A new paradigm for molecular dynamics databases: the COVID-19 database, the legacy of a titanic community effort.


Journal

Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011

Informations de publication

Date de publication:
11 Nov 2023
Historique:
accepted: 17 10 2023
revised: 16 10 2023
received: 14 08 2023
medline: 13 11 2023
pubmed: 13 11 2023
entrez: 12 11 2023
Statut: aheadofprint

Résumé

Molecular dynamics (MD) simulations are keeping computers busy around the world, generating a huge amount of data that is typically not open to the scientific community. Pioneering efforts to ensure the safety and reusability of MD data have been based on the use of simple databases providing a limited set of standard analyses on single-short trajectories. Despite their value, these databases do not offer a true solution for the current community of MD users, who want a flexible analysis pipeline and the possibility to address huge non-Markovian ensembles of large systems. Here we present a new paradigm for MD databases, resilient to large systems and long trajectories, and designed to be compatible with modern MD simulations. The data are offered to the community through a web-based graphical user interface (GUI), implemented with state-of-the-art technology, which incorporates system-specific analysis designed by the trajectory providers. A REST API and associated Jupyter Notebooks are integrated into the platform, allowing fully customized meta-analysis by final users. The new technology is illustrated using a collection of trajectories obtained by the community in the context of the effort to fight the COVID-19 pandemic. The server is accessible at https://bioexcel-cv19.bsc.es/#/. It is free and open to all users and there are no login requirements. It is also integrated into the simulations section of the BioExcel-MolSSI COVID-19 Molecular Structure and Therapeutics Hub: https://covid.molssi.org/simulations/ and is part of the MDDB effort (https://mddbr.eu).

Identifiants

pubmed: 37953362
pii: 7416383
doi: 10.1093/nar/gkad991
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : European Union
ID : 101094651
Organisme : BioExcel Centre of Excellence for Computational Biomolecular Research
ID : 823830

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.

Auteurs

Daniel Beltrán (D)

Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain.

Adam Hospital (A)

Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain.

Josep Lluís Gelpí (JL)

Department of Biochemistry and Biomedicine. University of Barcelona, Barcelona, Spain.
Barcelona Supercomputing Center (BSC), Barcelona, Spain.

Modesto Orozco (M)

Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain.
Department of Biochemistry and Biomedicine. University of Barcelona, Barcelona, Spain.

Classifications MeSH