ABSTRACT:
This a model from the article:
Modelling the dynamics of the yeast pheromone pathway.
Kofahl B, Klipp E
Yeast[2004 Jul; Volume: 21 (Issue: 10 )] Page info: 831-50
15300679,
Abstract:
We present a mathematical model of the dynamics of the pheromone pathways in haploid yeast cells of mating type MATa after stimulation with pheromone alpha-factor. The model consists of a set of differential equations and describes the dynamics of signal transduction from the receptor via several steps, including a G protein and a scaffold MAP kinase cascade, up to changes in the gene expression after pheromone stimulation in terms of biochemical changes (complex formations, phosphorylations, etc.). The parameters entering the models have been taken from the literature or adapted to observed time courses or behaviour. Using this model we can follow the time course of the various complex formation processes and of the phosphorylation states of the proteins involved. Furthermore, we can explain the phenotype of more than a dozen well-characterized mutants and also the graded response of yeast cells to varying concentrations of the stimulating pheromone.
The model was updated on 21st October 2010, by Vijayalakshmi Chelliah.
The following changes were made: 1) The model has been converted to SBML l2v4.
2) The model has been recurated and the curation figure was updated (units are in nanoMolar; but the publication has units in microMolar). Simulations were done using Copasi v4.6 (Build 32).
3) Notes have been added.
4) Annotation for one of the species has been corrected (Complex M).
SBML level 2 code generated for the JWS Online project by Jacky Snoep using
PySCeS
Run this model online at
http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004)
Web-based
modelling using JWS Online, Bioinformatics, 20:2143-2144
The following are the four major differences between the original publication by Kofahl et al and the model that actually is able to replicate the results as depicted in the publication (those corrections have been made in agreement with the authors):
1. Bar1 is the inactive protease present inside the cell but the publication wrongly mentions that Bar1 is also the protease that is present on the extracellular surface.
The model correctly names the protease in it's different forms by calling inactive Bar1 within the cell as Bar1, active Bar1 within the cell as Bar1a and extracellular Bar1 as Bar1aex
2. The initial amount of Alpha-factor is given as 1000nM but the model uses a value of 100nM.
3. The value of the paramenter k8 is given as 0.33 but the model uses a value of 0.033.
4. The value of the paramenter k41 is given as 0.002 but the model uses a value of 0.02.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/).(http://www.ebi.ac.uk/biomodels/). 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.
Harish Dharuri 
