Benary2019 - Controlling NFKB dynamics by B-TrCP

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Model Identifier
Short description
its a mathematical model studying impact of b_TrCP on NFKB nuclear dynamics. This model is derived from Lipniacki2004 (PMID:15094015).
Related Publication
  • Controlling Nuclear NF-κB Dynamics by β-TrCP-Insights from a Computational Model.
  • Benary U, Wolf J
  • Biomedicines , 5/ 2019 , Volume 7 , Issue 2 , PubMed ID: 31137887
  • Mathematical Modelling of Cellular Processes, Max Delbrück Center for Molecular Medicine, 13125 Berlin-Buch, Germany.
  • The canonical nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway regulates central processes in mammalian cells and plays a fundamental role in the regulation of inflammation and immunity. Aberrant regulation of the activation of the transcription factor NF-κB is associated with severe diseases such as inflammatory bowel disease and arthritis. In the canonical pathway, the inhibitor IκB suppresses NF-κB's transcriptional activity. NF-κB becomes active upon the degradation of IκB, a process that is, in turn, regulated by the β-transducin repeat-containing protein (β-TrCP). β-TrCP has therefore been proposed as a promising pharmacological target in the development of novel therapeutic approaches to control NF-κB's activity in diseases. This study explores the extent to which β-TrCP affects the dynamics of nuclear NF-κB using a computational model of canonical NF-κB signaling. The analysis predicts that β-TrCP influences the steady-state concentration of nuclear NF-κB, as well as changes characteristic dynamic properties of nuclear NF-κB, such as fold-change and the duration of its response to pathway stimulation. The results suggest that the modulation of β-TrCP has a high potential to regulate the transcriptional activity of NF-κB.
Submitter of the first revision: Krishna Kumar Tiwari
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari

Metadata information

is (2 statements)
BioModels Database MODEL1908130003
BioModels Database BIOMD0000000794

isDescribedBy (1 statement)
PubMed 31137887

hasTaxon (1 statement)
Taxonomy Mus musculus

hasProperty (3 statements)
isPartOf (1 statement)
occursIn (1 statement)

Curation status


Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files

Benary2019.xml SBML L2V4 file for benary2019 234.86 KB Preview | Download

Additional files

Benary2019.cps COPASI 4.24 (build 197) file for benary2019 230.93 KB Preview | Download
Benary2019.sedml SEDML file for benary2019 2.41 KB Preview | Download

  • Model originally submitted by : Krishna Kumar Tiwari
  • Submitted: Aug 13, 2019 4:29:35 PM
  • Last Modified: Aug 13, 2019 4:29:35 PM
  • Version: 3 public model Download this version
    • Submitted on: Aug 13, 2019 4:29:35 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Automatically added model identifier BIOMD0000000794
: Variable used inside SBML models

Species Initial Concentration/Amount
IKK neutral

Inhibitor of nuclear factor kappa-B kinase subunit alpha
199.999999987913 nmol
IKK inact

Inhibitor of nuclear factor kappa-B kinase subunit alpha
2.78889437354332E-25 nmol

NF-kappa-B inhibitor alpha
0.00286970847085134 nmol
IKK active

Inhibitor of nuclear factor kappa-B kinase subunit alpha
2.44263810567829E-26 nmol
IKKactive IkB

NF-kappa-B inhibitor alpha ; Inhibitor of nuclear factor kappa-B kinase subunit alpha
1.17746437501971E-28 nmol

NF-kappa-B inhibitor alpha
2.5066291758827 nmol
IkB nuc

NF-kappa-B inhibitor alpha
3.43573095552417 nmol
IKKactive IkB NFKB

NF-kappa-B inhibitor alpha ; Inhibitor of nuclear factor kappa-B kinase subunit alpha ; Nuclear factor NF-kappa-B p105 subunit
1.41567842221093E-26 nmol
Reactions Rate Parameters
IKK_neutral => Cytosol*Kdeg*IKK_neutral Kdeg = 0.0075
IKK_active => IKK_inact; TNF, A20 Cytosol*function_for_R26(k2, TNF, A20, IKK_active) k2 = 0.006
IkB_mRNA => Nucleus*c3a*IkB_mRNA c3a = 0.024
IKK_active + IkB_NFKB => IKKactive_IkB_NFKB Cytosol*a3*IKK_active*IkB_NFKB a3 = 0.06
IKK_active + IkB => IKKactive_IkB Cytosol*a2*IKK_active*IkB a2 = 0.012
=> IkB; IkB_mRNA function_for_substrateless_production(c4a, IkB_mRNA) c4a = 30.0
IkB_nuc => Nucleus*function_for_transport(e1a, Kv, IkB_nuc) e1a = 0.03; Kv = 5.0
IKKactive_IkB_NFKB => IKK_active + NFKB; b_TrCP Cytosol*function_for_R3(t2, b_TrCP, IKKactive_IkB_NFKB) t2 = 6.0
IKK_inact => Cytosol*Kdeg*IKK_inact Kdeg = 0.0075
Curator's comment:
(added: 13 Aug 2019, 16:29:05, updated: 13 Aug 2019, 16:29:05)
Literature figure 2A,B,C is reproduced. Simulation is done for 630 mins post TNF stimulation on a pre-simulated steady state updated system. Model encoding and simulation is done on COPASI 4.24 (Build 197). Data plotted using Microsoft excel.