Curto1998 - purine metabolism

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:

Mathematical models of
purine metabolism in man.

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.

This model is hosted on
BioModels Database
and identified by:
BIOMD0000000015.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.

To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.