Literature DB >> 25028009

Irreversible thermodynamics of open chemical networks. I. Emergent cycles and broken conservation laws.

Matteo Polettini1, Massimiliano Esposito1.   

Abstract

In this paper and Paper II, we outline a general framework for the thermodynamic description of open chemical reaction networks, with special regard to metabolic networks regulating cellular physiology and biochemical functions. We first introduce closed networks "in a box", whose thermodynamics is subjected to strict physical constraints: the mass-action law, elementarity of processes, and detailed balance. We further digress on the role of solvents and on the seemingly unacknowledged property of network independence of free energy landscapes. We then open the system by assuming that the concentrations of certain substrate species (the chemostats) are fixed, whether because promptly regulated by the environment via contact with reservoirs, or because nearly constant in a time window. As a result, the system is driven out of equilibrium. A rich algebraic and topological structure ensues in the network of internal species: Emergent irreversible cycles are associated with nonvanishing affinities, whose symmetries are dictated by the breakage of conservation laws. These central results are resumed in the relation a + b = s(Y) between the number of fundamental affinities a, that of broken conservation laws b and the number of chemostats s(Y). We decompose the steady state entropy production rate in terms of fundamental fluxes and affinities in the spirit of Schnakenberg's theory of network thermodynamics, paving the way for the forthcoming treatment of the linear regime, of efficiency and tight coupling, of free energy transduction, and of thermodynamic constraints for network reconstruction.

Mesh:

Year:  2014        PMID: 25028009     DOI: 10.1063/1.4886396

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  10 in total

1.  Bond graph modelling of the cardiac action potential: implications for drift and non-unique steady states.

Authors:  Michael Pan; Peter J Gawthrop; Kenneth Tran; Joseph Cursons; Edmund J Crampin
Journal:  Proc Math Phys Eng Sci       Date:  2018-06-27       Impact factor: 2.704

2.  Intrinsic and Extrinsic Thermodynamics for Stochastic Population Processes with Multi-Level Large-Deviation Structure.

Authors:  Eric Smith
Journal:  Entropy (Basel)       Date:  2020-10-07       Impact factor: 2.524

3.  Spontaneous fine-tuning to environment in many-species chemical reaction networks.

Authors:  Jordan M Horowitz; Jeremy L England
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-03       Impact factor: 11.205

4.  Energy-based analysis of biomolecular pathways.

Authors:  Peter J Gawthrop; Edmund J Crampin
Journal:  Proc Math Phys Eng Sci       Date:  2017-06-21       Impact factor: 2.704

5.  What makes a reaction network "chemical"?

Authors:  Stefan Müller; Christoph Flamm; Peter F Stadler
Journal:  J Cheminform       Date:  2022-09-19       Impact factor: 8.489

6.  A semantics, energy-based approach to automate biomodel composition.

Authors:  Niloofar Shahidi; Michael Pan; Kenneth Tran; Edmund J Crampin; David P Nickerson
Journal:  PLoS One       Date:  2022-06-03       Impact factor: 3.752

7.  Modular bond-graph modelling and analysis of biomolecular systems.

Authors:  Peter J Gawthrop; Edmund J Crampin
Journal:  IET Syst Biol       Date:  2016-10       Impact factor: 1.615

8.  Network Thermodynamical Modeling of Bioelectrical Systems: A Bond Graph Approach.

Authors:  Peter J Gawthrop; Michael Pan
Journal:  Bioelectricity       Date:  2021-03-16

9.  Survival of Self-Replicating Molecules under Transient Compartmentalization with Natural Selection.

Authors:  Gabin Laurent; Luca Peliti; David Lacoste
Journal:  Life (Basel)       Date:  2019-10-03

Review 10.  Nonequilibrium Thermodynamics in Biochemical Systems and Its Application.

Authors:  Dongliang Zhang; Qi Ouyang
Journal:  Entropy (Basel)       Date:  2021-02-25       Impact factor: 2.524

  10 in total

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