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.