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Biochemical reaction networks in living cells usually involve reversiblecovalent modification of signaling molecules, such as protein phosphorylation.Under conditions of small molecule numbers, as is frequently the case in livingcells, mass action theory fails to describe the dynamics of such systems.Instead, the biochemical reactions must be treated as stochastic processes thatintrinsically generate concentration fluctuations of the chemicals. Weinvestigate the stochastic reaction kinetics of covalent modification cycles(CMCs) by analytical modeling and numerically exact Monte-Carlo simulation ofthe temporally fluctuating concentration. Depending on the parameter regime, wefind for the probability density of the concentration qualitatively distinctclasses of distribution functions, including power law distributions with afractional and tunable exponent. These findings challenge the traditional viewof biochemical control networks as deterministic computational systems andsuggest that CMCs in cells can function as versatile and tunable noisegenerators.

Noise and critical phenomena in biochemical signaling cycles at small molecule numbers