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Specificity in Stochastic Protein-Protein Interaction Networks


For a cell to properly respond to external stimuli, it must translate the stimulus into a signal from the cell surface, to the inner cell machinery, such as the nucleus. This signal transduction occurs by way of protein-protein reaction networks, which act as a set of relays via chemical reactions down to the cell’s interior. These relays, often called cascades, are seen everywhere in biology, and involve many proteins in intricate reaction networks; more- over, these reaction networks will often have many separate cascades within them, and to complicate things further, cascades can share components with other cascades, opening a possibility for cross-talk. The concept of specificity has been used to quantify the relative strength of on-versus off-target interactions for individual protein-protein interactions. The concept has also been extended to larger signaling cascades in order to measure how much the system prefers the correct pathway over the incorrect pathway. In this work, we study specificity in the context of discrete, stochastic chemical kinetics networks. We study two networks motifs, small commonly seen subportions of the network, known as the CB3 and bifan motif. We use a variety of stochastic modeling techniques, including Master Equations, simulations, and numerical approximations. We find that the fluctuations of specificity in a stochastic network system show qualitatively different behavior than the deterministic, mean-field specificity. Such stochastic effects may contribute to cellular optimization of relative protein concentrations, by affecting the balance between strengthening in-pathway signals while minimizing cross-talk.

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