6533b7d4fe1ef96bd1263201
RESEARCH PRODUCT
RepeatsDB 2.0: improved annotation, classification, search and visualization of repeat protein structures
Miguel A. Andrade-navarroSilvio C. E. TosattoLayla HirshLayla HirshLisanna PaladinAndrey V. KajavaDamiano Piovesansubject
0301 basic medicineRepetitive Sequences Amino Acid[SDV.BC]Life Sciences [q-bio]/Cellular BiologyBiologyBioinformaticsSearch engineAnnotationStructure-Activity Relationship03 medical and health sciences0302 clinical medicineTandem repeatGeneticsAnimalsHumansDatabase IssueDatabases ProteinComputingMilieux_MISCELLANEOUSRepeat unit030304 developmental biology0303 health sciencesInformation retrievalProteinscomputer.file_formatProtein Data BankVisualizationSchema (genetic algorithms)030104 developmental biologyData qualityCorrigendumcomputerSoftware030217 neurology & neurosurgerydescription
RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ∼5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by an extensive manual validation for >60% of the entries. The updated web interface includes a new search engine for complex queries and a fully re-designed entry page for a better overview of structural data. It is now possible to compare unit positions, together with secondary structure, fold information and Pfam domains. Moreover, a new classification level has been introduced on top of the existing scheme as an independent layer for sequence similarity relationships at 40%, 60% and 90% identity.
year | journal | country | edition | language |
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2017-01-01 | Nucleic Acids Research |