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Schoeberl2002 - EGF MAPK


ABSTRACT: Schoeberl2002 - EGF MAPK Computational model that offers an integrated quantitative, dynamic, and topological representation of intracellular signal networks, based on known components of epidermal growth factor (EGF) receptor signal pathways. The initial model was constructed by Ken Lau from the MATLAB source code. This model is described in the article: Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Schoeberl B, Eichler-Jonsson C, Gilles ED, Müller G Nat. Biotechnol. 2002 Apr; 20(4): 370-375 Abstract: We present a computational model that offers an integrated quantitative, dynamic, and topological representation of intracellular signal networks, based on known components of epidermal growth factor (EGF) receptor signal pathways. The model provides insight into signal-response relationships between the binding of EGF to its receptor at the cell surface and the activation of downstream proteins in the signaling cascade. It shows that EGF-induced responses are remarkably stable over a 100-fold range of ligand concentration and that the critical parameter in determining signal efficacy is the initial velocity of receptor activation. The predictions of the model agree well with experimental analysis of the effect of EGF on two downstream responses, phosphorylation of ERK-1/2 and expression of the target gene, c-fos. This model does not exactly reproduce the results given in the original publication. It has, though, the same reaction graph and gives very similar time courses for the conditions depicted in the article. Several corrections were applied to the parameters described in the paper's supplementary materials. Some parameter names were replaced by the corresponding identical ones: k(r)26 by k(r)18, k(r)27 by k(r)19, k(r)30 by k(r)20, k(r)38 by k(r)24, k(r)39 by k(r)37, k(r)46 by k(r)44, k51 by k49, k(r)54 by k(r)52 and k62 by k62. In particular the parameter values described in the column "remark" of supplementary table 1 override the values explicitely written in the numerical columns: name in suppl. value used in model value used remarks kr16 0.055 0.275 k30 7.9e6 2.1e6 as k20 kr30 0.3 0.4 as kr24 k38 3e7 1e7 as k20 kr38 0.055 0.55 as kr24 k52 1.1e5 5.34e7 k5 was used for v116, v119, v122 and v125 in addition of v107, v110 and v113 as listed in the legend of supplementary figure 2. k5 is calculated using th eformula from the matlab file not given in the supplements. All rate constants were rescaled to minutes (k[min] = 60*k[sec]) and all second order rate constants additionally to molecules/cell with a cell volume of 1 picolitre (k[molecs/cell] = k[M]/(Vc*Na), with Vc=1e-12 l and Na = 6e23). The association constant of internalized EGF was rescaled to molecules/endosome using an endosomal volume of 4.3 al (= 4.3*10 -18 litre). The extracellular EGF concentration was converted to molecules per picolitre with a MW of 6045 Da. [ng/ml] [numb/pl] 50 4962 0.5 49.6 0.125 12.4 With the initial conditions given in the paper, the results could not be reproduced at all. Therefore the initial conditions used in the MATLAB file were adopted for SHC (1.01 * 10 5 instead of 1.01 * 10 6 ) and Ras_GDP. (7.2 * 10 4 instead of 1.14 * 10 7 ) This model is hosted on BioModels Database and identified by: BIOMD0000000019. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Nicolas Le Novère  

PROVIDER: BIOMD0000000019 | BioModels | 2005-08-15

REPOSITORIES: BioModels

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Publications

Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors.

Schoeberl Birgit B   Eichler-Jonsson Claudia C   Gilles Ernst Dieter ED   Müller Gertraud G  

Nature biotechnology 20020401 4


We present a computational model that offers an integrated quantitative, dynamic, and topological representation of intracellular signal networks, based on known components of epidermal growth factor (EGF) receptor signal pathways. The model provides insight into signal-response relationships between the binding of EGF to its receptor at the cell surface and the activation of downstream proteins in the signaling cascade. It shows that EGF-induced responses are remarkably stable over a 100-fold r  ...[more]

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