Hornberg2005 - MAPKsignalling

  public model
Model Identifier
BIOMD0000000667
Short description
Hornberg2005 - MAPKsignalling
Large model of the ERK signalling network. Results from this model were used to generate a simplified version of the network.

This model is described in the article:

Hornberg JJ, Binder B, Bruggeman FJ, Schoeberl B, Heinrich R, Westerhoff HV.
Oncogene 2005 Aug; 24(36): 5533-5542

Abstract:

Oncogenesis results from changes in kinetics or in abundance of proteins in signal transduction networks. Recently, it was shown that control of signalling cannot reside in a single gene product, and might well be dispersed over many components. Which of the reactions in these complex networks are most important, and how can the existing molecular information be used to understand why particular genes are oncogenes whereas others are not? We implement a new method to help address such questions. We apply control analysis to a detailed kinetic model of the epidermal growth factor-induced mitogen-activated protein kinase network. We determine the control of each reaction with respect to three biologically relevant characteristics of the output of this network: the amplitude, duration and integrated output of the transient phosphorylation of extracellular signal-regulated kinase (ERK). We confirm that control is distributed, but far from randomly: a small proportion of reactions substantially control signalling. In particular, the activity of Raf is in control of all characteristics of the transient profile of ERK phosphorylation, which may clarify why Raf is an oncogene. Most reactions that really matter for one signalling characteristic are also important for the other characteristics. Our analysis also predicts the effects of mutations and changes in gene expression.

This model is hosted on BioModels Database and identified by: BIOMD0000000667.

To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8.

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
  • Control of MAPK signalling: from complexity to what really matters.
  • Hornberg JJ, Binder B, Bruggeman FJ, Schoeberl B, Heinrich R, Westerhoff HV
  • Oncogene , 8/ 2005 , Volume 24 , Issue 36 , pages: 5533-5542 , PubMed ID: 16007170
  • Department of Molecular Cell Physiology, Institute of Molecular Cell Biology, Faculty of Earth and Life Sciences, Vrije Universiteit, Amsterdam, The Netherlands.
  • Oncogenesis results from changes in kinetics or in abundance of proteins in signal transduction networks. Recently, it was shown that control of signalling cannot reside in a single gene product, and might well be dispersed over many components. Which of the reactions in these complex networks are most important, and how can the existing molecular information be used to understand why particular genes are oncogenes whereas others are not? We implement a new method to help address such questions. We apply control analysis to a detailed kinetic model of the epidermal growth factor-induced mitogen-activated protein kinase network. We determine the control of each reaction with respect to three biologically relevant characteristics of the output of this network: the amplitude, duration and integrated output of the transient phosphorylation of extracellular signal-regulated kinase (ERK). We confirm that control is distributed, but far from randomly: a small proportion of reactions substantially control signalling. In particular, the activity of Raf is in control of all characteristics of the transient profile of ERK phosphorylation, which may clarify why Raf is an oncogene. Most reactions that really matter for one signalling characteristic are also important for the other characteristics. Our analysis also predicts the effects of mutations and changes in gene expression.
Contributors
Submitter of the first revision: Vijayalakshmi Chelliah
Submitter of this revision: administrator
Modellers: administrator, Vijayalakshmi Chelliah

Metadata information

is (2 statements)
BioModels Database MODEL0848279215
BioModels Database BIOMD0000000667

isDescribedBy (2 statements)
PubMed 16007170
PubMed 16007170

isVersionOf (1 statement)

Curation status
Curated

Tags

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files

BIOMD0000000667_url.xml SBML L2V4 representation of Hornberg2005 - MAPKsignalling 573.99 KB Preview | Download

Additional files

BIOMD0000000667-biopax2.owl Auto-generated BioPAX (Level 2) 232.25 KB Preview | Download
BIOMD0000000667-biopax3.owl Auto-generated BioPAX (Level 3) 410.94 KB Preview | Download
BIOMD0000000667.m Auto-generated Octave file 48.06 KB Preview | Download
BIOMD0000000667.pdf Auto-generated PDF file 545.95 KB Preview | Download
BIOMD0000000667.png Auto-generated Reaction graph (PNG) 2.09 MB Preview | Download
BIOMD0000000667.sci Auto-generated Scilab file 47.07 KB Preview | Download
BIOMD0000000667.svg Auto-generated Reaction graph (SVG) 325.55 KB Preview | Download
BIOMD0000000667.xpp Auto-generated XPP file 38.51 KB Preview | Download
BIOMD0000000667_urn.xml Auto-generated SBML file with URNs 573.50 KB Preview | Download
MODEL0848279215.cps COPASI file with annotations and plot to produce figure 2 that shows ERK-PP concentration over time (seconds) 600.71 KB Preview | Download
MODEL0848279215.sedml SED-ML file to produce figure 2. Model time units are seconds and not minutes. Y-axis: ERK_PP. 1.67 KB Preview | Download

  • Model originally submitted by : Vijayalakshmi Chelliah
  • Submitted: Apr 28, 2009 1:25:23 PM
  • Last Modified: Feb 1, 2018 9:57:43 AM
Revisions
  • Version: 3 public model Download this version
    • Submitted on: Feb 1, 2018 9:57:43 AM
    • Submitted by: administrator
    • With comment: Notes updated using online editor.
  • Version: 2 public model Download this version
    • Submitted on: Apr 28, 2009 1:25:23 PM
    • Submitted by: Vijayalakshmi Chelliah
    • With comment: Current version of Hornberg2005_MAPKsignalling
  • Version: 1 public model Download this version
    • Submitted on: Apr 28, 2009 1:25:23 PM
    • Submitted by: Vijayalakshmi Chelliah
    • With comment: Original import of Hornberg2005_MAPKsignalling

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Reactions
Reactions Rate Parameters
MEK_P + Raf_0 => MEK_P_Raf Compartment*(k44*MEK_P*Raf_0-kd52*MEK_P_Raf) k44 = 1.95E-5; kd52 = 0.033
_EGF_EGFRi__2_GAP + Shc_0 => _EGF_EGFRi__2_GAP_SHC_0 Compartment*(k37*_EGF_EGFRi__2_GAP*Shc_0-kd37*_EGF_EGFRi__2_GAP_SHC_0) k37 = 1.5E-6; kd37 = 0.3
_EGF_EGFRi__2_GAP_SHC__Grb2 => _EGF_EGFRi___2deg Compartment*k60*_EGF_EGFRi__2_GAP_SHC__Grb2 k60 = 0.0055
ERKi_PP + Sos => Sos_ERKi_PP Compartment*(k126*ERKi_PP*Sos-kd126*Sos_ERKi_PP) k126 = 1.66E-7; kd126 = 2.0
EGFR => EGF_EGFR; EGF Compartment*(k1*EGF*EGFR-kd1*EGF_EGFR) kd1 = 0.00384; k1 = 3.0E7
_EGF_EGFRi_2 => _EGF_EGFRi__2 Compartment*(k3*_EGF_EGFRi_2-kd3*_EGF_EGFRi__2) k3 = 1.0; kd3 = 0.01
_EGF_EGFR__2_GAP_Grb2_Sos_Prot => Proti + _EGF_EGFRi__2_GAP_Grb2_Sos Compartment*kd5*_EGF_EGFR__2_GAP_Grb2_Sos_Prot kd5 = 0.0146
_EGF_EGFR__2_GAP_SHC__Grb2_Prot_0 => Proti + _EGF_EGFRi__2_GAP_SHC__Grb2 Compartment*kd5*_EGF_EGFR__2_GAP_SHC__Grb2_Prot_0 kd5 = 0.0146
_EGF_EGFR__2_GAP_SHC__Grb2 + Prot => _EGF_EGFR__2_GAP_SHC__Grb2_Prot_0 Compartment*(k4*_EGF_EGFR__2_GAP_SHC__Grb2*Prot-kd4*_EGF_EGFR__2_GAP_SHC__Grb2_Prot_0) kd4 = 0.00166; k4 = 1.73E-7
_EGF_EGFR__2_GAP_SHC__Grb2_Sos_Ras_GDP + Prot => _EGF_EGFR__2_GAP_SHC__Grb2_Sos_Ras_GDP_Prot_0 Compartment*(k4*_EGF_EGFR__2_GAP_SHC__Grb2_Sos_Ras_GDP*Prot-kd4*_EGF_EGFR__2_GAP_SHC__Grb2_Sos_Ras_GDP_Prot_0) kd4 = 0.00166; k4 = 1.73E-7
Curator's comment:
(added: 01 Feb 2018, 09:54:40, updated: 01 Feb 2018, 09:54:40)
?Figure 2 of the reference publication has been reproduced. The simulations were performed and plots were obtained using Copasi 4.19 (Build 140).