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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.

Related Publication
  • DARPP-32 is a robust integrator of dopamine and glutamate signals.
  • Fernandez E, Schiappa R, Girault JA, Le Novère N
  • PLoS computational biology , 12/ 2006 , Volume 2 , pages: e176 , PubMed ID: 17194217
  • EMBL-EBI, Wellcome-Trust Genome Campus, Hinxton, United Kingdom.
  • Integration of neurotransmitter and neuromodulator signals in the striatum plays a central role in the functions and dysfunctions of the basal ganglia. DARPP-32 is a key actor of this integration in the GABAergic medium-size spiny neurons, in particular in response to dopamine and glutamate. When phosphorylated by cAMP-dependent protein kinase (PKA), DARPP-32 inhibits protein phosphatase-1 (PP1), whereas when phosphorylated by cyclin-dependent kinase 5 (CDK5) it inhibits PKA. DARPP-32 is also regulated by casein kinases and by several protein phosphatases. These complex and intricate regulations make simple predictions of DARPP-32 dynamic behaviour virtually impossible. We used detailed quantitative modelling of the regulation of DARPP-32 phosphorylation to improve our understanding of its function. The models included all the combinations of the three best-characterized phosphorylation sites of DARPP-32, their regulation by kinases and phosphatases, and the regulation of those enzymes by cAMP and Ca(2+) signals. Dynamic simulations allowed us to observe the temporal relationships between cAMP and Ca(2+) signals. We confirmed that the proposed regulation of protein phosphatase-2A (PP2A) by calcium can account for the observed decrease of Threonine 75 phosphorylation upon glutamate receptor activation. DARPP-32 is not simply a switch between PP1-inhibiting and PKA-inhibiting states. Sensitivity analysis showed that CDK5 activity is a major regulator of the response, as previously suggested. Conversely, the strength of the regulation of PP2A by PKA or by calcium had little effect on the PP1-inhibiting function of DARPP-32 in these conditions. The simulations showed that DARPP-32 is not only a robust signal integrator, but that its response also depends on the delay between cAMP and calcium signals affecting the response to the latter. This integration did not depend on the concentration of DARPP-32, while the absolute effect on PP1 varied linearly. In silico mutants showed that Ser137 phosphorylation affects the influence of the delay between dopamine and glutamate, and that constitutive phosphorylation in Ser137 transforms DARPP-32 in a quasi-irreversible switch. This work is a first attempt to better understand the complex interactions between cAMP and Ca(2+) regulation of DARPP-32. Progressive inclusion of additional components should lead to a realistic model of signalling networks underlying the function of striatal neurons.
Submitter of the first revision: Nicolas Le Novère
Submitter of this revision: Nicolas Le Novère
Modellers: Nicolas Le Novère

Metadata information

BioModels Database MODEL3492630792
BioModels Database BIOMD0000000152
PubMed 17194217
Taxonomy Homo sapiens

Curation status

Original model(s)


Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files

BIOMD0000000152_url.xml SBML L2V1 representation of Fernandez2006_ModelA 197.98 KB Preview | Download

Additional files

BIOMD0000000152-biopax2.owl Auto-generated BioPAX (Level 2) 189.37 KB Preview | Download
BIOMD0000000152-biopax3.owl Auto-generated BioPAX (Level 3) 338.73 KB Preview | Download
BIOMD0000000152.m Auto-generated Octave file 46.81 KB Preview | Download
BIOMD0000000152.pdf Auto-generated PDF file 732.38 KB Preview | Download
BIOMD0000000152.png Auto-generated Reaction graph (PNG) 3.47 MB Preview | Download
BIOMD0000000152.sci Auto-generated Scilab file 67.00 Bytes Preview | Download
BIOMD0000000152.svg Auto-generated Reaction graph (SVG) 0.00 Bytes Preview | Download
BIOMD0000000152.vcml Auto-generated VCML file 266.39 KB Preview | Download
BIOMD0000000152.xpp Auto-generated XPP file 34.90 KB Preview | Download
BIOMD0000000152_urn.xml Auto-generated SBML file with URNs 193.62 KB Preview | Download

  • Model originally submitted by : Nicolas Le Novère
  • Submitted: Oct 30, 2007 6:58:31 PM
  • Last Modified: Apr 8, 2016 4:37:35 PM
  • Version: 2 public model Download this version
    • Submitted on: Apr 8, 2016 4:37:35 PM
    • Submitted by: Nicolas Le Novère
    • With comment: Current version of Fernandez2006_ModelA
  • Version: 1 public model Download this version
    • Submitted on: Oct 30, 2007 6:58:31 PM
    • Submitted by: Nicolas Le Novère
    • With comment: Original import of Fernandez2006_ModelA

(*) 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.

: Variable used inside SBML models

Reactions Rate Parameters
D_CK1 => D + CK1 Spine*koff2*D_CK1 koff2=12.0
D34 + CDK5 => D34_CDK5 Spine*D34*CDK5*kon4 kon4=5600000.0
D_CK1 => D137 + CK1 Spine*kcat2*D_CK1 kcat2=3.0
D34_CK1 => D34_137 + CK1 Spine*D34_CK1*kcat5 kcat5=3.0
D + PKA => D_PKA Spine*D*PKA*kon3 kon3=5600000.0
PDE_PKA => PDEP + PKA Spine*PDE_PKA*kcat31 kcat31=9.0
D34_75 + PP2B => D34_75_PP2B Spine*D34_75*PP2B*kon17 kon17=1.0E7
D34_75_134_PP2A => D34_137 + PP2A Spine*D34_75_134_PP2A*kcat25 kcat25=10.0
D75 + PP2A => D75_PP2A Spine*D75*PP2A*kon9 kon9=3800000.0
Curator's comment:
(added: 03 Mar 2008, 11:20:27, updated: 03 Mar 2008, 11:20:27)
Figure 5A reproduced with SBML odeSolver. Note that the ordinates are in concentrations rather than number of molecules.