  We are looking at local protein interaction networks from the perspective of
directed, labeled graphs with quantitative values for monotonic changes in
concentrations. These systems can be used to perform stability analysis for a
stable attractor, given initial values. They can also show re-configuration of
whole system states by dynamic insertion of links, given specific patterns of
input. The latter issue seems particularly relevant for the concept of
multistability in cellular memory. We attempt to show that this level of
analysis is well-suited for a number of relevant biological subsystems, such as
transactivation in cardiac myocytes or G-protein coupling to adrenergic
receptors. In particular, we analyse the 'motif' of an "overflow gate" as a
concentration-dependent system reconfiguration.
