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      The Overlap of Small Molecule and Protein Binding Sites within Families of Protein Structures

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      1 , * , 2 , *
      PLoS Computational Biology
      Public Library of Science

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          Abstract

          Protein–protein interactions are challenging targets for modulation by small molecules. Here, we propose an approach that harnesses the increasing structural coverage of protein complexes to identify small molecules that may target protein interactions. Specifically, we identify ligand and protein binding sites that overlap upon alignment of homologous proteins. Of the 2,619 protein structure families observed to bind proteins, 1,028 also bind small molecules (250–1000 Da), and 197 exhibit a statistically significant (p<0.01) overlap between ligand and protein binding positions. These “bi-functional positions”, which bind both ligands and proteins, are particularly enriched in tyrosine and tryptophan residues, similar to “energetic hotspots” described previously, and are significantly less conserved than mono-functional and solvent exposed positions. Homology transfer identifies ligands whose binding sites overlap at least 20% of the protein interface for 35% of domain–domain and 45% of domain–peptide mediated interactions. The analysis recovered known small-molecule modulators of protein interactions as well as predicted new interaction targets based on the sequence similarity of ligand binding sites. We illustrate the predictive utility of the method by suggesting structural mechanisms for the effects of sanglifehrin A on HIV virion production, bepridil on the cellular entry of anthrax edema factor, and fusicoccin on vertebrate developmental pathways. The results, available at http://pibase.janelia.org, represent a comprehensive collection of structurally characterized modulators of protein interactions, and suggest that homologous structures are a useful resource for the rational design of interaction modulators.

          Author Summary

          Proteins function through their interactions with other biological molecules, including other proteins. Often times, these interactions underlie cellular processes that go awry in disease. Therefore, modulating these interactions with small molecules is an active area of research for new drugs to treat diseases and new chemical tools to dissect cellular interaction networks. However, targeting protein–protein interactions has proven to be more challenging than the typical drug targets found on individual proteins. Here, we present a computational approach that aims to help in this challenge by identifying regions of protein–protein interfaces that may be amenable to targeting by small molecules. Through a comprehensive analysis of all known protein structures, we identify closely related proteins that in one case bind a protein and in another case bind a small molecule. We find that a significant number of protein–protein interactions occur through surface regions that bind small molecules in related proteins. These “bi-functional” positions, which can bind both proteins and ligands, will serve as an additional piece of structural information that can aid experimentalists in developing small molecules that modulate protein interactions.

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          Most cited references41

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          Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae.

          Defining protein complexes is critical to virtually all aspects of cell biology. Two recent affinity purification/mass spectrometry studies in Saccharomyces cerevisiae have vastly increased the available protein interaction data. The practical utility of such high throughput interaction sets, however, is substantially decreased by the presence of false positives. Here we created a novel probabilistic metric that takes advantage of the high density of these data, including both the presence and absence of individual associations, to provide a measure of the relative confidence of each potential protein-protein interaction. This analysis largely overcomes the noise inherent in high throughput immunoprecipitation experiments. For example, of the 12,122 binary interactions in the general repository of interaction data (BioGRID) derived from these two studies, we marked 7504 as being of substantially lower confidence. Additionally, applying our metric and a stringent cutoff we identified a set of 9074 interactions (including 4456 that were not among the 12,122 interactions) with accuracy comparable to that of conventional small scale methodologies. Finally we organized proteins into coherent multisubunit complexes using hierarchical clustering. This work thus provides a highly accurate physical interaction map of yeast in a format that is readily accessible to the biological community.
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            The atomic structure of protein-protein recognition sites.

            The non-covalent assembly of proteins that fold separately is central to many biological processes, and differs from the permanent macromolecular assembly of protein subunits in oligomeric proteins. We performed an analysis of the atomic structure of the recognition sites seen in 75 protein-protein complexes of known three-dimensional structure: 24 protease-inhibitor, 19 antibody-antigen and 32 other complexes, including nine enzyme-inhibitor and 11 that are involved in signal transduction.The size of the recognition site is related to the conformational changes that occur upon association. Of the 75 complexes, 52 have "standard-size" interfaces in which the total area buried by the components in the recognition site is 1600 (+/-400) A2. In these complexes, association involves only small changes of conformation. Twenty complexes have "large" interfaces burying 2000 to 4660 A2, and large conformational changes are seen to occur in those cases where we can compare the structure of complexed and free components. The average interface has approximately the same non-polar character as the protein surface as a whole, and carries somewhat fewer charged groups. However, some interfaces are significantly more polar and others more non-polar than the average. Of the atoms that lose accessibility upon association, half make contacts across the interface and one-third become fully inaccessible to the solvent. In the latter case, the Voronoi volume was calculated and compared with that of atoms buried inside proteins. The ratio of the two volumes was 1.01 (+/-0.03) in all but 11 complexes, which shows that atoms buried at protein-protein interfaces are close-packed like the protein interior. This conclusion could be extended to the majority of interface atoms by including solvent positions determined in high-resolution X-ray structures in the calculation of Voronoi volumes. Thus, water molecules contribute to the close-packing of atoms that insure complementarity between the two protein surfaces, as well as providing polar interactions between the two proteins. Copyright 1999 Academic Press.
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              A hot spot of binding energy in a hormone-receptor interface.

              The x-ray crystal structure of the complex between human growth hormone (hGH) and the extracellular domian of its first bound receptor (hGHbp) shows that about 30 side chains from each protein make contact. Individual replacement of contact residues in the hGHbp with alanine showed that a central hydrophobic region, dominated by two tryptophan residues, accounts for more than three-quarters of the binding free energy. This "functional epitope" is surrounded by less important contact residues that are generally hydrophilic and partially hydrated, so that the interface resembles a cross section through a globular protein. The functionally important residues on the hGHbp directly contact those on hGH. Thus, only a small and complementary set of contact residues maintains binding affinity, a property that may be general to protein-protein interfaces.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                February 2010
                February 2010
                5 February 2010
                : 6
                : 2
                : e1000668
                Affiliations
                [1 ]Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, United States of America
                [2 ]Department of Bioengineering and Therapeutic Sciences, Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, California, United States of America
                University of California San Diego, United States of America
                Author notes

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

                Article
                09-PLCB-RA-1090R2
                10.1371/journal.pcbi.1000668
                2816688
                20140189
                03abe5e3-292f-4cc8-8b1e-e95fc6bf3f43
                Davis, Sali. 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.
                History
                : 14 September 2009
                : 31 December 2009
                Page count
                Pages: 10
                Categories
                Research Article
                Computational Biology/Macromolecular Structure Analysis

                Quantitative & Systems biology
                Quantitative & Systems biology

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