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Nucleic Acids Res. 2019 Nov 12. pii: gkz975. doi: 10.1093/nar/gkz975. [Epub ahead of print]

DisProt: intrinsic protein disorder annotation in 2020.

Author information

1
Department of Biomedical Sciences, University of Padova, Padova 35121, Italy.
2
MTA-ELTE Lendület Bioinformatics Research Group, Department of Biochemistry, Eötvös Loránd University, Budapest 1117, Hungary.
3
Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes - CONICET, Bernal, Buenos Aires B1876BXD, Argentina.
4
Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Biotecnológicas IIBIO, Universidad Nacional de San Martín, San Martín, Buenos Aires, Argentina.
5
Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen DK-2100, Denmark.
6
Department of Biochemistry and Biophysics and Science for Life Laboratory, Stockholm University, Box 1031, Solna 17121, Sweden.
7
Biological Computation & Process Laboratory, Chemical Process & Energy Resources Institute, Centre for Research & Technology Hellas, Thessalonica GR-57500, Greece.
8
Departamento de Fisiología y Biología Molecular y Celular (DFBMC), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.
9
Division of Cancer Biology, The Institute of Cancer Research, Chelsea, London SW3 6BJ, UK.
10
Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade 11001, Serbia.
11
Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, IN 46202, USA.
12
Swiss Institute of Bioinformatics and HES-SO \ HEG, Geneva 1200, Switzerland.
13
Structural Biology Brussels, Vrije Universiteit Brussel (VUB), Brussels 1050, Belgium.
14
VIB-VUB Center for Structural Biology, Flanders Institute for Biotechnology (VIB), Brussels 1050, Belgium.
15
Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest H-1117, Hungary.
16
Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain.
17
Centre de Recherche en Biologie cellulaire de Montpellier (CRBM), UMR 5237 CNRS, Université Montpellier, Montpellier 34293, France.
18
Institut de Biologie Computationnelle(IBC), Montpellier 34095, France.
19
Department of Woman and Child Health, University of Padova, Padova 35127, Italy.
20
Fondazione Istituto di Ricerca Pediatrica (IRP), Città della Speranza, Padova 35127, Italy.
21
Instituto de Biologia Molecular e Celular (IBMC) and Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto 4200-135, Portugal.
22
Bioinformatics Unit. Fundación Instituto Leloir, Ciudad de Buenos Aires C1405BWE, Argentina.
23
Translational Disease Systems Biology, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research University of Copenhagen, Copenhagen DK-2200, Denmark.
24
Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, Nicosia, CY 1678, Cyprus.
25
Interuniversity Institute of Bioinformatics in Brussels (IB2), ULB-VUB, Brussels 1050, Belgium.
26
CNR Institute of Neurosceince, Padova 35121, Italy.

Abstract

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome.

PMID:
31713636
DOI:
10.1093/nar/gkz975

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