Modeling networks of coupled enzymatic reactions using the total quasi-steady state approximation
dc.contributor.author | Ciliberto, Andrea | en |
dc.contributor.author | Capuani, Fabrizio | en |
dc.contributor.author | Tyson, John J. | en |
dc.contributor.department | Biological Sciences | en |
dc.date.accessioned | 2016-12-09T21:34:32Z | en |
dc.date.available | 2016-12-09T21:34:32Z | en |
dc.date.issued | 2007-03-01 | en |
dc.description.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. | en |
dc.description.version | Published version | en |
dc.format.extent | 463 - 472 (10) page(s) | en |
dc.identifier.doi | https://doi.org/10.1371/journal.pcbi.0030045 | en |
dc.identifier.issn | 1553-734X | en |
dc.identifier.issue | 3 | en |
dc.identifier.uri | http://hdl.handle.net/10919/73631 | en |
dc.identifier.volume | 3 | en |
dc.language | English | en |
dc.publisher | PLOS | en |
dc.relation.uri | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000246191000012&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1 | en |
dc.rights | Creative Commons Attribution 4.0 International | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | Biochemical Research Methods | en |
dc.subject | Mathematical & Computational Biology | en |
dc.subject | Biochemistry & Molecular Biology | en |
dc.subject | XENOPUS-OOCYTE EXTRACTS | en |
dc.subject | M-PHASE CONTROL | en |
dc.subject | CELL-CYCLE | en |
dc.subject | KINETICS | en |
dc.subject | BISTABILITY | en |
dc.subject | HYSTERESIS | en |
dc.subject | CASCADES | en |
dc.title | Modeling networks of coupled enzymatic reactions using the total quasi-steady state approximation | en |
dc.title.serial | PLOS Computational Biology | en |
dc.type | Article - Refereed | en |
pubs.organisational-group | /Virginia Tech | en |
pubs.organisational-group | /Virginia Tech/All T&R Faculty | en |
pubs.organisational-group | /Virginia Tech/Faculty of Health Sciences | en |
pubs.organisational-group | /Virginia Tech/Science | en |
pubs.organisational-group | /Virginia Tech/Science/Biological Sciences | en |
pubs.organisational-group | /Virginia Tech/Science/COS T&R Faculty | en |
pubs.organisational-group | /Virginia Tech/University Distinguished Professors | en |
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