism of directed hypergraphs is used to prove that bifunctional enzyme action plays a key role in generating robustness. Moreover, we use another novel concept of "current" on a directed hypergraph to establish a link between potentially remote network components. Current is an essential notion required for existence of positive steady states, and furthermore, current-matching combined with bifunctionality generates concentration robustness.
title Bifunctional enzyme action as a source of robustness in biochemical reaction networks: a novel hypergraph approach
topic Molecular Networks
92C40, 37N25, 05C65
url https://arxiv.org/abs/2504.21011