Jenkinson2011_EGF_MAPK

  public model
Model Identifier
BIOMD0000000399
Short description

This is a model described in the article:
Thermodynamically Consistent Model Calibration in Chemical Kinetics.
Garrett Jenkinson and John Goutsias, BMC Systems Biology 2011 May 6;5(1):64.; PMID:21548948.

ABSTRACT:
BACKGROUND:
The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function.
RESULTS:
We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database.
CONCLUSIONS:
TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting.

This model is a thermodynamically feasible version of a previous model in the BioModels database,BIOMD0000000019, described in Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Schoeberl et al (2002), PMID:11923843.
The only difference between the present model and the model listed under BIOMD0000000019 are the values of the parameters.

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2012 The BioModels.net Team.
For more information see the terms of use.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Format
SBML (L2V1)
Related Publication
  • Thermodynamically consistent model calibration in chemical kinetics.
  • Jenkinson G, Goutsias J
  • BMC systems biology , 0/ 2011 , Volume 5 , pages: 64 , PubMed ID: 21548948
  • Whitaker Biomedical Engineering Institute, The Johns Hopkins University, Baltimore, MD 21218, USA. goutsias@jhu.edu
  • BACKGROUND: The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. RESULTS: We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. CONCLUSIONS: TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting.
Contributors
Garrett Jenkinson

Metadata information

is
BioModels Database MODEL1105060003
BioModels Database BIOMD0000000399
isDerivedFrom
BioModels Database BIOMD0000000019
isDescribedBy
PubMed 21548948
hasTaxon
Taxonomy Homo sapiens
hasVersion
Gene Ontology MAPK cascade
Gene Ontology Ras protein signal transduction

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000399_url.xml SBML L2V1 representation of Jenkinson2011_EGF_MAPK 247.06 KB Preview | Download

Additional files

BIOMD0000000399.m Auto-generated Octave file 37.73 KB Preview | Download
BIOMD0000000399_urn.xml Auto-generated SBML file with URNs 239.34 KB Preview | Download
BIOMD0000000399.pdf Auto-generated PDF file 681.79 KB Preview | Download
BIOMD0000000399-biopax2.owl Auto-generated BioPAX (Level 2) 192.42 KB Preview | Download
BIOMD0000000399.png Auto-generated Reaction graph (PNG) 2.62 MB Preview | Download
BIOMD0000000399.sci Auto-generated Scilab file 185.00 Bytes Preview | Download
BIOMD0000000399.xpp Auto-generated XPP file 28.48 KB Preview | Download
BIOMD0000000399-biopax3.owl Auto-generated BioPAX (Level 3) 330.83 KB Preview | Download
BIOMD0000000399.svg Auto-generated Reaction graph (SVG) 319.71 KB Preview | Download
BIOMD0000000399.vcml Auto-generated VCML file 897.00 Bytes Preview | Download

  • Model originally submitted by : Garrett Jenkinson
  • Submitted: May 6, 2011 8:16:29 PM
  • Last Modified: Apr 8, 2016 6:21:34 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Apr 8, 2016 6:21:34 PM
    • Submitted by: Garrett Jenkinson
    • With comment: Current version of Jenkinson2011_EGF_MAPK
  • Version: 1 public model Download this version
    • Submitted on: May 6, 2011 8:16:29 PM
    • Submitted by: Garrett Jenkinson
    • With comment: Original import of BIOMD0000000399.xml.origin

(*) 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
x34 => x15 + x39 k37*x34-kr37*x15*x39 kr37 = 5.477036E-6 peritempermin; k37 = 29.34687 permin
x34 => x65 k6*x34-kr6*x65 k6 = 4.123214E-4 permin; kr6 = 0.294324 permin
x34 + x12 => x91 k4*x34*x12-kr4*x91 k4 = 3.047285E-5 peritempermin; kr4 = 0.1230832 permin
x36 => x35 + x28 k19*x36-kr19*x35*x28 k19 = 349.772 permin; kr19 = 5.84737E-6 peritempermin
x35 + x43 => x37 k20*x35*x43-kr20*x37 k20 = 5.17656E-5 peritempermin; kr20 = 12.816 permin
x37 => x35 + x26 k21*x37-kr21*x35*x26 k21 = 0.4722901 permin; kr21 = 1.714441E-5 peritempermin
x30 + x33 => x35 k41*x30*x33-kr41*x35 kr41 = 44.60169 permin; k41 = 0.001522817 peritempermin
x35 => x66 k6*x35-kr6*x66 k6 = 4.123214E-4 permin; kr6 = 0.294324 permin
x35 + x12 => x92 k4*x35*x12-kr4*x92 k4 = 3.047285E-5 peritempermin; kr4 = 0.1230832 permin
x26 + x66 => x67 k18*x26*x66-kr18*x67 k18 = 0.004463938 peritempermin; kr18 = 11.1361 permin
x27 => x20 k6*x27-kr6*x20 k6 = 4.123214E-4 permin; kr6 = 0.294324 permin
x27 + x12 => x89 k4*x27*x12-kr4*x89 k4 = 3.047285E-5 peritempermin; kr4 = 0.1230832 permin
x25 + x43 => x29 k20*x25*x43-kr20*x29 k20 = 5.17656E-5 peritempermin; kr20 = 12.816 permin
x29 => x25 + x26 k21*x29-kr21*x25*x26 k21 = 0.4722901 permin; kr21 = 1.714441E-5 peritempermin
Curator's comment:
(added: 03 Nov 2011, 14:33:22, updated: 03 Nov 2011, 14:33:22)
Figure 1 and S1 of the reference publication has been reproduced here. The inconsistency between the y-axis measure of the curation figure and that of the paper is due to the units. In the papers, ERK_PP concentration dynamics is measured in mol/m3 and as the number of molecules. The plot shows the dynamics of ERK_PP for different values of EGF ranging from 0.0625ng/mL to 50ng/mL. In the model, EGF is presented as the number of molecules. EGF=5962molecules correspond to 50ng/mL, 596.2molecules correspond to 5ng/mL, 49.62 correspond to .5ng/mL, 12.405molecules correspond to 0.125ng/mL and 6.2025molecules correspond to 0.0625ng/mL. The simulated was done using Copasi v4.7 (Build 34).