A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles.
BACKGROUND
In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems.


RESULTS
The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations.


CONCLUSIONS
The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.
Kitayama
Tomoya
T
Institute of Advanced Bioscience, Keio University, Fujisawa, 252-8520, Japan. tomoyan@sfc.keio.ac.jp
Kinoshita
Ayako
A
Sugimoto
Masahiro
M
Nakayama
Yoichi
Y
Tomita
Masaru
M
D007700:Kinetics; D008660:Metabolism / Q000502:physiology*; D008954:Models, Biological; D013997:Time Factors