Curto1998 - purine metabolism

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Short description
Curto1998 - purine metabolism

This is a purine metabolism model that is geared toward studies of gout.

The model uses Generalized Mass Action (GMA; i.e. power law) descriptions of reaction rate laws.

Such descriptions are local approximations that assume independent substrate binding.

This model is described in the article:

Curto R, Voit EO, Sorribas A, Cascante M.
Math Biosci 1998 Jul; 151(1): 1-49

Abstract:

Experimental and clinical data on purine metabolism are collated and analyzed with three mathematical models. The first model is the result of an attempt to construct a traditional kinetic model based on Michaelis-Menten rate laws. This attempt is only partially successful, since kinetic information, while extensive, is not complete, and since qualitative information is difficult to incorporate into this type of model. The data gaps necessitate the complementation of the Michaelis-Menten model with other functional forms that can incorporate different types of data. The most convenient and established representations for this purpose are rate laws formulated as power-law functions, and these are used to construct a Complemented Michaelis-Menten (CMM) model. The other two models are pure power-law-representations, one in the form of a Generalized Mass Action (GMA) system, and the other one in the form of an S-system. The first part of the paper contains a compendium of experimental data necessary for any model of purine metabolism. This is followed by the formulation of the three models and a comparative analysis. For physiological and moderately pathological perturbations in metabolites or enzymes, the results of the three models are very similar and consistent with clinical findings. This is an encouraging result since the three models have different structures and data requirements and are based on different mathematical assumptions. Significant enzyme deficiencies are not so well modeled by the S-system model. The CMM model captures the dynamics better, but judging by comparisons with clinical observations, the best model in this case is the GMA model. The model results are discussed in some detail, along with advantages and disadvantages of each modeling strategy.

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Format
SBML (L2V1)
Related Publication
  • Mathematical models of purine metabolism in man.
  • Curto R, Voit EO, Sorribas A, Cascante M
  • Mathematical biosciences , 7/ 1998 , Volume 151 , pages: 1-49
  • Departament de Bioquímica i Biología Molecular, Facultat de Químiques, Universitat de Barcelona, Catalunya, Spain.
  • Experimental and clinical data on purine metabolism are collated and analyzed with three mathematical models. The first model is the result of an attempt to construct a traditional kinetic model based on Michaelis-Menten rate laws. This attempt is only partially successful, since kinetic information, while extensive, is not complete, and since qualitative information is difficult to incorporate into this type of model. The data gaps necessitate the complementation of the Michaelis-Menten model with other functional forms that can incorporate different types of data. The most convenient and established representations for this purpose are rate laws formulated as power-law functions, and these are used to construct a Complemented Michaelis-Menten (CMM) model. The other two models are pure power-law-representations, one in the form of a Generalized Mass Action (GMA) system, and the other one in the form of an S-system. The first part of the paper contains a compendium of experimental data necessary for any model of purine metabolism. This is followed by the formulation of the three models and a comparative analysis. For physiological and moderately pathological perturbations in metabolites or enzymes, the results of the three models are very similar and consistent with clinical findings. This is an encouraging result since the three models have different structures and data requirements and are based on different mathematical assumptions. Significant enzyme deficiencies are not so well modeled by the S-system model. The CMM model captures the dynamics better, but judging by comparisons with clinical observations, the best model in this case is the GMA model. The model results are discussed in some detail, along with advantages and disadvantages of each modeling strategy.
Contributors
Nicolas Le Novère

Metadata information

is
BioModels Database MODEL6617035399
BioModels Database BIOMD0000000015
Reactome REACT_522
KEGG Pathway Purine metabolism - Homo sapiens (human)
isDescribedBy
PubMed 9664759
hasTaxon
Taxonomy Homo sapiens
isVersionOf
Curation status
Curated
  • Model originally submitted by : Nicolas Le Novère
  • Submitted: Sep 13, 2005 2:11:12 PM
  • Last Modified: Jul 2, 2014 5:48:59 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Jul 2, 2014 5:48:59 PM
    • Submitted by: Nicolas Le Novère
    • With comment: Current version of Curto1998 - purine metabolism
  • Version: 1 public model Download this version
    • Submitted on: Sep 13, 2005 2:11:12 PM
    • Submitted by: Nicolas Le Novère
    • With comment: Original import of Curto1998_purineMetabol
Curator's comment:
(added: 02 Jun 2008, 14:14:13, updated: 02 Jun 2008, 14:14:13)
Reproduction of figure 2b of the original publication, showing the time course of hypoxanthine of the GMA model in response to a PRPP pulse. As mentioned in the article, the concentration of PRPP was increased 10 fold from 5 to 50 microM. There seems to be a typo in the articles figure caption, as the increase of PRPP takes place at t =0 not 10. The simulation was performed using Copasi 4.4 b.26.