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type: Species
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initial concentration: 90.9
name: P

BIOMD0000000400
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rule: 118858
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parameter: 118952
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parameter: 118968
parameter: 118929
parameter: 118922
parameter: 118955
rule: 118868
rule: 118866
rule: 118886
volume units: metaid_0000323
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substance units: metaid_0000321
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parameter: 118960
parameter: 118948
parameter: 118976
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species: 118901
parameter: 118930
type: SBMLModel
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parameter: 118933
parameter: 118950
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species: 118906
parameter: 118923
species: 118907
parameter: 118940
length unit: length
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parameter: 118956
parameter: 118926
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parameter: 118961
species: 118916
is version of: FMA:83108
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curated: true
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parameter: 118964
notes: This a model from the article: Modeling hypertrophic IP3 transients in the cardiac myocyte. Cooling M, Hunter P, Crampin EJ. Biophys J 2007 Nov 15;93(10):3421-33 17693463 , Abstract: Cardiac hypertrophy is a known risk factor for heart disease, and at the cellular level is caused by a complex interaction of signal transduction pathways. The IP3-calcineurin pathway plays an important role in stimulating the transcription factor NFAT which binds to DNA cooperatively with other hypertrophic transcription factors. Using available kinetic data, we construct a mathematical model of the IP3 signal production system after stimulation by a hypertrophic alpha-adrenergic agonist (endothelin-1) in the mouse atrial cardiac myocyte. We use a global sensitivity analysis to identify key controlling parameters with respect to the resultant IP3 transient, including the phosphorylation of cell-membrane receptors, the ligand strength and binding kinetics to precoupled (with G(alpha)GDP) receptor, and the kinetics associated with precoupling the receptors. We show that the kinetics associated with the receptor system contribute to the behavior of the system to a great extent, with precoupled receptors driving the response to extracellular ligand. Finally, by reparameterizing for a second hypertrophic alpha-adrenergic agonist, angiotensin-II, we show that differences in key receptor kinetic and membrane density parameters are sufficient to explain different observed IP3 transients in essentially the same pathway. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Cooling M, Hunter P, Crampin EJ. (2007) - version02 The original CellML model was created by: Cooling, Mike, m.cooling@aukland.ac.nz The University of Auckland The Bioengineering Institute 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…
time units: metaid_0000322
species: 118913

118909
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118896
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initial concentration: 0.1
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constant: false
name: Ca
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118943
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118922
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value: NaN
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118957
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118929
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constant: true
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name: kr3
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118953
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value: NaN
name: J11
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118936
is: SBO:0000153
constant: true
value: 4.0E-4
name: kf5
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118963
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118939
is: SBO:0000153
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value: 1.0
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118901
type: Species
initial concentration: 10000.0
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118967
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118977
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initial concentration: 0.0
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118912
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initial amount: NaN
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name: kf4
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118974
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118921
is: SBO:0000356
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value: 3.0E-5
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118958
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118897
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value: NaN
name: L
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constant: true
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118911
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constant: true
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118950
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type: Parameter

118978
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118828
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size: 1.0
spatial dimensions: 3.0
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118926
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value: 27500.0
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118913
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118934
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118955
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value: 0.1
name: Ls
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118910
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118923
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118962
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name: kf13
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118928
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constant: true
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118956
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initial amount: NaN
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name: R

118946
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118933
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constant: false
value: NaN
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118966
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constant: true
value: 19.8
name: Km14
type: Parameter

118918
is: SBO:0000153
constant: true
value: 3.0E-4
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118952
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value: 1.0
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type: Parameter

ORG:
  orgname: The Bioengineering Institute, The University of Auckland.
n:
  given: Mike
  family: Cooling

W3 CDTF: Tue Apr 28 12:55:20 BST 2009

W3 CDTF: Mon Jul 16 12:57:19 BST 2012