Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: " Bringing metabolic networks to life: convenience rate law and thermodynamic constraints | Theoretical Biology and Medical Modelling BioMed Central Research Bringing metabolic networks to life convenience rate law and thermodynamic constraints Wolfram Liebermeister and Edda Klipp Open Access Address Computational Systems Biology Max Planck Institute for Molecular Genetics Ihnestrafie 63-73 14195 Berlin Germany Email Wolfram Liebermeister - lieberme@ Edda Klipp - klipp@ Corresponding author Published 15 December 2006 Received 26 June 2006 Theoretical Biology and Medical Modelling 2006 3 41 doi 1742-4682-3-41 Accepted 15 December 2006 This article is available from http content 3 1 41 2006 Liebermeister and Klipp licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. Results We introduce a simple and general rate law called convenience kinetics . It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence to facilitate model fitting and parameter optimisation for large networks we introduce thermodynamically independent system parameters their values can be varied independently without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates generalised Michaelis-Menten .
