Publication details for Dr Junli Liu

Liu, JL (2005). Kinetic constraints for formation of steady states in biochemical networks. Biophysical Journal 88(5): 3212-3223.

• Publication type: Journal Article
• ISSN/ISBN: 0006-3495, 1542-0086
• DOI: 10.1529/biophysj.104.056085
• Keywords: Complex metabolic networks, Saccharomyces-cerevisiae, Escherichia-coli, Pathway analysis, Causal connectivities, Sufficient conditions, Substrate-inhibition, System coordination, Gene-expression, Genome.
• Further publication details on publisher web site
• Durham Research Online (DRO) - may include full text

Author(s) from Durham

• Dr Junli Liu

Abstract

The constraint-based analysis has emerged as a useful tool for analysis of biochemical networks. This work introduces the concept of kinetic constraints. It is shown that maximal reaction rates are appropriate constraints only for isolated enzymatic reactions. For biochemical networks, it is revealed that constraints for formation of a steady state require specific relationships between maximal reaction rates of all enzymes. The constraints for a branched network are significantly different from those for a cyclic network. Moreover, the constraints do not require Michaelis-Menten constants for most enzymes, and they only require the constants for the enzymes at the branching or cyclic point. Reversibility of reactions at system boundary or branching point may significantly impact on kinetic constraints. When enzymes are regulated, regulations may impose severe kinetic constraints for the formation of steady states. As the complexity of a network increases, kinetic constraints become more severe. In addition, it is demonstrated that kinetic constraints for networks with co-regulation can be analyzed using the approach. In general, co-regulation enhances the constraints and therefore larger fluctuations in fluxes can be accommodated in the networks with co-regulation. As a first example of the application, we derive the kinetic constraints for an actual network that describes sucrose accumulation in the sugar cane culm, and confirm their validity using numerical simulations.