Reduced-order modelling of biochemical networks: application to the GTPase-cycle signalling module.
Biochemical systems embed complex networks and hence development and analysis of their detailed models pose a challenge for computation. Coarse-grained biochemical models, called reduced-order models (ROMs), consisting of essential biochemical mechanisms are more useful for computational analysis and for studying important features of a biochemical network. The authors present a novel method to model-reduction by identifying potentially important parameters using multidimensional sensitivity analysis. A ROM is generated for the GTPase-cycle module of m1 muscarinic acetylcholine receptor, Gq, and regulator of G-protein signalling 4 (a GTPase-activating protein or GAP) starting from a detailed model of 48 reactions. The resulting ROM has only 17 reactions. The ROM suggested that complexes of G-protein coupled receptor (GPCR) and GAP--which were proposed in the detailed model as a hypothesis--are required to fit the experimental data. Models previously published in the literature are also simulated and compared with the ROM. Through this comparison, a minimal ROM, that also requires complexes of GPCR and GAP, with just 15 parameters is generated. The proposed reduced-order modelling methodology is scalable to larger networks and provides a general framework for the reduction of models of biochemical systems.
Maurya
M R
MR
San Diego Supercomputer Center, La Jolla, CA 92093, USA.
Bornheimer
S J
SJ
Venkatasubramanian
V
V
Subramaniam
S
S
D000465:Algorithms; D000818:Animals; D001671:Biochemistry / Q000379:methods; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D020558:GTP Phosphohydrolases / Q000378:metabolism*; D020690:GTPase-Activating Proteins / Q000378:metabolism*; D006801:Humans; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods*
D020690:GTPase-Activating Proteins; D020558:GTP Phosphohydrolases