Noise-induced breakdown of the Michaelis-Menten equation in steady-state conditions.
The Michaelis-Menten (MM) equation is the basic equation of enzyme kinetics; it is also a basic building block of many models of biological systems. We build a stochastic and microscopic model of enzyme kinetics inside a small subcellular compartment. Using both theory and simulations, we show that intrinsic noise induces a breakdown of the MM equation even if steady-state metabolic conditions are enforced. In particular, we show that (i) given a reaction velocity, deterministic rate equations can severely underestimate steady-state intracellular substrate concentrations and (ii) different reaction schemes which on a macroscopic level are indistinguishable because they are described by the same MM equation obey distinctly different equations in subcellular compartments.
Grima
R
R
School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
D000465:Algorithms; D003198:Computer Simulation; D004798:Enzymes / Q000378:metabolism*; D007700:Kinetics; D008956:Models, Chemical; D013269:Stochastic Processes; D013347:Subcellular Fractions / Q000201:enzymology
D004798:Enzymes