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

Published: 31-10-2019| Version 1 | DOI: 10.17632/ctjfr72bpm.1
Contributors:
Hugo Schweke,
Marie-Helene Mucchielli,
Sophie Sacquin-Mora,
Wayning Bei,
Anne Lopes

Description

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. Here, the dataset contains all data produced and analyzed in Schweke, Mucchielli, Sacquin-Mora, Bei and Lopes, Protein interaction energy landscapes are shaped by functional and also non-functional partners. This includes 103x103 protein docking calculations, the resulting 2D energy maps (text and pdf files) and the protein surface properties of the 103 proteins of the study projected in 2D (text and pdf files).

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