• András Hatos
  • Borbala Hajdu-Soltesz
  • Alexander Miguel Monzon
  • Nicolas Palopoli
  • Lucia Alvarez
  • Burcu Aykac-Fas
  • Claudio Bassot
  • Guillermo Ignacio Benitez
  • Martina Bevilacqua
  • Anastasia Chasapi
  • Lucia Chemes
  • Norman Davey
  • Radoslav Davidovic
  • A Keith Dunker
  • Arne Elofsson
  • Julien Gobeill
  • Govindarajan Sudha
  • Tamas Horvath
  • Valentin Iglesias
  • Andrey V Kajava
  • Orsolya Panna Kovacs
  • John Lamb
  • Matteo Lambrughi
  • Jeremy Leclercq
  • Emmanuela Leonardi
  • Sandra Macedo-Ribeiro
  • Eemiliano Maiani
  • Jose A. Manso
  • Cristina Marino-Buslje
  • Elizabeth Martinez-Perez
  • Bálint Mészáros
  • Ivan Micetic
  • Giovanni Minervini
  • Nikoletta Murvai
  • Marco Necci
  • Cristos Ouzounis
  • Matyas Pajkos
  • Lisanna Paladin
  • Elena Papaleo
  • Emilie Pasche
  • Pedro Jose Barbosa Pereira
  • Vasilis J. Promponas
  • Jordi Pujols
  • Federica Quaglia
  • Patrick Ruch
  • Marco Salvatore
  • Eva Schad
  • Beata Szabo
  • Tamas Szaniszlo
  • Stella Tamana
  • Agnes Tantos
  • Nevena Veljković
  • Salvador Ventura
  • Zsuzsanna Dosztányi
  • Silvio C E Tosatto
  • Damiano Piovesan

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.

Original languageEnglish
Article numbergkz975
JournalNucleic Acids Research
Issue numberD1
Publication statusPublished - 2020

ID: 48116552