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      MoonDB 2.0: an updated database of extreme multifunctional and moonlighting proteins

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          Abstract

          MoonDB 2.0 ( http://moondb.hb.univ-amu.fr/) is a database of predicted and manually curated extreme multifunctional (EMF) and moonlighting proteins, i.e. proteins that perform multiple unrelated functions. We have previously shown that such proteins can be predicted through the analysis of their molecular interaction subnetworks, their functional annotations and their association to distinct groups of proteins that are involved in unrelated functions. In MoonDB 2.0, we updated the set of human EMF proteins (238 proteins), using the latest functional annotations and protein–protein interaction networks. Furthermore, for the first time, we applied our method to four additional model organisms - mouse, fly, worm and yeast - and identified 54 novel EMF proteins in these species. In addition to novel predictions, this update contains 63 human and yeast proteins that were manually curated from literature, including descriptions of moonlighting functions and associated references. Importantly, MoonDB’s interface was fully redesigned and improved, and its entries are now cross-referenced in the UniProt Knowledgebase (UniProtKB). MoonDB will be updated once a year with the novel EMF candidates calculated from the latest available protein interactions and functional annotations.

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          Moonlighting proteins.

          C Jeffery (1998)
          The idea of one gene--one protein--one function has become too simple because increasing numbers of proteins are found to have two or more different functions. The multiple functions of such moonlighting proteins add another dimension to cellular complexity and benefit cells in several ways. However, cells have had to develop sophisticated mechanisms for switching between the distinct functions of these proteins.
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            Multifunctional proteins revealed by overlapping clustering in protein interaction network

            Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters. Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overlapping clusters and which is, therefore, capable of correct assignment of multifunctional proteins. The principle of OCG is to cover the graph with initial overlapping classes that are iteratively fused into a hierarchy according to an extension of Newman's modularity function. By applying OCG to a human protein–protein interaction network, we show that multifunctional proteins are revealed at the intersection of clusters and demonstrate that the method outperforms other existing methods on simulated graphs and PPI networks. Availability: This software can be downloaded from http://tagc.univ-mrs.fr/welcome/spip.php?rubrique197 Contact: brun@tagc.univ-mrs.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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              A new reference implementation of the PSICQUIC web service

              The Proteomics Standard Initiative Common QUery InterfaCe (PSICQUIC) specification was created by the Human Proteome Organization Proteomics Standards Initiative (HUPO-PSI) to enable computational access to molecular-interaction data resources by means of a standard Web Service and query language. Currently providing >150 million binary interaction evidences from 28 servers globally, the PSICQUIC interface allows the concurrent search of multiple molecular-interaction information resources using a single query. Here, we present an extension of the PSICQUIC specification (version 1.3), which has been released to be compliant with the enhanced standards in molecular interactions. The new release also includes a new reference implementation of the PSICQUIC server available to the data providers. It offers augmented web service capabilities and improves the user experience. PSICQUIC has been running for almost 5 years, with a user base growing from only 4 data providers to 28 (April 2013) allowing access to 151 310 109 binary interactions. The power of this web service is shown in PSICQUIC View web application, an example of how to simultaneously query, browse and download results from the different PSICQUIC servers. This application is free and open to all users with no login requirement (http://www.ebi.ac.uk/Tools/webservices/psicquic/view/main.xhtml).
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                29 October 2018
                29 October 2018
                : 47
                : Database issue , Database issue
                : D398-D402
                Affiliations
                [1 ]Aix-Marseille Univ, INSERM, TAGC, UMR_S1090, Marseille, France
                [2 ]The European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus CB10 1SD, UK
                [3 ]CNRS, Marseille, France
                Author notes
                To whom correspondence should be addressed. Tel: +33 491828712; Email: christine-g.brun@ 123456inserm.fr

                Present address: Galadriel Briere, Bordeaux Sciences Agro, 33175 Gradignan, France.

                Author information
                http://orcid.org/0000-0002-5563-6765
                Article
                gky1039
                10.1093/nar/gky1039
                6323955
                30371819
                1b95947f-b648-4917-bb29-0c23b9bdb12e
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 17 October 2018
                : 17 September 2018
                : 09 August 2018
                Page count
                Pages: 5
                Funding
                Funded by: Aix-Marseille University 10.13039/100007586
                Categories
                Database Issue

                Genetics
                Genetics

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