Kinetic modules in biochemical networks/ Upstream Algorithm

Modules represent fundamental building blocks of cellular networks, and are thought to facilitate robustness of phenotypes against perturbations. While reaction kinetic shapes the concentration of components and reaction rates, its use in identification of modules entails knowledge of parameter values. Here we demonstrate that kinetic modules can be efficiently identified based on steady-state reaction rate couplings in large-scale biochemical networks endowed with mass action kinetics without knowledge of parameter values. We then link the kinetic modules of metabolic networks with robustness of metabolite concentrations to perturbations. Analyzing 34 metabolic network models of 26 organisms, we demonstrate that the ordered binding enzyme mechanism leads to increased concentration robustness compared to random binding. Our findings pave the way for usage of modules in synthetic biology and biotechnological applications.