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Beauty Is in the Eye of the Beholder: Proteins Can Recognize Binding Sites of Homologous Proteins in More than One Way


PLoS Computational Biology

Public Library of Science

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      Understanding the mechanisms of protein–protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein–protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A) and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein–protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution.

      Author Summary

      Interaction between proteins is a fundamental process, generic to most biological pathways. The increasing number of protein–protein complexes with atomic data should help us to understand the major factors that guide protein interactions. In particular, a number of examples are available of similar proteins that interact with proteins that are very different in terms of structure and function. An intuitive hypothesis to explain the ability of these different proteins to recognize the same partner is that they display the same local region for interaction, in other words, they imitate the same binding site. Here, we quantify the similarity between these putatively mimicking binding sites. We show that it is not statistically significant. We confirm this observation on the small sets of evolutionarily conserved residues. Our results suggest that different proteins that bind the same protein do not imitate binding sites, but probably target specific locations or residues at the binding site.

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          This review examines protein complexes in the Brookhaven Protein Databank to gain a better understanding of the principles governing the interactions involved in protein-protein recognition. The factors that influence the formation of protein-protein complexes are explored in four different types of protein-protein complexes--homodimeric proteins, heterodimeric proteins, enzyme-inhibitor complexes, and antibody-protein complexes. The comparison between the complexes highlights differences that reflect their biological roles.

            Author and article information

            Université de Lyon, Lyon, France; Université Lyon 1, IFR 128, CNRS, UMR 5086 Institut de Biologie et Chimie des Protéines (IBCP), Lyon, France
            National Cancer Institute, United States of America and Tel Aviv University, Israel
            Author notes

            Conceived and designed the experiments: JM. Performed the experiments: JM. Analyzed the data: JM. Wrote the paper: JM.

            Role: Editor
            PLoS Comput Biol
            PLoS Computational Biology
            Public Library of Science (San Francisco, USA )
            June 2010
            June 2010
            17 June 2010
            : 6
            : 6
            Juliette Martin. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
            Pages: 13
            Research Article
            Computational Biology/Macromolecular Structure Analysis

            Quantitative & Systems biology


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