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      Is Open Access

      The Universal Protein Resource (UniProt)

      research-article
      The UniProt Consortium 1 , 2 , 3
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          The ability to store and interconnect all available information on proteins is crucial to modern biological research. Accordingly, the Universal Protein Resource (UniProt) plays an increasingly important role by providing a stable, comprehensive, freely accessible central resource on protein sequences and functional annotation. UniProt is produced by the UniProt Consortium, formed in 2002 by the European Bioinformatics Institute (EBI), the Protein Information Resource (PIR) and the Swiss Institute of Bioinformatics (SIB). The core activities include manual curation of protein sequences assisted by computational analysis, sequence archiving, development of a user-friendly UniProt web site and the provision of additional value-added information through cross-references to other databases. UniProt is comprised of three major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase and the UniProt Reference Clusters. An additional component consisting of metagenomic and environmental sequences has recently been added to UniProt to ensure availability of such sequences in a timely fashion. UniProt is updated and distributed on a bi-weekly basis and can be accessed online for searches or download at http://www.uniprot.org.

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          Current views on scorpion toxins specific for K+-channels.

          Much of our knowledge on K+-channels was elucidated using specific peptide ligands isolated from a number of venomous organisms. Recently, this field received a strong support and increased interest due to the solution of the three-dimensional structure of a couple of K+-channels. At the same time, several new subfamilies of specific toxins for K+-channels were isolated from scorpion venoms, enhancing the availability and diversity of such useful molecular tools. It opened new lines of research for the better understanding of K+-channel biophysics and pharmacology. In this review, we listed 120 amino acid sequences of peptides isolated from scorpion venoms. They were demonstrated or assumed to be specific for K+-channels. These sequences were aligned and used to generate a rooted phylogenetic tree. The evolutionary tree indicates that several clusters of divergent peptides show preference for specific subtypes of channels. The three-dimensional structures of representative examples of these peptides were drawn and analysed concerning the molecular fitness of their interactions with the channel targets. Four different interacting modes were identified to exist between scorpion toxins and the various subtypes of K+-channels. Copyright 2004 Elsevier Ltd.
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            UniProt archive.

            UniProt Archive (UniParc) is the most comprehensive, non-redundant protein sequence database available. Its protein sequences are retrieved from predominant, publicly accessible resources. All new and updated protein sequences are collected and loaded daily into UniParc for full coverage. To avoid redundancy, each unique sequence is stored only once with a stable protein identifier, which can be used later in UniParc to identify the same protein in all source databases. When proteins are loaded into the database, database cross-references are created to link them to the origins of the sequences. As a result, performing a sequence search against UniParc is equivalent to performing the same search against all databases cross-referenced by UniParc. UniParc contains only protein sequences and database cross-references; all other information must be retrieved from the source databases.
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              Automated annotation of microbial proteomes in SWISS-PROT.

              Large-scale sequencing of prokaryotic genomes demands the automation of certain annotation tasks currently manually performed in the production of the SWISS-PROT protein knowledgebase. The HAMAP project, or 'High-quality Automated and Manual Annotation of microbial Proteomes', aims to integrate manual and automatic annotation methods in order to enhance the speed of the curation process while preserving the quality of the database annotation. Automatic annotation is only applied to entries that belong to manually defined orthologous families and to entries with no identifiable similarities (ORFans). Many checks are enforced in order to prevent the propagation of wrong annotation and to spot problematic cases, which are channelled to manual curation. The results of this annotation are integrated in SWISS-PROT, and a website is provided at http://www.expasy.org/sprot/hamap/.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2007
                16 November 2006
                16 November 2006
                : 35
                : Database issue
                : D193-D197
                Affiliations
                1Protein Information Resource, Georgetown University Medical Center, 3300 Whitehaven St. NW, Suite 1200 Washington, DC 20007, USA
                2The EMBL Outstation, The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD, UK
                3Swiss Institute of Bioinformatics, Centre Medical Universitaire 1 rue Michel Servet 1211 Geneva 4, Switzerland
                Author notes
                To whom correspondence should be addressed to Rolf Apweiler. Tel: +44 1223 494435; Fax: +44 1223 494468; Email: rolf.apweiler@ 123456ebi.ac.uk

                The UniProt Consortium: Amos Bairoch, Lydie Bougueleret, Severine Altairac, Valeria Amendolia, Andrea Auchincloss, Ghislaine Argoud Puy, Kristian Axelsen, Delphine Baratin, Marie-Claude Blatter, Brigitte Boeckmann, Laurent Bollondi, Emmanuel Boutet, Silvia Braconi Quintaje, Lionel Breuza, Alan Bridge, Edouard deCastro, Danielle Coral, Elisabeth Coudert, Isabelle Cusin, Pavel Dobrokhotov, Dolnide Dornevil, Severine Duvaud, Anne Estreicher, Livia Famiglietti, Marc Feuermann, Sebastian Gehant, Nathalie Farriol-Mathis, Serenella Ferro, Elisabeth Gasteiger, Alain Gateau, Vivienne Gerritsen, Arnaud Gos, Nadine Gruaz-Gumowski, Ursula Hinz, Chantal Hulo, Nicolas Hulo, Vassilios Ioannidis, Ivan Ivanyi, Janet James, Eric Jain, Silvia Jimenez, Florence Jungo, Vivien Junker, Guillaume Keller, Corinne Lachaize, Lydie Lane-Guermonprez, Petra Langendijk-Genevaux, Vicente Lara, Philippe Lemercier, Virginie Le Saux, Damien Lieberherr, Tania de Oliveira Lima, Veronique Mangold, Xavier Martin, Karine Michoud, Madelaine Moinat, Cristiano Moreira, Anne Morgat, Marisa Nicolas, Shoko Ohji, Salvo Paesano, Ivo Pedruzzi, David Perret, Isabelle Phan, Sandrine Pilbout, Violaine Pillet, Sylvain Poux, Nicole Redaschi, Sorogini Reynaud, Catherine Rivoire, Bernd Roechert, Claudia Sapsezian, Michel Schneider, Christian Sigrist, Mauricio da Silva, Karin Sonesson, Andre Stutz, Shyamala Sundaram, Michael Tognolli, Laure Verbregue, Anne-Lise Veuthey, Claudia Vitorello and Lina Yip at the Swiss Institute of Bioinformatics (SIB) and the Medical Biochemistry Department of the University of Geneva; Rolf Apweiler, Yasmin Alam-Faruque, Daniel Barrell, Lawrence Bower, Paul Browne, Wei Mun Chan, Louise Daugherty, Emilio Salazar Donate, Ruth Eberhardt, Alexander Fedotov, Rebecca Foulger, Gill Fraser, Gabriella Frigerio, John Garavelli, Renato Golin, Alan Horne, Julius Jacobsen, Michael Kleen, Paul Kersey, Ernst Kretschmann, Kati Laiho, Rasko Leinonen, Duncan Legge, Michele Magrane, Maria Jesus Martin, Patricia Monteiro, Claire O'Donovan, Sandra Orchard, John O'Rourke, Samuel Patient, Manuela Pruess, Andrey Sitnov, Nataliya Sklyar, Eleanor Whitfield, Daniela Wieser, Quan Lin, Mark Rynbeek, Giuseppe di Martino, Mike Donnelly and Pieter van Rensburg at the European Bioinformatics Institute (EBI). Cathy Wu, Cecilia Arighi, Leslie Arminski, Winona Barker, Yongxing Chen, Sehee Chung, Christina Fang, Vincent Hermoso, Zhang-Zhi Hu, Hsing-Kuo Hua, Hongzhan Huang, Robel Kahsay, Raja Mazumder, Peter McGarvey, Darren Natale, Anastasia Nikolskaya, Natalia Petrova, Baris Suzek, Sona Vasudevan, C. R. Vinayaka, Lai Su Yeh, Xin Yuan and Jian Zhang at the Protein Information Resource (PIR)

                The authors wish it to be know that, in their opinion, all authors should be regarded as joint First Authors

                Article
                10.1093/nar/gkl929
                1669721
                17142230
                347107a4-b580-4704-b3e8-47c51389b593
                © 2006 The Author(s)

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 September 2006
                : 12 October 2006
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                Genetics
                Genetics

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