Vinod2011_MitoticExit

  public model
Model Identifier
BIOMD0000000370
Short description

This model is from the article:
Computational modelling of mitotic exit in budding yeast: the role of separase and Cdc14 endocycles
Vinod PK, Freire P, Rattani A, Ciliberto A, Uhlmann F, Novak B. J R Soc Interface. 2011 Aug 7;8(61):1128-41. Epub 2011 Feb 2. 21288956 ,
Abstract:
The operating principles of complex regulatory networks are best understood with the help of mathematical modelling rather than by intuitive reasoning. Hereby, we study the dynamics of the mitotic exit (ME) control system in budding yeast by further developing the Queralt's model. A comprehensive systems view of the network regulating ME is provided based on classical experiments in the literature. In this picture, Cdc20-APC is a critical node controlling both cyclin (Clb2 and Clb5) and phosphatase (Cdc14) branches of the regulatory network. On the basis of experimental situations ranging from single to quintuple mutants, the kinetic parameters of the network are estimated. Numerical analysis of the model quantifies the dependence of ME control on the proteolytic and non-proteolytic functions of separase. We show that the requirement of the non-proteolytic function of separase for ME depends on cyclin-dependent kinase activity. The model is also used for the systematic analysis of the recently discovered Cdc14 endocycles. The significance of Cdc14 endocycles in eukaryotic cell cycle control is discussed as well.

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 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 (L2V4)
Related Publication
  • Computational modelling of mitotic exit in budding yeast: the role of separase and Cdc14 endocycles.
  • Vinod PK, Freire P, Rattani A, Ciliberto A, Uhlmann F, Novak B
  • Journal of the Royal Society, Interface , 8/ 2011 , Volume 8 , pages: 1128-1141 , PubMed ID: 21288956
  • Department of Biochemistry, Oxford Centre for Integrative Systems Biology, University of Oxford, South Parks Road, Oxford OX1 3QU, UK.
  • The operating principles of complex regulatory networks are best understood with the help of mathematical modelling rather than by intuitive reasoning. Hereby, we study the dynamics of the mitotic exit (ME) control system in budding yeast by further developing the Queralt's model. A comprehensive systems view of the network regulating ME is provided based on classical experiments in the literature. In this picture, Cdc20-APC is a critical node controlling both cyclin (Clb2 and Clb5) and phosphatase (Cdc14) branches of the regulatory network. On the basis of experimental situations ranging from single to quintuple mutants, the kinetic parameters of the network are estimated. Numerical analysis of the model quantifies the dependence of ME control on the proteolytic and non-proteolytic functions of separase. We show that the requirement of the non-proteolytic function of separase for ME depends on cyclin-dependent kinase activity. The model is also used for the systematic analysis of the recently discovered Cdc14 endocycles. The significance of Cdc14 endocycles in eukaryotic cell cycle control is discussed as well.
Contributors
Bela Novak

Metadata information

is
BioModels Database MODEL1111030000
BioModels Database BIOMD0000000370
isDerivedFrom
BioModels Database BIOMD0000000409
isDescribedBy
PubMed 21288956
hasTaxon
isVersionOf
Gene Ontology GO:0000278
Cell Cycle Ontology CCO:P0000038

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000370_url.xml SBML L2V4 representation of Vinod2011_MitoticExit 69.38 KB Preview | Download

Additional files

BIOMD0000000370_urn.xml Auto-generated SBML file with URNs 71.93 KB Preview | Download
BIOMD0000000370.svg Auto-generated Reaction graph (SVG) 851.00 Bytes Preview | Download
BIOMD0000000370.xpp Auto-generated XPP file 14.67 KB Preview | Download
BIOMD0000000370.pdf Auto-generated PDF file 208.62 KB Preview | Download
BIOMD0000000370.vcml Auto-generated VCML file 900.00 Bytes Preview | Download
BIOMD0000000370-biopax2.owl Auto-generated BioPAX (Level 2) 13.79 KB Preview | Download
BIOMD0000000370-biopax3.owl Auto-generated BioPAX (Level 3) 16.90 KB Preview | Download
BIOMD0000000370.m Auto-generated Octave file 19.00 KB Preview | Download
BIOMD0000000370.sci Auto-generated Scilab file 195.00 Bytes Preview | Download
BIOMD0000000370.png Auto-generated Reaction graph (PNG) 5.04 KB Preview | Download

  • Model originally submitted by : Bela Novak
  • Submitted: Nov 3, 2011 4:25:35 PM
  • Last Modified: Mar 8, 2012 12:34:01 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Mar 8, 2012 12:34:01 PM
    • Submitted by: Bela Novak
    • With comment: Current version of Vinod2011_MitoticExit
  • Version: 1 public model Download this version
    • Submitted on: Nov 3, 2011 4:25:35 PM
    • Submitted by: Bela Novak
    • With comment: Original import of mitoticexit_2011

(*) 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
Species Initial Concentration/Amount
Swi5 1

Transcriptional factor SWI5
0.0 mol
MBF 1

Multiprotein-bridging factor 1
0.001977 mol
Pds1T 1

Securin
0.601977 mol
Cdc14n 1

Tyrosine-protein phosphatase CDC14
0.00214 mol
Cdc15 1

Cell division control protein 15
0.933 mol
Clb2 2

G2/mitotic-specific cyclin-2
0.0 mol
Sic1 1

Protein SIC1
0.0 mol
Pds1 1

Securin
0.0 mol
Esp1b 1

Separin
0.24857 mol
Esp1 1

Separin
0.24857 mol
Clb2T 1

G2/mitotic-specific cyclin-2
0.999107 mol
Clb5T 1

S-phase entry cyclin-5
0.201977 mol
Cln 1

G1/S-specific cyclin CLN2
0.04079 mol
Cdc20 1

APC/C activator protein CDC20
0.0 mol
Cdh1 1

APC/C activator protein CDH1
0.0 mol
Reactions
Reactions Rate Parameters
Swi5_1 = Vaswi_1*(Swi5T_1-Swi5_1)/((Jswi_1+Swi5T_1)-Swi5_1)-Viswi_1*Swi5_1/(Jswi_1+Swi5_1) Vaswi_1*(Swi5T_1-Swi5_1)/((Jswi_1+Swi5T_1)-Swi5_1)-Viswi_1*Swi5_1/(Jswi_1+Swi5_1) Viswi_1 = NaN; Vaswi_1 = NaN; Swi5T_1 = 1.0; Jswi_1 = 0.1
MBF_1 = kambf_1*(1-MBF_1)/((Jmbf_1+1)-MBF_1)-(kimbf_1*Clb2_2+kimbf_3*Clb5_1)*MBF_1/(Jmbf_1+MBF_1) kambf_1*(1-MBF_1)/((Jmbf_1+1)-MBF_1)-(kimbf_1*Clb2_2+kimbf_3*Clb5_1)*MBF_1/(Jmbf_1+MBF_1) kimbf_1 = 0.5; Jmbf_1 = 0.01; kambf_1 = 0.1; kimbf_3 = 0.5
Pds1T_1 = (kspds_2+kspds_1*MBF_1)-(kdpds_1+kdpds_2*Cdc20_1)*Pds1T_1 (kspds_2+kspds_1*MBF_1)-(kdpds_1+kdpds_2*Cdc20_1)*Pds1T_1 kspds_1 = 0.01; kdpds_2 = 2.0; kspds_2 = 0.006; kdpds_1 = 0.01
Cdc14n_1 = (((kp_1*Polo_1*RENTp_1-lanet_1*((Net1T_1-Net1pp_1)-RENT_1)*Cdc14n_1)+ldnet_1*RENT_1)-Vexp_1*Cdc14n_1)+kimp_1*Cdc14c_1 (((kp_1*Polo_1*RENTp_1-lanet_1*((Net1T_1-Net1pp_1)-RENT_1)*Cdc14n_1)+ldnet_1*RENT_1)-Vexp_1*Cdc14n_1)+kimp_1*Cdc14c_1 kp_1 = 2.0; ldnet_1 = 1.0; lanet_1 = 500.0; kimp_1 = 1.0; Vexp_1 = NaN; Net1T_1 = 1.0
Cdc15_1 = (kac15_1+kac15_2*Cdc14c_1)*(1-Cdc15_1)/((Jcdc15_1+1)-Cdc15_1)-(kic15_1+kic15_2*Clb2_2)*Cdc15_1/(Jcdc15_1+Cdc15_1) (kac15_1+kac15_2*Cdc14c_1)*(1-Cdc15_1)/((Jcdc15_1+1)-Cdc15_1)-(kic15_1+kic15_2*Clb2_2)*Cdc15_1/(Jcdc15_1+Cdc15_1) Jcdc15_1 = 1.0; kac15_2 = 0.5; kic15_2 = 0.2; kac15_1 = 0.03; kic15_1 = 0.03
Clb2_2 = (Clb2T_1+Clb2nd_1)-Trim2_1 [] Clb2nd_1 = 0.0
Sic1_1 = (Sic1T_1-Trim2_1)-Trim5_1 [] []
Pds1_1 = Pds1T_1-Esp1b_1 [] []
Esp1b_1 = lapds_1*Pds1_1*Esp1_1-(ldpds_1+kdesp_1+kdpds_1+kdpds_2*Cdc20_1)*Esp1b_1 lapds_1*Pds1_1*Esp1_1-(ldpds_1+kdesp_1+kdpds_1+kdpds_2*Cdc20_1)*Esp1b_1 lapds_1 = 500.0; ldpds_1 = 1.0; kdesp_1 = 0.004; kdpds_2 = 2.0; kdpds_1 = 0.01
Esp1_1 = Esp1T_1-Esp1b_1 [] []
Clb2T_1 = (ksclb2_1+ksclb2_2*Mcm_1)-V2_1*Clb2T_1 (ksclb2_1+ksclb2_2*Mcm_1)-V2_1*Clb2T_1 ksclb2_1 = 0.015; V2_1 = NaN; ksclb2_2 = 0.005
Clb5T_1 = (ksclb5_2+ksclb5_1*MBF_1)-V6_1*Clb5T_1 (ksclb5_2+ksclb5_1*MBF_1)-V6_1*Clb5T_1 ksclb5_1 = 0.01; V6_1 = NaN; ksclb5_2 = 0.002
Cln_1 = (kscln_2+kscln_1*MBF_1)-kdcln_1*Cln_1 (kscln_2+kscln_1*MBF_1)-kdcln_1*Cln_1 kdcln_1 = 0.25; kscln_1 = 0.1; kscln_2 = 0.01
Cdc20_1 = (ks20_2+ks20_1*Mcm_1)-(kd20_1+kd20_2*Cdh1_1)*Cdc20_1 (ks20_2+ks20_1*Mcm_1)-(kd20_1+kd20_2*Cdh1_1)*Cdc20_1 kd20_1 = 0.1; ks20_2 = 0.001; ks20_1 = 0.05; kd20_2 = 1.0
Cdh1_1 = Vacdh_1*(1-Cdh1_1)/((Jcdh_1+1)-Cdh1_1)-Vicdh_1*Cdh1_1/(Jcdh_1+Cdh1_1) Vacdh_1*(1-Cdh1_1)/((Jcdh_1+1)-Cdh1_1)-Vicdh_1*Cdh1_1/(Jcdh_1+Cdh1_1) Jcdh_1 = 0.01; Vicdh_1 = NaN; Vacdh_1 = NaN
Curator's comment:
(added: 10 Nov 2011, 16:53:46, updated: 10 Nov 2011, 16:53:46)
Figure 2 of the reference publication has been reproduced here. The model was simulated using Copasi v4.7 (Build 34)