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      SMART: recent updates, new developments and status in 2015

      research-article
      Author(s): 1 , 2 , 2 , *
      Publication date (Electronic):
      Journal: Nucleic Acids Research
      Publisher: Oxford University Press

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          Abstract

          SMART (Simple Modular Architecture Research Tool) is a web resource ( http://smart.embl.de/) providing simple identification and extensive annotation of protein domains and the exploration of protein domain architectures. In the current version, SMART contains manually curated models for more than 1200 protein domains, with ∼200 new models since our last update article. The underlying protein databases were synchronized with UniProt, Ensembl and STRING, bringing the total number of annotated domains and other protein features above 100 million. SMART's ‘Genomic’ mode, which annotates proteins from completely sequenced genomes was greatly expanded and now includes 2031 species, compared to 1133 in the previous release. SMART analysis results pages have been completely redesigned and include links to several new information sources. A new, vector-based display engine has been developed for protein schematics in SMART, which can also be exported as high-resolution bitmap images for easy inclusion into other documents. Taxonomic tree displays in SMART have been significantly improved, and can be easily navigated using the integrated search engine.

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          SMART, a simple modular architecture research tool: identification of signaling domains.

          J. Schultz, F Milpetz, P. Bork … (1998)
          Accurate multiple alignments of 86 domains that occur in signaling proteins have been constructed and used to provide a Web-based tool (SMART: simple modular architecture research tool) that allows rapid identification and annotation of signaling domain sequences. The majority of signaling proteins are multidomain in character with a considerable variety of domain combinations known. Comparison with established databases showed that 25% of our domain set could not be deduced from SwissProt and 41% could not be annotated by Pfam. SMART is able to determine the modular architectures of single sequences or genomes; application to the entire yeast genome revealed that at least 6.7% of its genes contain one or more signaling domains, approximately 350 greater than previously annotated. The process of constructing SMART predicted (i) novel domain homologues in unexpected locations such as band 4.1-homologous domains in focal adhesion kinases; (ii) previously unknown domain families, including a citron-homology domain; (iii) putative functions of domain families after identification of additional family members, for example, a ubiquitin-binding role for ubiquitin-associated domains (UBA); (iv) cellular roles for proteins, such predicted DEATH domains in netrin receptors further implicating these molecules in axonal guidance; (v) signaling domains in known disease genes such as SPRY domains in both marenostrin/pyrin and Midline 1; (vi) domains in unexpected phylogenetic contexts such as diacylglycerol kinase homologues in yeast and bacteria; and (vii) likely protein misclassifications exemplified by a predicted pleckstrin homology domain in a Candida albicans protein, previously described as an integrin.
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            Activities at the Universal Protein Resource (UniProt)

            emmanuel boutet, Claire O'Donovan (2014)
            The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation. It integrates, interprets and standardizes data from literature and numerous resources to achieve the most comprehensive catalog possible of protein information. The central activities are the biocuration of the UniProt Knowledgebase and the dissemination of these data through our Web site and web services. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.
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              Hidden Markov models in computational biology. Applications to protein modeling.

              A. Krogh, M. Brown, I. S. Mian … (1994)
              Hidden Markov Models (HMMs) are applied to the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated on the globin family, the protein kinase catalytic domain, and the EF-hand calcium binding motif. In each case the parameters of an HMM are estimated from a training set of unaligned sequences. After the HMM is built, it is used to obtain a multiple alignment of all the training sequences. It is also used to search the SWISS-PROT 22 database for other sequences that are members of the given protein family, or contain the given domain. The HMM produces multiple alignments of good quality that agree closely with the alignments produced by programs that incorporate three-dimensional structural information. When employed in discrimination tests (by examining how closely the sequences in a database fit the globin, kinase and EF-hand HMMs), the HMM is able to distinguish members of these families from non-members with a high degree of accuracy. Both the HMM and PROFILESEARCH (a technique used to search for relationships between a protein sequence and multiply aligned sequences) perform better in these tests than PROSITE (a dictionary of sites and patterns in proteins). The HMM appears to have a slight advantage over PROFILESEARCH in terms of lower rates of false negatives and false positives, even though the HMM is trained using only unaligned sequences, whereas PROFILESEARCH requires aligned training sequences. Our results suggest the presence of an EF-hand calcium binding motif in a highly conserved and evolutionary preserved putative intracellular region of 155 residues in the alpha-1 subunit of L-type calcium channels which play an important role in excitation-contraction coupling. This region has been suggested to contain the functional domains that are typical or essential for all L-type calcium channels regardless of whether they couple to ryanodine receptors, conduct ions or both.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (hwp): nar
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): 28 January 2015
                Publication date (Electronic): 09 October 2014
                Publication date PMC-release: 09 October 2014
                Volume: 43
                Issue: Database issue , Database issue
                Pages: D257-D260
                Affiliations
                [1 ]Biobyte solutions GmbH, Bothestr 142, 69126 Heidelberg, Germany
                [2 ]EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +49 6221 387 8526; Fax: +49 6221 387 517; Email: bork@ 123456embl.de
                Article
                DOI: 10.1093/nar/gku949
                PMC ID: 4384020
                PubMed ID: 25300481
                SO-VID: d3e1e49e-c8a0-406d-bed8-7aa59a0bfa18
                Copyright © © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date accepted : 29 September 2014
                Date received : 13 September 2014
                Page count
                Pages: 4
                Categories
                Subject: Database Issue
                Custom metadata
                cover-date 28 January 2015

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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