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BIOMD0000000271 - Becker2010_EpoR_CoreModel

 

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Reference Publication
Publication ID: 20488988
Becker V, Schilling M, Bachmann J, Baumann U, Raue A, Maiwald T, Timmer J, Klingmüller U.
Covering a broad dynamic range: information processing at the erythropoietin receptor.
Science 2010 Jun; 328(5984): 1404-1408
Division Systems Biology of Signal Transduction, DKFZ-ZMBH Alliance, German Cancer Research Center, 69120 Heidelberg, Germany.  [more]
Model
Original Model: BIOMD0000000271.xml.origin
Submitter: Verena Becker
Submission ID: MODEL1005260000
Submission Date: 26 May 2010 13:59:38 UTC
Last Modification Date: 31 Jan 2012 13:10:43 UTC
Creation Date: 26 May 2010 16:12:55 UTC
Encoders:  Vijayalakshmi Chelliah
   Marcel Schilling
   Verena Becker
set #1
bqbiol:isPartOf KEGG Pathway ko04630
KEGG Pathway ko04640
bqbiol:occursIn Taxonomy Murinae
Brenda Tissue Ontology BTO:0001035
bqbiol:isVersionOf Gene Ontology erythropoietin receptor activity
Notes

This is the core model described in the article:
Covering a Broad Dynamic Range: Information Processing at the Erythropoietin Receptor
Verena Becker, Marcel Schilling, Julie Bachmann, Ute Baumann, Andreas Raue, Thomas Maiwald, Jens Timmer and Ursula Klingmüller; Science Published Online May 20, 2010; DOI: 10.1126/science.1184913 PMID: 20488988
Abstract:
Cell surface receptors convert extracellular cues into receptor activation, thereby triggering intracellular signaling networks and controlling cellular decisions. A major unresolved issue is the identification of receptor properties that critically determine processing of ligand-encoded information. We show by mathematical modeling of quantitative data and experimental validation that rapid ligand depletion and replenishment of cell surface receptor are characteristic features of the erythropoietin (Epo) receptor (EpoR). The amount of Epo-EpoR complexes and EpoR activation integrated over time corresponds linearly to ligand input, covering a broad range of ligand concentrations. This relation solely depends on EpoR turnover independent of ligand binding, suggesting an essential role of large intracellular receptor pools. These receptor properties enable the system to cope with basal and acute demand in the hematopoietic system.

SBML model exported from PottersWheel.

% PottersWheel model definition file

function m = BeckerSchilling2010_EpoR_CoreModel()

m             = pwGetEmptyModel();

%% Meta information

m.ID          = 'BeckerSchilling2010_EpoR_CoreModel';
m.name        = 'BeckerSchilling2010_EpoR_CoreModel';
m.description = 'BeckerSchilling2010_EpoR_CoreModel';
m.authors     = {'Verena Becker',' Marcel Schilling'};
m.dates       = {'2010'};
m.type        = 'PW-2-0-42';

%% X: Dynamic variables
% m = pwAddX(m, ID, startValue, type, minValue, maxValue, unit, compartment, name, description, typeOfStartValue)

m = pwAddX(m, 'EpoR'     ,     516, 'fix'   ,    0, 10000,   [], 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'Epo'      , 2030.19, 'global', 1890,  2310,   [], 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'Epo_EpoR' ,       0, 'fix'   ,    0, 10000,   [], 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'Epo_EpoRi',       0, 'fix'   ,    0, 10000,   [], 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'dEpoi'    ,       0, 'fix'   ,    0, 10000,   [], 'cell', []  , []  , []             , []  , 'protein.generic');
m = pwAddX(m, 'dEpoe'    ,       0, 'fix'   ,    0, 10000,   [], 'cell', []  , []  , []             , []  , 'protein.generic');


%% R: Reactions
% m = pwAddR(m, reactants, products, modifiers, type, options, rateSignature, parameters, description, ID, name, fast, compartments, parameterTrunks, designerPropsR, stoichiometry, reversible)

m = pwAddR(m, {            }, {'EpoR'      }, {  }, 'C' , [] , 'k1*k2', {'kt','Bmax'}, [], 'reaction0001');
m = pwAddR(m, {'EpoR'      }, {            }, {  }, 'MA', [] , []     , {'kt'       }, [], 'reaction0002');
m = pwAddR(m, {'Epo','EpoR'}, {'Epo_EpoR'  }, {  }, 'MA', [] , []     , {'kon'      }, [], 'reaction0003');
m = pwAddR(m, {'Epo_EpoR'  }, {'Epo','EpoR'}, {  }, 'MA', [] , []     , {'koff'     }, [], 'reaction0004');
m = pwAddR(m, {'Epo_EpoR'  }, {'Epo_EpoRi' }, {  }, 'MA', [] , []     , {'ke'       }, [], 'reaction0005');
m = pwAddR(m, {'Epo_EpoRi' }, {'Epo','EpoR'}, {  }, 'MA', [] , []     , {'kex'      }, [], 'reaction0006');
m = pwAddR(m, {'Epo_EpoRi' }, {'dEpoi'     }, {  }, 'MA', [] , []     , {'kdi'      }, [], 'reaction0007');
m = pwAddR(m, {'Epo_EpoRi' }, {'dEpoe'     }, {  }, 'MA', [] , []     , {'kde'      }, [], 'reaction0008');



%% C: Compartments
% m = pwAddC(m, ID, size,  outside, spatialDimensions, name, unit, constant)

m = pwAddC(m, 'cell', 1);


%% K: Dynamical parameters
% m = pwAddK(m, ID, value, type, minValue, maxValue, unit, name, description)

m = pwAddK(m, 'kt'  , 0.0329366 , 'global', 1e-007, 1000);
m = pwAddK(m, 'Bmax', 516       , 'fix'   , 492   , 540 );
m = pwAddK(m, 'kon' , 0.00010496, 'global', 1e-007, 1000);
m = pwAddK(m, 'koff', 0.0172135 , 'global', 1e-007, 1000);
m = pwAddK(m, 'ke'  , 0.0748267 , 'global', 1e-007, 1000);
m = pwAddK(m, 'kex' , 0.00993805, 'global', 1e-007, 1000);
m = pwAddK(m, 'kdi' , 0.00317871, 'global', 1e-007, 1000);
m = pwAddK(m, 'kde' , 0.0164042 , 'global', 1e-007, 1000);


%% Default sampling time points
m.t = 0:3:99;


%% Y: Observables
% m = pwAddY(m, rhs, ID, scalingParameter, errorModel, noiseType, unit, name, description, alternativeIDs, designerProps)

m = pwAddY(m, 'Epo + dEpoe'      , 'Epo_extracellular_obs');
m = pwAddY(m, 'Epo_EpoR'         , 'Epo_cellsurface_obs'  );
m = pwAddY(m, 'Epo_EpoRi + dEpoi', 'Epo_intracellular_obs');


%% S: Scaling parameters
% m = pwAddS(m, ID, value, type, minValue, maxValue, unit, name, description)

m = pwAddS(m, 'scale_Epo_extracellular_obs', 1, 'fix', 0, 100);
m = pwAddS(m, 'scale_Epo_cellsurface_obs'  , 1, 'fix', 0, 100);
m = pwAddS(m, 'scale_Epo_intracellular_obs', 1, 'fix', 0, 100);


%% Designer properties (do not modify)
m.designerPropsM = [1 1 1 0 0 0 400 250 600 400 1 1 1 0 0 0 0];

This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 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.

Model
Publication ID: 20488988 Submission Date: 26 May 2010 13:59:38 UTC Last Modification Date: 31 Jan 2012 13:10:43 UTC Creation Date: 26 May 2010 16:12:55 UTC
Mathematical expressions
Reactions
reaction_1 reaction_2 reaction_3 reaction_4
reaction_5 reaction_6 reaction_7 reaction_8
Rules
Assignment Rule (variable: Epo_medium) Assignment Rule (variable: Epo_cells)    
Physical entities
Compartments Species
medium Epo dEpoe  
cellsurface EpoR Epo_EpoR  
cell Epo_EpoRi dEpoi  
Global parameters
kt Bmax kon koff
ke kex kdi kde
Epo_medium Epo_cells    
Reactions (8)
 
 reaction_1  → [EpoR];  
 
 reaction_2 [EpoR] → ;  
 
 reaction_3 [Epo] + [EpoR] → [Epo_EpoR];  
 
 reaction_4 [Epo_EpoR] → [Epo] + [EpoR];  
 
 reaction_5 [Epo_EpoR] → [Epo_EpoRi];  
 
 reaction_6 [Epo_EpoRi] → [Epo] + [EpoR];  
 
 reaction_7 [Epo_EpoRi] → [dEpoi];  
 
 reaction_8 [Epo_EpoRi] → [dEpoe];  
 
Rules (2)
 
 Assignment Rule (name: Epo_medium) Epo_medium = Epo+dEpoe
 
 Assignment Rule (name: Epo_cells) Epo_cells = Epo_EpoRi+dEpoi
 
 medium Spatial dimensions: 3.0  Compartment size: 1.0
 
 Epo
Compartment: medium
Initial concentration: 2030.19
 
 dEpoe
Compartment: medium
Initial concentration: 0.0
 
 cellsurface Spatial dimensions: 3.0  Compartment size: 1.0
 
 EpoR
Compartment: cellsurface
Initial concentration: 516.0
 
 Epo_EpoR
Compartment: cellsurface
Initial concentration: 0.0
 
 cell Spatial dimensions: 3.0  Compartment size: 1.0
 
 Epo_EpoRi
Compartment: cell
Initial concentration: 0.0
 
 dEpoi
Compartment: cell
Initial concentration: 0.0
 
Global Parameters (10)
 
 kt
Value: 0.0329366   (Units: per_minute)
Constant
 
 Bmax
Value: 516.0   (Units: pM)
Constant
 
 kon
Value: 1.0496E-4   (Units: per_minute_per_pM)
Constant
 
 koff
Value: 0.0172135   (Units: per_minute)
Constant
 
 ke
Value: 0.0748267   (Units: per_minute)
Constant
 
 kex
Value: 0.00993805   (Units: per_minute)
Constant
 
 kdi
Value: 0.00317871   (Units: per_minute)
Constant
 
 kde
Value: 0.0164042   (Units: per_minute)
Constant
 
   Epo_medium
Value: NaN
 
   Epo_cells
Value: NaN
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000271

Curator's comment: (updated: 19 Aug 2011 13:40:27 BST)

Fig 2B of the reference publication has been reproduced. The model was integrated and simulated using Copasi 4.6 (Build 32).

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