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

TL;DR

This paper explores how biochemical signaling cycles in cells behave under small molecule numbers, revealing stochastic effects and diverse distribution patterns that challenge traditional deterministic models.

Contribution

It provides analytical and numerical insights into the stochastic dynamics of covalent modification cycles, highlighting their role as noise generators in cellular processes.

Findings

Identification of distinct probability distribution classes, including power laws.

Demonstration of stochastic effects dominating in small molecule regimes.

Revealing the potential of CMCs as tunable noise sources.

Abstract

Biochemical reaction networks in living cells usually involve reversible covalent modification of signaling molecules, such as protein phosphorylation. Under conditions of small molecule numbers, as is frequently the case in living cells, mass action theory fails to describe the dynamics of such systems. Instead, the biochemical reactions must be treated as stochastic processes that intrinsically generate concentration fluctuations of the chemicals. We investigate the stochastic reaction kinetics of covalent modification cycles (CMCs) by analytical modeling and numerically exact Monte-Carlo simulation of the temporally fluctuating concentration. Depending on the parameter regime, we find for the probability density of the concentration qualitatively distinct classes of distribution functions, including power law distributions with a fractional and tunable exponent. These findings challenge the traditional view of biochemical control networks as deterministic computational systems and suggest that CMCs in cells can function as versatile and tunable noise generators.