Literature DB >> 24123488

Detection of peptide-binding sites on protein surfaces: the first step toward the modeling and targeting of peptide-mediated interactions.

Assaf Lavi1, Chi Ho Ngan, Dana Movshovitz-Attias, Tanggis Bohnuud, Christine Yueh, Dmitri Beglov, Ora Schueler-Furman, Dima Kozakov.   

Abstract

Peptide-mediated interactions, in which a short linear motif binds to a globular domain, play major roles in cellular regulation. An accurate structural model of this type of interaction is an excellent starting point for the characterization of the binding specificity of a given peptide-binding domain. A number of different protocols have recently been proposed for the accurate modeling of peptide-protein complex structures, given the structure of the protein receptor and the binding site on its surface. When no information about the peptide binding site(s) is a priori available, there is a need for new approaches to locate peptide-binding sites on the protein surface. While several approaches have been proposed for the general identification of ligand binding sites, peptides show very specific binding characteristics, and therefore, there is a need for robust and accurate approaches that are optimized for the prediction of peptide-binding sites. Here, we present PeptiMap, a protocol for the accurate mapping of peptide binding sites on protein structures. Our method is based on experimental evidence that peptide-binding sites also bind small organic molecules of various shapes and polarity. Using an adaptation of ab initio ligand binding site prediction based on fragment mapping (FTmap), we optimize a protocol that specifically takes into account peptide binding site characteristics. In a high-quality curated set of peptide-protein complex structures PeptiMap identifies for most the accurate site of peptide binding among the top ranked predictions. We anticipate that this protocol will significantly increase the number of accurate structural models of peptide-mediated interactions.
Copyright © 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  FFT sampling; PeptiDB; binding site detection; mapping; protein peptide interactions

Mesh:

Substances:

Year:  2013        PMID: 24123488      PMCID: PMC4183195          DOI: 10.1002/prot.24422

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  36 in total

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Authors:  K L Morrison; G A Weiss
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Review 3.  CHARMM: the biomolecular simulation program.

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Journal:  J Comput Chem       Date:  2009-07-30       Impact factor: 3.376

Review 4.  Peptide docking and structure-based characterization of peptide binding: from knowledge to know-how.

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Review 5.  Locating and characterizing binding sites on proteins.

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6.  The structural basis of peptide-protein binding strategies.

Authors:  Nir London; Dana Movshovitz-Attias; Ora Schueler-Furman
Journal:  Structure       Date:  2010-02-10       Impact factor: 5.006

7.  Structural conservation of druggable hot spots in protein-protein interfaces.

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8.  Can self-inhibitory peptides be derived from the interfaces of globular protein-protein interactions?

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  25 in total

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3.  Fully Blind Docking at the Atomic Level for Protein-Peptide Complex Structure Prediction.

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Journal:  Structure       Date:  2016-09-15       Impact factor: 5.006

4.  GalaxyPepDock: a protein-peptide docking tool based on interaction similarity and energy optimization.

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5.  Exploring the molecular basis of RNA recognition by the dimeric RNA-binding protein via molecular simulation methods.

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6.  PEP-SiteFinder: a tool for the blind identification of peptide binding sites on protein surfaces.

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Journal:  Nucleic Acids Res       Date:  2014-05-06       Impact factor: 16.971

7.  ClusPro in rounds 38 to 45 of CAPRI: Toward combining template-based methods with free docking.

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8.  Protein-peptide docking using CABS-dock and contact information.

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9.  Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking.

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10.  Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces.

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