The strength of protein-protein interactions controls the information capacity and dynamical response of signaling networks

Eukaryotic cells transmit information by signaling through complex networks of interacting proteins. Here we develop a theoretical and computational framework that relates the biophysics of protein-protein interactions (PPIs) within a signaling network to its information processing properties. We formulate a statistical physics-inspired model and combine it with information-theoretic methods to find that PPIs are a key determinant of information transmission within a signaling network, with weak interactions giving rise to “noise” that diminishes information transmission. While noise can be mitigated by increasing interaction strength, the accompanying increase in transmission comes at the expense of a slower dynamical response. This suggests that the biophysics of signaling protein interactions give rise to a fundamental “speed-information” trade-off. We further use this framework to interrogate the relationship between pathway cross-talks and information capacity, as well as its implications in synthetic biology.