GPCRmd uncovers the dynamics of the 3D-GPCRome

Research output: Contribution to journalJournal articlepeer-review

  • Ismael Rodríguez-Espigares
  • Mariona Torrens-Fontanals
  • Johanna K. S. Tiemann
  • David Aranda-García
  • Juan Manuel Ramírez-Anguita
  • Tomasz Maciej Stepniewski
  • Nathalie Worp
  • Alejandro Varela-Rial
  • Adrián Morales-Pastor
  • Brian Medel-Lacruz
  • Eduardo Mayol
  • Toni Giorgino
  • Jens Carlsson
  • Xavier Deupi
  • Slawomir Filipek
  • Marta Filizola
  • José Carlos Gómez-Tamayo
  • Angel Gonzalez
  • Hugo Gutiérrez-de-Terán
  • Mireia Jiménez-Rosés
  • Willem Jespers
  • Jon Kapla
  • George Khelashvili
  • Peter Kolb
  • Dorota Latek
  • Maria Marti-Solano
  • Pierre Matricon
  • Minos-Timotheos Matsoukas
  • Przemyslaw Miszta
  • Mireia Olivella
  • Laura Perez-Benito
  • Davide Provasi
  • Santiago Ríos
  • Iván R. Torrecillas
  • Jessica Sallander
  • Agnieszka Sztyler
  • Silvana Vasile
  • Harel Weinstein
  • Ulrich Zachariae
  • Peter W. Hildebrand
  • Gianni De Fabritiis
  • Ferran Sanz
  • Arnau Cordomi
  • Ramon Guixà-González
  • Jana Selent

G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.

Original languageEnglish
JournalNature Methods
Volume17
Issue number8
Pages (from-to)777-787
ISSN1548-7091
DOIs
Publication statusPublished - 2020

Bibliographical note

Correction to: Nature Methods https://doi.org/10.1038/s41592-020-0884-y, published online 13 July 2020.

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