Protein social behavior makes a stronger signal for partner identification than surface geometry.
Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico-chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross-docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S-index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface-based (ranking) score to discriminate partners from non-interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137-154. © 2016 Wiley Periodicals, Inc.
Sorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative - UMR 7238, Paris, 75005, France.
Elodie
E
Laine
Sorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative - UMR 7238, Paris, 75005, France.|Institut Universitaire de France, Paris, 75005, France.
Alessandra
A
Carbone
D001665:Binding Sites; D004926:Escherichia coli / Q000737:chemistry; D006801:Humans; D015233:Models, Statistical; D062105:Molecular Docking Simulation; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping / Q000379:methods / Q000706:statistics & numerical data*; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D012984:Software; D014780:Viruses / Q000737:chemistry
D011506:Proteins
binding site; complete cross-docking; geometrical docking; interface prediction; partner identification; protein-protein interaction