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Modeling Networks of Coupled Enzymatic Reactions Using the Total Quasi-Steady State Approximation

Overview of attention for article published in PLoS Computational Biology, March 2007
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Title
Modeling Networks of Coupled Enzymatic Reactions Using the Total Quasi-Steady State Approximation
Published in
PLoS Computational Biology, March 2007
DOI 10.1371/journal.pcbi.0030045
Pubmed ID
Authors

Andrea Ciliberto, Fabrizio Capuani, John J Tyson

Abstract

In metabolic networks, metabolites are usually present in great excess over the enzymes that catalyze their interconversion, and describing the rates of these reactions by using the Michaelis-Menten rate law is perfectly valid. This rate law assumes that the concentration of enzyme-substrate complex (C) is much less than the free substrate concentration (S0). However, in protein interaction networks, the enzymes and substrates are all proteins in comparable concentrations, and neglecting C with respect to S0 is not valid. Borghans, DeBoer, and Segel developed an alternative description of enzyme kinetics that is valid when C is comparable to S0. We extend this description, which Borghans et al. call the total quasi-steady state approximation, to networks of coupled enzymatic reactions. First, we analyze an isolated Goldbeter-Koshland switch when enzymes and substrates are present in comparable concentrations. Then, on the basis of a real example of the molecular network governing cell cycle progression, we couple two and three Goldbeter-Koshland switches together to study the effects of feedback in networks of protein kinases and phosphatases. Our analysis shows that the total quasi-steady state approximation provides an excellent kinetic formalism for protein interaction networks, because (1) it unveils the modular structure of the enzymatic reactions, (2) it suggests a simple algorithm to formulate correct kinetic equations, and (3) contrary to classical Michaelis-Menten kinetics, it succeeds in faithfully reproducing the dynamics of the network both qualitatively and quantitatively.

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Mendeley readers

The data shown below were compiled from readership statistics for 149 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 6%
United Kingdom 4 3%
Germany 3 2%
Turkey 1 <1%
Netherlands 1 <1%
Switzerland 1 <1%
France 1 <1%
Italy 1 <1%
Australia 1 <1%
Other 5 3%
Unknown 122 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 32%
Researcher 38 26%
Professor > Associate Professor 15 10%
Student > Bachelor 9 6%
Professor 8 5%
Other 22 15%
Unknown 10 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 38%
Biochemistry, Genetics and Molecular Biology 16 11%
Physics and Astronomy 14 9%
Mathematics 11 7%
Chemistry 10 7%
Other 27 18%
Unknown 14 9%