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      PoSSuM: a database of similar protein–ligand binding and putative pockets

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          Abstract

          Numerous potential ligand-binding sites are available today, along with hundreds of thousands of known binding sites observed in the PDB. Exhaustive similarity search for such vastly numerous binding site pairs is useful to predict protein functions and to enable rapid screening of target proteins for drug design. Existing databases of ligand-binding sites offer databases of limited scale. For example, SitesBase covers only ∼33 000 known binding sites. Inferring protein function and drug discovery purposes, however, demands a much more comprehensive database including known and putative-binding sites. Using a novel algorithm, we conducted a large-scale all-pairs similarity search for 1.8 million known and potential binding sites in the PDB, and discovered over 14 million similar pairs of binding sites. Here, we present the results as a relational database Pocket Similarity Search using Multiple-sketches (PoSSuM) including all the discovered pairs with annotations of various types. PoSSuM enables rapid exploration of similar binding sites among structures with different global folds as well as similar ones. Moreover, PoSSuM is useful for predicting the binding ligand for unbound structures, which provides important clues for characterizing protein structures with unclear functions. The PoSSuM database is freely available at http://possum.cbrc.jp/PoSSuM/.

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          Most cited references22

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          CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues

          Cavities on a proteins surface as well as specific amino acid positioning within it create the physicochemical properties needed for a protein to perform its function. CASTp () is an online tool that locates and measures pockets and voids on 3D protein structures. This new version of CASTp includes annotated functional information of specific residues on the protein structure. The annotations are derived from the Protein Data Bank (PDB), Swiss-Prot, as well as Online Mendelian Inheritance in Man (OMIM), the latter contains information on the variant single nucleotide polymorphisms (SNPs) that are known to cause disease. These annotated residues are mapped to surface pockets, interior voids or other regions of the PDB structures. We use a semi-global pair-wise sequence alignment method to obtain sequence mapping between entries in Swiss-Prot, OMIM and entries in PDB. The updated CASTp web server can be used to study surface features, functional regions and specific roles of key residues of proteins.
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            Data growth and its impact on the SCOP database: new developments

            The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. The SCOP hierarchy comprises the following levels: Species, Protein, Family, Superfamily, Fold and Class. While keeping the original classification scheme intact, we have changed the production of SCOP in order to cope with a rapid growth of new structural data and to facilitate the discovery of new protein relationships. We describe ongoing developments and new features implemented in SCOP. A new update protocol supports batch classification of new protein structures by their detected relationships at Family and Superfamily levels in contrast to our previous sequential handling of new structural data by release date. We introduce pre-SCOP, a preview of the SCOP developmental version that enables earlier access to the information on new relationships. We also discuss the impact of worldwide Structural Genomics initiatives, which are producing new protein structures at an increasing rate, on the rates of discovery and growth of protein families and superfamilies. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop.
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              The Gene Ontology project in 2008

              (2008)
              The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.
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                Author and article information

                Journal
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2012
                January 2012
                30 November 2011
                30 November 2011
                : 40
                : D1 , Database issue
                : D541-D548
                Affiliations
                1Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, 2Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064 and 3Minato Discrete Structure Manipulation System Project, ERATO, Japan Science and Technology Agency, Sapporo 060-0814, Japan
                Author notes
                *To whom correspondence should be addressed. Tel: +81 3 3599 8080; Fax: +81 3 3599 8081; Email: k-tomii@ 123456aist.go.jp
                Article
                gkr1130
                10.1093/nar/gkr1130
                3245044
                22135290
                e720b6ef-fdb6-409a-8697-c6f204cea6e5
                © The Author(s) 2011. 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
                : 22 August 2011
                : 31 October 2011
                : 8 November 2011
                Page count
                Pages: 8
                Categories
                Articles

                Genetics
                Genetics

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