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      PepSite: prediction of peptide-binding sites from protein surfaces

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          Abstract

          Complex biological functions emerge through intricate protein–protein interaction networks. An important class of protein–protein interaction corresponds to peptide-mediated interactions, in which a short peptide stretch from one partner interacts with a large protein surface from the other partner. Protein–peptide interactions are typically of low affinity and involved in regulatory mechanisms, dynamically reshaping protein interaction networks. Due to the relatively small interaction surface, modulation of protein–peptide interactions is feasible and highly attractive for therapeutic purposes. Unfortunately, the number of available 3D structures of protein–peptide interfaces is very limited. For typical cases where a protein–peptide structure of interest is not available, the PepSite web server can be used to predict peptide-binding spots from protein surfaces alone. The PepSite method relies on preferred peptide-binding environments calculated from a set of known protein–peptide 3D structures, combined with distance constraints derived from known peptides. We present an updated version of the web server that is orders of magnitude faster than the original implementation, returning results in seconds instead of minutes or hours. The PepSite web server is available at http://pepsite2.russelllab.org.

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          Most cited references35

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          PROSITE, a protein domain database for functional characterization and annotation

          PROSITE consists of documentation entries describing protein domains, families and functional sites, as well as associated patterns and profiles to identify them. It is complemented by ProRule, a collection of rules based on profiles and patterns, which increases the discriminatory power of these profiles and patterns by providing additional information about functionally and/or structurally critical amino acids. PROSITE is largely used for the annotation of domain features of UniProtKB/Swiss-Prot entries. Among the 983 (DNA-binding) domains, repeats and zinc fingers present in Swiss-Prot (release 57.8 of 22 September 2009), 696 (∼70%) are annotated with PROSITE descriptors using information from ProRule. In order to allow better functional characterization of domains, PROSITE developments focus on subfamily specific profiles and a new profile building method giving more weight to functionally important residues. Here, we describe AMSA, an annotated multiple sequence alignment format used to build a new generation of generalized profiles, the migration of ScanProsite to Vital-IT, a cluster of 633 CPUs, and the adoption of the Distributed Annotation System (DAS) to facilitate PROSITE data integration and interchange with other sources. The latest version of PROSITE (release 20.54, of 22 September 2009) contains 1308 patterns, 863 profiles and 869 ProRules. PROSITE is accessible at: http://www.expasy.org/prosite/.
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            Predicting functionally important residues from sequence conservation.

            All residues in a protein are not equally important. Some are essential for the proper structure and function of the protein, whereas others can be readily replaced. Conservation analysis is one of the most widely used methods for predicting these functionally important residues in protein sequences. We introduce an information-theoretic approach for estimating sequence conservation based on Jensen-Shannon divergence. We also develop a general heuristic that considers the estimated conservation of sequentially neighboring sites. In large-scale testing, we demonstrate that our combined approach outperforms previous conservation-based measures in identifying functionally important residues; in particular, it is significantly better than the commonly used Shannon entropy measure. We find that considering conservation at sequential neighbors improves the performance of all methods tested. Our analysis also reveals that many existing methods that attempt to incorporate the relationships between amino acids do not lead to better identification of functionally important sites. Finally, we find that while conservation is highly predictive in identifying catalytic sites and residues near bound ligands, it is much less effective in identifying residues in protein-protein interfaces. Data sets and code for all conservation measures evaluated are available at http://compbio.cs.princeton.edu/conservation/
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              Cell signaling in space and time: where proteins come together and when they're apart.

              Signal transduction can be defined as the coordinated relay of messages derived from extracellular cues to intracellular effectors. More simply put, information received on the cell surface is processed across the plasma membrane and transmitted to intracellular targets. This requires that the activators, effectors, enzymes, and substrates that respond to cellular signals come together when they need to.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                July 2012
                July 2012
                16 May 2012
                16 May 2012
                : 40
                : Web Server issue
                : W423-W427
                Affiliations
                1CellNetworks, University of Heidelberg, 69120 Heidelberg, Germany, 2The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK, 3Centre for Systems Biology, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, M5G 1X5, Canada and 4Department of Molecular Genetics, University of Toronto, Toronto, M5S 1A8, Canada
                Author notes
                *To whom correspondence should be addressed. Tel: +49 6221 54 54 362; Fax: +49 6221 54 51 486; Email: robert.russell@ 123456bioquant.uni-heidelberg.de
                Article
                gks398
                10.1093/nar/gks398
                3394340
                22600738
                ee968747-ac43-4572-973b-fce40e98f67e
                © The Author(s) 2012. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 February 2012
                : 11 April 2012
                : 17 April 2012
                Page count
                Pages: 5
                Categories
                Articles

                Genetics
                Genetics

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