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

Abstract 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).This work was supported by the Center of Excellence for HPC H2020 European Commission; ‘BioExcel Centre of Excellence for Computational Biomolecular Research’ (BioExcel-2 [823830]; BioExcel-3 [European Union: 101093290; Ministerio de Ciencia e Innovación: PCI2022-134976-2]); Spanish Ministry of Science [RTI2018-096704-B-100, PID2021-122478NB-I00]; Instituto de Salud Carlos III–Instituto Nacional de Bioinformatica, Fondo Europeo de Desarrollo Regional [ISCIII PT 17/0009/0007]; European Regional Development Fund, ERFD Operative Program for Catalunya, the Catalan Government AGAUR [SGR2021 00863]; European Union ‘MDDB: Molecular Dynamics Data Bank. The European Repository for Biosimulation Data’ [101094651] and the EU Human Brain Flagship program. We acknowledge the use of Fenix Infrastructure resources, which are partially funded from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858. IRB Barcelona is the recipient of a Severo Ochoa Award of Excellence from the Spanish Ministerio de Asuntos Económicos y Transformación Digital (MINECO). Modesto Orozco is an ICREA Academy scholar. Data for the project is kept on BSC disks thanks to the Red Española de Supercomputación (RES) DATA [DATA-2020-1-0037] project.Peer ReviewedPostprint (published version