Description
Folding@home is a massively distributed computing project that uses biomolecular simulations to investigate the molecular origins of disease and accelerate the discovery of new therapies. Run by the Folding@home Consortium, a worldwide network of research laboratories focusing on a variety of different diseases, Folding@home seeks to address problems in human health on a scale that is infeasible by another other means, sharing the results of these large-scale studies with the research community through peer-reviewed publications and publicly shared datasets. During the COVID-19 epidemic, Folding@home focused its resources on understanding the vulnerabilities in SARS-CoV-2, the virus that causes COVID-19 disease, and working closely with a number of experimental collaborators to accelerate progress toward effective therapies for treating COVID-19 and ending the pandemic. In the process, it created the world's first exascale distributed computing resource, enabling it to generate valuable scientific datasets of unprecedented size. More information about Folding@home's COVID-19 research activities at the Folding@home COVID-19 page. In addition to working directly with experimental collaborators and rapidly sharing new research findings through preprint servers, Folding@home has joined other researchers in committing to rapidly share all COVID-19 research data, and has joined forces with AWS and the Molecular Sciences Software Institute (MolSSI) to share datasets of unprecedented side through the AWS Open Data Registry, indexing these massive datasets via the MolSSI COVID-19 Molecular Structure and Therapeutics Hub. The complete index of all Folding@home datasets can be found here. This repository contains several major datasets from this effort and comprises the single largest collection of molecular simulation data ever released.
Update Frequency
Datasets will be updated periodically as additional simulations are completed.
License
CC0
Documentation
https://github.com/FoldingAtHome/coronavirus
Managed By
Folding@home
See all datasets managed by Folding@home.
Contact
Folding@home
How to Cite
Foldingathome COVID-19 Datasets was accessed on DATE
from https://registry.opendata.aws/foldingathome-covid19.
Usage Examples
Tutorials
Tools & Applications
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SARS-CoV-2 spike RBD with N501Y mutation bound to human ACE2 (953.7 µs) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 COVID Moonshot absolute free energy calculations by The Voelz lab at Temple University
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SARS-CoV-2 main viral protease (Mpro, 3CLPro, nsp5) dimer simulations: A 2.9 ms dataset of the SARS-CoV-2 main viral protease (apo, dimer) in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 main viral protease (Mpro, 3CLPro, nsp5) monomer simulations: A 2.6 ms equilibrium dataset of the SARS-CoV-2 main viral protease (apo, monomer) by The Chodera lab at MSKCC
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SARS-CoV-2 main viral protease (Mpro, 3CLPro, nsp5) monomer simulations: A 6.4 ms dataset of the SARS-CoV-2 main viral protease (apo, monomer) in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 nsp10 dataset: A 6.1 ms dataset of the SARS-CoV-2 nsp10 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 nsp3 macrodomain dataset: An 11 ms dataset of the SARS-CoV-2 nsp3 macrodomain in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 nsp3 pl2pro domain dataset: An 731 µs dataset of the SARS-CoV-2 nsp3 pl2pro domain in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 nsp7 simulations: A 3.7 ms dataset of the SARS-CoV-2 nsp7 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 nsp8 simulations: A 1.8 ms dataset of the SARS-CoV-2 nsp8 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 nsp9 simulations: A 9 ms dataset of the SARS-CoV-2 nsp9 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 RNA polymerase (nsp12, RdRP) dataset: A 3.4 ms dataset of the SARS-CoV-2 nsp12 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 spike protein dataset: A 1.2 ms dataset of the SARS-CoV-2 spike protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
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SARS-CoV-2 spike RBD (with glycosylation) (1.8 ms) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 spike RBD (without glycosylation) (1.9 ms) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 spike RBD bound to human ACE2 receptor (173.8 us): Wild-type and mutant simulations by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 spike RBD bound to monoclonal antibody S2H97 (623.7 us) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 spike RBD bound to monoclonal antibody S309 (1.1 ms) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 spike RBD with P337A mutation bound to monoclonal antibody S309 (907.0 µs) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
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SARS-CoV-2 spike RBD with P337L mutation bound to monoclonal antibody S309 (923.2 µs) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
Publications
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Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity by Emma C. Thomson, Laura E, Rosen, James G. Shepherd, et al.
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SARS-CoV-2 RBD antibodies that maximize breadth and resistance to escape by Tyler N. Starr, Nadine Czudnochowski, Zhuoming Liu, et al.
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SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome by Maxwell I. Zimmerman, Justin R. Porter, Michael D. Ward, Sukrit Singh, Neha Vithani, Artur Meller, Upasana L. Mallimadugula, Catherine E. Kuhn, Jonathan H. Borowsky, View ORCID ProfileRafal P. Wiewiora, Matthew F. D. Hurley, Aoife M Harbison, Carl A Fogarty, Joseph E. Coffland, Elisa Fadda, Vincent A. Voelz, John D. Chodera, Gregory R. Bowman