Schoeberl2002 - EGF MAPK

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Model Identifier
BIOMD0000000019
Short description
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:

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 )

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.

Format
SBML (L2V4)
Related Publication
  • 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
  • Nature biotechnology , 4/ 2002 , Volume 20 , pages: 370-375 , PubMed ID: 11923843
  • Max Planck Institute for Dynamics of Complex Technical Systems, Leipziger Str. 44, D-39120 Magdeburg, Germany.
  • 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.
Contributors
Nicolas Le Novère

Metadata information

is
BioModels Database MODEL6617455076
BioModels Database BIOMD0000000019
isDescribedBy
PubMed 11923843
hasTaxon
Taxonomy Homo sapiens
hasVersion
Gene Ontology Ras protein signal transduction
Gene Ontology MAPK cascade

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000019_url.xml SBML L2V4 representation of Schoeberl2002 - EGF MAPK 149.81 KB Preview | Download

Additional files

BIOMD0000000019_urn.xml Auto-generated SBML file with URNs 148.65 KB Preview | Download
BIOMD0000000019-biopax3.owl Auto-generated BioPAX (Level 3) 298.50 KB Preview | Download
BIOMD0000000019-biopax2.owl Auto-generated BioPAX (Level 2) 166.34 KB Preview | Download
BIOMD0000000019.m Auto-generated Octave file 37.30 KB Preview | Download
BIOMD0000000019.pdf Auto-generated PDF file 686.92 KB Preview | Download
BIOMD0000000019.sci Auto-generated Scilab file 185.00 bytes Preview | Download
BIOMD0000000019.png Auto-generated Reaction graph (PNG) 2.84 MB Preview | Download
BIOMD0000000019.svg Auto-generated Reaction graph (SVG) 287.94 KB Preview | Download
BIOMD0000000019.vcml Auto-generated VCML file 897.00 bytes Preview | Download
BIOMD0000000019.xpp Auto-generated XPP file 28.05 KB Preview | Download

  • Model originally submitted by : Nicolas Le Novère
  • Submitted: 13-Sep-2005 14:19:14
  • Last Modified: 08-Apr-2016 15:31:50
Revisions
  • Version: 2 public model Download this version
    • Submitted on: 08-Apr-2016 15:31:50
    • Submitted by: Nicolas Le Novère
    • With comment: Current version of Schoeberl2002 - EGF MAPK
  • Version: 1 public model Download this version
    • Submitted on: 13-Sep-2005 14:19:14
    • Submitted by: Nicolas Le Novère
    • With comment: Original import of BIOMD0000000019.xml.origin
Legends
: Variable used inside SBML models


Species
Reactions
Reactions Rate Parameters
(EGF-EGFR) => (EGF-EGFR^2)

([EGF:EGFR [plasma membrane]; Pro-epidermal growth factor; Epidermal growth factor receptor]) => ([EGF:EGFR dimer [plasma membrane]; Pro-epidermal growth factor; Epidermal growth factor receptor])
k2*x3*x3-kr2*x4

k2*[EGF:EGFR [plasma membrane]; Pro-epidermal growth factor; Epidermal growth factor receptor]*x3-kr2*[EGF:EGFR dimer [plasma membrane]; Pro-epidermal growth factor; Epidermal growth factor receptor]
kr2 = 6.0 permin; k2 = 0.001 peritempermin
(EGF-EGFR*^2 + GAP) => (EGF-EGFR*^2-GAP)

([Phosphoprotein; Epidermal growth factor receptor; Pro-epidermal growth factor] + [Ras GTPase-activating protein 1; 139150]) => ([EGF-EGFR*^2-GAP])
k8*x5*x14-kr8*x15

k8*[Phosphoprotein; Epidermal growth factor receptor; Pro-epidermal growth factor]*[Ras GTPase-activating protein 1; 139150]-kr8*[EGF-EGFR*^2-GAP]
k8 = 1.0E-4 peritempermin; kr8 = 12.0 permin
(EGFR) => (EGFRi)

([EGFR]) => ([Epidermal growth factor receptor])
k6*x2-kr6*x6

k6*[EGFR]-kr6*[Epidermal growth factor receptor]
k6 = 0.003 permin; kr6 = 0.3 permin
(EGFRi + EGFi) => (EGF-EGFRi)

([Epidermal growth factor receptor] + [EGFi]) => ([Pro-epidermal growth factor; Epidermal growth factor receptor])
k10*x6*x16-kr10*x10

k10*[Epidermal growth factor receptor]*[EGFi]-kr10*[Pro-epidermal growth factor; Epidermal growth factor receptor]
k10 = 3.25581 peritempermin; kr10 = 0.66 permin
(EGF-EGFR*^2-GAP-Grb2-Prot) => (EGF-EGFRi*^2-GAP-Grb2 + Proti)

([Ras GTPase-activating protein 1; Growth factor receptor-bound protein 2; Epidermal growth factor receptor; Pro-epidermal growth factor; AP-type membrane coat adaptor complex]) => ([EGF-EGFRi*^2-GAP-Grb2] + [AP-type membrane coat adaptor complex])
k5*x7

k5*[Ras GTPase-activating protein 1; Growth factor receptor-bound protein 2; Epidermal growth factor receptor; Pro-epidermal growth factor; AP-type membrane coat adaptor complex]
k5 = NaN permin
(EGF-EGFRi*^2 + GAP) => (EGF-EGFRi*^2-GAP)

([Epidermal growth factor receptor; Pro-epidermal growth factor] + [Ras GTPase-activating protein 1; 139150]) => ([EGF-EGFRi*^2-GAP])
k14*x8*x14-kr14*x17

k14*[Epidermal growth factor receptor; Pro-epidermal growth factor]*[Ras GTPase-activating protein 1; 139150]-kr14*[EGF-EGFRi*^2-GAP]
k14 = 1.0E-4 peritempermin; kr14 = 12.0 permin
(EGF-EGFRi*^2) => (EGF-EGFRi*^2deg)

([Epidermal growth factor receptor; Pro-epidermal growth factor]) => ([EGF-EGFRi*^2deg])
k60*x8

k60*[Epidermal growth factor receptor; Pro-epidermal growth factor]
k60 = 0.04002 permin
(Proti) => (Prot)

([AP-type membrane coat adaptor complex]) => ([Prot])
k15*x9

k15*[AP-type membrane coat adaptor complex]
k15 = 600000.0 permin
(EGF-EGFR*^2-GAP-Grb2-Sos-Prot) => (Proti + EGF-EGFRi*^2-GAP-Grb2-Sos)

([EGF-EGFR*^2-GAP-Grb2-Sos-Prot]) => ([AP-type membrane coat adaptor complex] + [EGF-EGFRi*^2-GAP-Grb2-Sos])
k5*x88

k5*[EGF-EGFR*^2-GAP-Grb2-Sos-Prot]
k5 = NaN permin
(EGF-EGFR*^2-GAP-Shc*-Grb2) => (EGF-EGFR*^2-GAP + Shc*-Grb2)

([EGF-EGFR*^2-GAP-Shc*-Grb2]) => ([EGF-EGFR*^2-GAP] + [Shc*-Grb2])
k37*x34-kr37*x15*x39

k37*[EGF-EGFR*^2-GAP-Shc*-Grb2]-kr37*[EGF-EGFR*^2-GAP]*[Shc*-Grb2]
k37 = 18.0 permin; kr37 = 9.0E-5 peritempermin
(EGF-EGFR*^2-GAP-Shc*-Grb2) => (EGF-EGFRi*^2-GAP-Shc*-Grb2)

([EGF-EGFR*^2-GAP-Shc*-Grb2]) => ([EGF-EGFRi*^2-GAP-Shc*-Grb2])
k6*x34-kr6*x65

k6*[EGF-EGFR*^2-GAP-Shc*-Grb2]-kr6*[EGF-EGFRi*^2-GAP-Shc*-Grb2]
k6 = 0.003 permin; kr6 = 0.3 permin
(Ras-GDP + EGF-EGFR*^2-GAP-Shc*-Grb2-Sos) => (EGF-EGFR*^2-GAP-Shc*-Grb2-Sos-Ras-GDP)

([GDP; GTPase HRas] + [EGF-EGFR*^2-GAP-Shc*-Grb2-Sos]) => ([EGF-EGFR*^2-GAP-Shc*-Grb2-Sos-Ras-GDP])
k18*x26*x35-kr18*x36

k18*[GDP; GTPase HRas]*[EGF-EGFR*^2-GAP-Shc*-Grb2-Sos]-kr18*[EGF-EGFR*^2-GAP-Shc*-Grb2-Sos-Ras-GDP]
k18 = 0.0015 peritempermin; kr18 = 78.0 permin
(EGF-EGFR*^2-GAP-Shc*-Grb2-Sos-Ras-GDP) => (EGF-EGFR*^2-GAP-Shc*-Grb2-Sos + Ras-GTP)

([EGF-EGFR*^2-GAP-Shc*-Grb2-Sos-Ras-GDP]) => ([EGF-EGFR*^2-GAP-Shc*-Grb2-Sos] + [GTP; GTPase HRas])
k19*x36-kr19*x35*x28

k19*[EGF-EGFR*^2-GAP-Shc*-Grb2-Sos-Ras-GDP]-kr19*[EGF-EGFR*^2-GAP-Shc*-Grb2-Sos]*[GTP; GTPase HRas]
k19 = 30.0 permin; kr19 = 1.0E-5 peritempermin
Curator's comment:
(added: 14 Jul 2008, 18:05:03, updated: 14 Jul 2008, 18:05:03)
time course of active species as in fig. 2 c,d,e,f in the original publication