Bungay2003_Thrombin_Generation

  public model
Model Identifier
BIOMD0000000334
Short description

This model is from the article:
A mathematical model of lipid-mediated thrombin generation
Bungay Sharene D., Gentry Patricia A., Gentry Rodney D. Mathematical Medicine and BiologyVolume 20, Issue 1, 1 March 2003, Pages 105-29 12974500,
Abstract:
Thrombin is an enzyme that is generated in both vascular and non-vascular systems. In blood coagulation, a fundamental process in all species, thrombin induces the formation of a fibrin clot. A dynamical model of thrombin generation in the presence of lipid surfaces is presented. This model also includes the self-regulating thrombin feedback reactions, the thrombomodulin-protein C-protein S inhibitory system, tissue factor pathway inhibitor (TFPI), and the inhibitor, antithrombin (AT). The dynamics of this complex system were found to be highly lipid dependent, as would be expected from experimental studies. Simulations of this model indicate that a threshold lipid level is required to generate physiologically relevant amounts of thrombin. The dependence of the onset, the peak levels, and the duration of thrombin generation on lipid was saturable. The lipid concentration affects the way in which the inhibitors modulate thrombin production. A novel feature of this model is the inclusion of the dynamical protein C pathway, initiated by thrombin feedback. This inhibitory system exerts its effects on the lipid surface, where its substrates are formed. The maximum impact of TFPI occurs at intermediate vesicle concentrations. Inhibition by AT is only indirectly affected by the lipid since AT irreversibly binds only to solution phase proteins. In a system with normal plasma concentrations of the proteins involved in thrombin formation, the combination of these three inhibitors is sufficient both to effectively stop thrombin generation prior to the exhaustion of its precursor, prothrombin, and to inhibit all thrombin formed. This model can be used to predict thrombin generation under extreme lipid conditions that are difficult to implement experimentally and to examine thrombin generation in non-vascular systems.

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 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
  • A mathematical model of lipid-mediated thrombin generation.
  • Bungay SD, Gentry PA, Gentry RD
  • Mathematical medicine and biology : a journal of the IMA , 3/ 2003 , Volume 20 , pages: 105-129 , PubMed ID: 12974500
  • Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada N1G 2W1.
  • Thrombin is an enzyme that is generated in both vascular and non-vascular systems. In blood coagulation, a fundamental process in all species, thrombin induces the formation of a fibrin clot. A dynamical model of thrombin generation in the presence of lipid surfaces is presented. This model also includes the self-regulating thrombin feedback reactions, the thrombomodulin-protein C-protein S inhibitory system, tissue factor pathway inhibitor (TFPI), and the inhibitor, antithrombin (AT). The dynamics of this complex system were found to be highly lipid dependent, as would be expected from experimental studies. Simulations of this model indicate that a threshold lipid level is required to generate physiologically relevant amounts of thrombin. The dependence of the onset, the peak levels, and the duration of thrombin generation on lipid was saturable. The lipid concentration affects the way in which the inhibitors modulate thrombin production. A novel feature of this model is the inclusion of the dynamical protein C pathway, initiated by thrombin feedback. This inhibitory system exerts its effects on the lipid surface, where its substrates are formed. The maximum impact of TFPI occurs at intermediate vesicle concentrations. Inhibition by AT is only indirectly affected by the lipid since AT irreversibly binds only to solution phase proteins. In a system with normal plasma concentrations of the proteins involved in thrombin formation, the combination of these three inhibitors is sufficient both to effectively stop thrombin generation prior to the exhaustion of its precursor, prothrombin, and to inhibit all thrombin formed. This model can be used to predict thrombin generation under extreme lipid conditions that are difficult to implement experimentally and to examine thrombin generation in non-vascular systems.
Contributors
Submitter of the first revision: Harish Dharuri
Submitter of this revision: Harish Dharuri
Modellers: Harish Dharuri

Metadata information

is
BioModels Database MODEL9852292468
BioModels Database BIOMD0000000334
isDescribedBy
PubMed 12974500
hasTaxon
Taxonomy Homo sapiens
isVersionOf
Gene Ontology blood coagulation
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model

Curation status
Curated


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Model files

BIOMD0000000334_url.xml SBML L2V1 representation of Bungay2003_Thrombin_Generation 167.66 KB Preview | Download

Additional files

BIOMD0000000334-biopax2.owl Auto-generated BioPAX (Level 2) 110.40 KB Preview | Download
BIOMD0000000334-biopax3.owl Auto-generated BioPAX (Level 3) 191.73 KB Preview | Download
BIOMD0000000334.m Auto-generated Octave file 30.32 KB Preview | Download
BIOMD0000000334.pdf Auto-generated PDF file 471.86 KB Preview | Download
BIOMD0000000334.png Auto-generated Reaction graph (PNG) 890.86 KB Preview | Download
BIOMD0000000334.sci Auto-generated Scilab file 27.71 KB Preview | Download
BIOMD0000000334.svg Auto-generated Reaction graph (SVG) 140.83 KB Preview | Download
BIOMD0000000334.vcml Auto-generated VCML file 246.11 KB Preview | Download
BIOMD0000000334.xpp Auto-generated XPP file 23.96 KB Preview | Download
BIOMD0000000334_urn.xml Auto-generated SBML file with URNs 163.29 KB Preview | Download

  • Model originally submitted by : Harish Dharuri
  • Submitted: Mar 20, 2008 12:03:15 AM
  • Last Modified: May 28, 2014 2:24:41 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: May 28, 2014 2:24:41 PM
    • Submitted by: Harish Dharuri
    • With comment: Current version of Bungay2003_Thrombin_Generation
  • Version: 1 public model Download this version
    • Submitted on: Mar 20, 2008 12:03:15 AM
    • Submitted by: Harish Dharuri
    • With comment: Original import of Bungay2003_Thrombin_Generation

(*) 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
V_mIIa_l => mIIa_l + Va_l compartment*k60*V_mIIa_l k60 = 1.035
IXa_f + LIPID => IXa_l compartment*(konIXa*IXa_f*LIPID/nva-koffIXa*IXa_l) koffIXa = 0.115; nva = 100.0; konIXa = 0.05
VIII_Xa_l => Xa_l + VIIIa_l compartment*k26*VIII_Xa_l k26 = 0.023
PC_f + LIPID => PC_l compartment*(konPC*PC_f*LIPID/nva-koffPC*PC_l) koffPC = 11.5; konPC = 0.05; nva = 100.0
IIa_f + V_l => V_IIa_l compartment*(k27*V_l*IIa_f-k28*V_IIa_l) k27 = 0.1; k28 = 6.94
TM_l + IIa_f => IIa_TM_l compartment*(k64*IIa_f*TM_l-k65*IIa_TM_l) k65 = 0.5; k64 = 1.0
V_Xa_l => Xa_l + Va_l compartment*k23*V_Xa_l k23 = 0.043
VIIa_f + LIPID => VIIa_l compartment*(konVIIa*VIIa_f*LIPID/nva-koffVIIa*VIIa_l) konVIIa = 0.05; nva = 100.0; koffVIIa = 0.227
VIIa_l + TF_l => TF_VIIa_l compartment*(k1*TF_l*VIIa_l-k2*TF_VIIa_l) k2 = 0.005; k1 = 0.5
Curator's comment:
(added: 12 May 2011, 14:06:57, updated: 12 May 2011, 14:06:57)
Thrombin generation model. Factors are denoted by their numbers, with _l and _f suffixes depending on whether they are lipid-bound or fluid phase. Vesicle concentration is derived from LIPID (concentration of head groups) using the formula [vesicle] * 4*10nm^2*pi / 0.74nm^2 per head group. The model was integrated and simulated using Copasi 4.6.32 and plotted using Matplotlib to reproduce figure 4 of the article.