Protein interaction energy landscapes are shaped by functional and also non-functional partners

In the crowded cell, a strong selective pressure operates on the proteome to limit the competition between functional and non-functional protein-protein interactions. Understanding how this competition constrains the behavior of proteins with respect to their partners or random encounters is very difficult to address experimentally. Here, we developed an original theoretical framework in order to investigate the propensity of protein surfaces to interact with functional and arbitrary partners and ask whether their interaction propensity is conserved during evolution. Therefore, we performed 5476 cross-docking simulations to systematically characterize the energy landscapes of 74 proteins interacting with different sets of homologs, corresponding to their functional partner’s family or arbitrary protein families. Our framework relies on an original representation of interaction energy landscapes with two-dimensional energy maps that reflect the propensity of a protein surface to interact. To address the evolution of interaction energy landscapes, we systematically compared the energy maps resulting from the docking of a protein with several homologous partners. Strikingly, we show that the interaction propensity of not only binding sites but also of the rest of protein surfaces is conserved for homologous partners, and this feature holds for both functional and arbitrary partners. While most studies aiming at depicting protein-protein interactions focus on native binding sites of proteins, our analysis framework enables in an efficient and automated way, the physical characterization of not only known binding sites, but also of the rest of the protein surfaces, and provides a wealth of valuable information to understand mechanisms driving and regulating protein-protein interactions. It enables to address the energy behavior of a protein in interaction with hundreds of selected partners, providing a functional and systemic point of view of protein interactions, and opening the way for further developments to study the behavior of proteins in a specific environment. Author Summary In the crowded cell, the competition between functional and non-functional interactions is severe. Understanding how a protein binds the right piece in the right way in this complex jigsaw puzzle is crucial and very difficult to address experimentally. To interrogate how this competition constrains the behavior of proteins with respect to their partners or random encounters, we (i) performed thousands of cross-docking simulations to systematically characterize the interaction energy landscapes of functional and non-functional protein pairs and (ii) developed an original theoretical framework based on two-dimensional energy maps that reflect the propensity of a protein surface to interact. Strikingly, we show that the interaction propensity of not only binding sites but also of the rest of protein surfaces is conserved for homologous partners be they functional or not. We show that exploring non-functional interactions (i.e. non-functional assemblies and interactions with non-functional partners) is a viable route to investigate the mechanisms underlying protein-protein interactions. Precisely, our 2D energy maps based strategy enables it in an efficient and automated way. Moreover, our theoretical framework opens the way for the developments of a variety of applications covering functional characterization, binding site prediction, or characterization of protein behaviors in a specific environment.