We study a simplified, solvable model of a fully connected metabolic network with constrained quenched disorder to mimic the conservation laws imposed by stoichiometry on chemical reactions. Within a spin-glass type of approach, we show that in the presence of a conserved metabolic pool the flux state corresponding to maximal growth is stationary independently of the pool size. In addition, and at odds with the case of unconstrained networks, the volume of optimal flux configurations remains finite, indicating that the frustration imposed by stoichiometric constraints, while reducing growth capabilities, confers robustness and flexibility to the system. These results have a clear biological interpretation and provide a basic, fully analytical explanation to features recently observed in real metabolic networks. Copyright © 2009 EPLA.

On the role of conserved moieties in shaping the robustness and production capabilities of reaction networks / De Martino, A.; Martelli, C.; Massucci, F. A.. - In: EUROPHYSICS LETTERS. - ISSN 0295-5075. - 85:3(2009), p. 38007. [10.1209/0295-5075/85/38007]

On the role of conserved moieties in shaping the robustness and production capabilities of reaction networks

De Martino A.;
2009

Abstract

We study a simplified, solvable model of a fully connected metabolic network with constrained quenched disorder to mimic the conservation laws imposed by stoichiometry on chemical reactions. Within a spin-glass type of approach, we show that in the presence of a conserved metabolic pool the flux state corresponding to maximal growth is stationary independently of the pool size. In addition, and at odds with the case of unconstrained networks, the volume of optimal flux configurations remains finite, indicating that the frustration imposed by stoichiometric constraints, while reducing growth capabilities, confers robustness and flexibility to the system. These results have a clear biological interpretation and provide a basic, fully analytical explanation to features recently observed in real metabolic networks. Copyright © 2009 EPLA.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2976714