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Eric Fagerberg

Visiting research fellow

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PED in 2021 : A major update of the protein ensemble database for intrinsically disordered proteins

Author

  • Tamas Lazar
  • Elizabeth Martínez-Pérez
  • Federica Quaglia
  • András Hatos
  • Lucía B. Chemes
  • Javier A. Iserte
  • Nicolás A. Méndez
  • Nicolás A. Garrone
  • Tadeo E. Saldaño
  • Julia Marchetti
  • Ana Julia Velez Rueda
  • Pau Bernadó
  • Martin Blackledge
  • Tiago N. Cordeiro
  • Eric Fagerberg
  • Julie D. Forman-Kay
  • Maria S. Fornasari
  • Toby J. Gibson
  • Gregory Neal W. Gomes
  • Claudiu C. Gradinaru
  • Teresa Head-Gordon
  • Malene Ringkjøbing Jensen
  • Edward A. Lemke
  • Sonia Longhi
  • Cristina Marino-Buslje
  • Giovanni Minervini
  • Tanja Mittag
  • Alexander Miguel Monzon
  • Rohit V. Pappu
  • Gustavo Parisi
  • Sylvie Ricard-Blum
  • Kiersten M. Ruff
  • Edoardo Salladini
  • Marie Skepö
  • Dmitri Svergun
  • Sylvain D. Vallet
  • Mihaly Varadi
  • Peter Tompa
  • Silvio C.E. Tosatto
  • Damiano Piovesan
Show all

Summary, in English

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Department/s

  • Computational Chemistry
  • LINXS - Institute of advanced Neutron and X-ray Science
  • eSSENCE: The e-Science Collaboration

Publishing year

2021-01-08

Language

English

Pages

404-411

Publication/Series

Nucleic Acids Research

Volume

49

Issue

D1

Document type

Journal article

Publisher

Oxford University Press

Topic

  • Theoretical Chemistry (including Computational Chemistry)

Status

Published

ISBN/ISSN/Other

  • ISSN: 0305-1048