DisProt: Intrinsic protein disorder annotation in 2020

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.Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) of Argentina [PICT-2015/3367, PICT-2017/1924]; Ministry of Education, Science and Technological Development of the Republic of Serbia [ON173001]; Vetenskapsrådet [2016-03798]; Hungarian National Research, Development, and Innovation Office (NKFIH) [FK-128133]; Italian Ministry of Health Young Investigator Grant [GR-2011-02347754]; Ministerio de Economía y Competitividad (MINECO) [BIO2016-78310-R]; ICREA (ICREA-Academia 2015); Fundac¸ão para a Ciência e a Tecnologia (FCT, Portugal); European Regional Development Fund [POCI-01-0145-FEDER-031173, POCI-01-0145-FEDER-029221]; Mexican National Council of Science and Technology (CONACYT) [215503]; Elixir-GR, Action ‘Reinforcement of the Research and Innovation Infrastructure’, Operational Programme ‘Competitiveness, Entrepreneurship and Innovation’ [NSRF 2014-2020]. co-financed by Greece and the European Union (European Regional Development Fund); Hungarian Academy of Sciences [PREMIUM-2017-48]; Carlsberg Distinguished Fellowship [CF18-0314]; Danmarks Grundforskningsfond [DNRF125]; National Research, Development and Innovation Office [K-125340]; Research Foundation Flanders (FWO) [G.0328.16N]; Hungarian Academy of Sciences [LP2014-18]; OTKA [K108798 and K124670]. This project has received funding from the European Union’s Horizon 2020 research and innovation programme [778247]. Funding for open access charge: European Union’s Horizon 2020 research and innovation programme [778247]. Conflict of interest statement. None declared