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Journal Articles The Journal of Chemical Physics Year : 2019

Convergent evolution in silico of biochemical log-response

Abstract

Numerous biological systems are known to harbour a form of logarithmic behaviour, from Weber's law to bacterial chemotaxis. Working on a logarithmic scale allows the organism to respond appropriately to large variations in a given input at a modest cost in terms of metabolism. Here we use a genetic algorithm to evolve biochemical networks displaying a direct logarithmic response. Interestingly, a quasi-perfect log-response implemented by the same simple core network evolves in a convergent way across our different replications. The best network is able to fit a logarithm over 4 order of magnitude with an accuracy of the order of 1%. At the heart of this network, we show that a logarithmic approximation may be implemented with one single non-linear interaction, that can be interpreted either as a phosphorylation or as a ligand induced multimerization and provide an analytical explanation of the effect. Biological log-response might thus be easier to implement than usually assumed.
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Dates and versions

hal-02389284 , version 1 (02-12-2019)

Identifiers

  • HAL Id : hal-02389284 , version 1

Cite

Mathieu Hemery, Paul François. Convergent evolution in silico of biochemical log-response. The Journal of Chemical Physics, 2019. ⟨hal-02389284⟩
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