A statistical thermodynamical interpretation of metabolism
type: Item
instance of: scholarly article
title: A statistical thermodynamical interpretation of metabolism
zbMATH Open document ID: 1229.82134
author: Friedrich Srienc
author: Pornkamol Unrean
published in: Entropy
publication date: 2012-01-09T00:00:00Z
review text: Summary: The metabolic network of a cell can be decomposed into discrete elementary modes that contribute, each with a certain probability, to the overall flux through the metabolism. These modes are cell function supporting, fundamental pathways that represent permissible `quantum' states of the metabolism. For the case that cellular regulatory mechanisms for pathway fluxes evolved in an unbiased way, we demonstrate theoretically that the usage probabilities of individual elementary modes are distributed according to Boltzmann's distribution law such that the rate of entropy production is maximized. Such distribution can be observed experimentally in highly evolved metabolic networks. Therefore, cell function has a natural tendency to operate at a maximum rate of entropy generation using preferentially efficient pathways with small reaction entropies. Ultimately, evolution of metabolic networks appears to be driven by forces that can be quantified by the distance of the current metabolic state from the state of maximum entropy generation that represents the unbiased, most probable selection of fundamental pathway choices.
Mathematics Subject Classification ID: 82C35
Mathematics Subject Classification ID: 92C30
zbMATH DE Number: 5995896
zbMATH Keywords: elementary flux modes
zbMATH Keywords: maximum entropy principle
zbMATH Keywords: metabolic networks
zbMATH Keywords: evolution
describes a project that uses: Metatool
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/e12081921
OpenAlex ID: W1991772013
cites work: Reaction routes in biochemical reaction systems: algebraic properties, validated calculation procedure and example from nucleotide metabolism
cites work: Information Theory and Statistical Mechanics
DOI: 10.3390/E12081921
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description: scientific article; zbMATH DE number 5995896