Modeling networks of coupled enzymatic reactions using the total quasi-steady state approximation

被引:127
作者
Ciliberto, Andrea [1 ]
Capuani, Fabrizio
Tyson, John J.
机构
[1] FIRC Inst Mol Oncol, Milan, Italy
[2] Virginia Polytech Inst & State Univ, Dept Biol Sci, Blacksburg, VA 24061 USA
关键词
D O I
10.1371/journal.pcbi.0030045
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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 (S-0). However, in protein interaction networks, the enzymes and substrates are all proteins in comparable concentrations, and neglecting C with respect to S-0 is not valid. Borghans, DeBoer, and Segel developed an alternative description of enzyme kinetics that is valid when C is comparable to S-0. 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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收藏
页码:463 / 472
页数:10
相关论文
共 19 条
[1]   Effects of sequestration on signal transduction cascades [J].
Blüthgen, N ;
Bruggeman, FJ ;
Legewie, S ;
Herzel, H ;
Westerhoff, HV ;
Kholodenko, BN .
FEBS JOURNAL, 2006, 273 (05) :895-906
[2]   How robust are switches in intracellular signaling cascades? [J].
Blüthgen, N ;
Herzel, H .
JOURNAL OF THEORETICAL BIOLOGY, 2003, 225 (03) :293-300
[3]   Extending the quasi-steady state approximation by changing variables [J].
Borghans, JAM ;
DeBoer, RJ ;
Segel, LA .
BULLETIN OF MATHEMATICAL BIOLOGY, 1996, 58 (01) :43-63
[4]   PROTEIN MOLECULES AS COMPUTATIONAL ELEMENTS IN LIVING CELLS [J].
BRAY, D .
NATURE, 1995, 376 (6538) :307-312
[5]   Understanding bistability in complex enzyme-driven reaction networks [J].
Craciun, Gheorghe ;
Tang, Yangzhong ;
Feinberg, Martin .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2006, 103 (23) :8697-8702
[6]   Testing a mathematical model of the yeast cell cycle [J].
Cross, FR ;
Archambault, V ;
Miller, M ;
Klovstad, M .
MOLECULAR BIOLOGY OF THE CELL, 2002, 13 (01) :52-70
[7]  
Ermentrout B, 2002, Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students
[8]   AN AMPLIFIED SENSITIVITY ARISING FROM COVALENT MODIFICATION IN BIOLOGICAL-SYSTEMS [J].
GOLDBETER, A ;
KOSHLAND, DE .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1981, 78 (11) :6840-6844
[9]   From molecular to modular cell biology [J].
Hartwell, LH ;
Hopfield, JJ ;
Leibler, S ;
Murray, AW .
NATURE, 1999, 402 (6761) :C47-C52
[10]   Modeling M-phase control in Xenopus oocyte extracts:: the surveillance mechanism for unreplicated DNA [J].
Marlovits, G ;
Tyson, CJ ;
Novak, B ;
Tyson, JJ .
BIOPHYSICAL CHEMISTRY, 1998, 72 (1-2) :169-184