Foldingathome COVID-19 Datasets

Stream data with DDA:

from dagshub.streaming import DagsHubFilesystem

fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/foldingathome-covid19-dataset")

fs.listdir("s3://fah-public-data-covid19-cryptic-pockets")

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.

Contact:

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.

Managed By:

Folding@home

Resources:

1. resource:

   • Description: Simulations of SARS-CoV-2 and associated host proteins, with emphasis on discovering druggable cryptic pockets, documented at the MolSSI COVID Hub.
   • ARN: arn:aws:s3:::fah-public-data-covid19-cryptic-pockets
   • Region: us-east-2
   • Type: S3 Bucket

2. resource:

   • Description: Simulations of SARS-CoV-2 and associated host proteins relevant to neutralization by therapeutic antibodies, documented at the MolSSI COVID Hub.
   • ARN: arn:aws:s3:::fah-public-data-covid19-antibodies
   • Region: us-east-2
   • Type: S3 Bucket

3. resource:

   • Description: Absolute free energy calculations of small molecules from the COVID Moonshot, documented at the MolSSI COVID Hub
   • ARN: arn:aws:s3:::fah-public-data-covid19-absolute-free-energy
   • Region: us-east-2
   • Type: S3 Bucket

4. resource:

   • Description: Simulations of target proteins and bound small molecules from the COVID Moonshot, documented at the MolSSI COVID Hub
   • ARN: arn:aws:s3:::fah-public-data-covid19-moonshot-dynamics
   • Region: us-east-2
   • Type: S3 Bucket

Tags:

alchemical free energy calculations, aws-pds, biomolecular modeling, coronavirus, COVID-19, foldingathome, health, life sciences, molecular dynamics, protein, SARS-CoV-2, simulations, structural biology

Tutorials:

1. tutorial:
   • Title: Folding@home COVID-19 efforts
   • URL: https://github.com/FoldingAtHome/coronavirus/blob/master/README.md
   • AuthorName: Folding@home Consortium

Tools & Applications:

1. tools & applications:

   • Title: 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)
   • URL: https://covid.molssi.org//simulations/#foldinghome-sars-cov-2-main-protease-apo-monomer-simulations-3clpro-3clpro-protease-activity
   • AuthorName: The Chodera lab at MSKCC
   • AuthorURL: https://choderalab.org

2. tools & applications:

   • Title: SARS-CoV-2 COVID Moonshot absolute free energy calculations
   • URL: https://covid.molssi.org//simulations/#foldinghome-expanded-ensemble-absolute-free-energy-calculations-of-potential-small-molecule-inhibitors-of-the-sars-cov-2-main-protease-from-the-covid-moonshot-3clpro-3clpro-protease-activity
   • AuthorName: The Voelz lab at Temple University
   • AuthorURL: http://www.voelzlab.org/

3. tools & applications:

   • Title: SARS-CoV-2 spike protein dataset: A 1.2 ms dataset of the SARS-CoV-2 spike protein in search of cryptic pockets
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-protein-spike-spike-binding
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

4. tools & applications:

   • Title: SARS-CoV-2 nsp10 dataset: A 6.1 ms dataset of the SARS-CoV-2 nsp10 protein in search of cryptic pockets
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp10-nsp10-nil
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

5. tools & applications:

   • Title: 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
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp12-rdrp-nil
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

6. tools & applications:

   • Title: SARS-CoV-2 nsp3 macrodomain dataset: An 11 ms dataset of the SARS-CoV-2 nsp3 macrodomain in search of cryptic pockets
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp3-macrodomain-macrodomain-host-immune-response
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

7. tools & applications:

   • Title: SARS-CoV-2 nsp3 pl2pro domain dataset: An 731 µs dataset of the SARS-CoV-2 nsp3 pl2pro domain in search of cryptic pockets
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp3-pl2pro-domain-plpro-plpro-protease-activity
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

8. tools & applications:

   • Title: 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
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp5-3clpro-3clpro-protease-activity
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

9. tools & applications:

   • Title: 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
   • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp5-3clpro-3clpro-protease-activity
   • AuthorName: The Bowman lab at Washington University in St. Louis
   • AuthorURL: https://bowmanlab.biochem.wustl.edu

10. tools & applications:

    • Title: SARS-CoV-2 nsp7 simulations: A 3.7 ms dataset of the SARS-CoV-2 nsp7 protein in search of cryptic pockets
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp7-nsp7-nil
    • AuthorName: The Bowman lab at Washington University in St. Louis
    • AuthorURL: https://bowmanlab.biochem.wustl.edu

11. tools & applications:

    • Title: SARS-CoV-2 nsp8 simulations: A 1.8 ms dataset of the SARS-CoV-2 nsp8 protein in search of cryptic pockets
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp8-nsp8-nil
    • AuthorName: The Bowman lab at Washington University in St. Louis
    • AuthorURL: https://bowmanlab.biochem.wustl.edu

12. tools & applications:

    • Title: SARS-CoV-2 nsp9 simulations: A 9 ms dataset of the SARS-CoV-2 nsp9 protein in search of cryptic pockets
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-nsp9-nsp9-nil
    • AuthorName: The Bowman lab at Washington University in St. Louis
    • AuthorURL: https://bowmanlab.biochem.wustl.edu

13. tools & applications:

    • Title: SARS-CoV-2 spike RBD bound to human ACE2 receptor (173.8 us): Wild-type and mutant simulations
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-bound-to-human-ace2
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

14. tools & applications:

    • Title: SARS-CoV-2 spike RBD bound to monoclonal antibody S309 (1.1 ms)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-bound-to-monoclonal-antibody-s309
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

15. tools & applications:

    • Title: SARS-CoV-2 spike RBD with P337L mutation bound to monoclonal antibody S309 (923.2 µs)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-with-p337l-mutation-bound-to-monoclonal-antibody-s309
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

16. tools & applications:

    • Title: SARS-CoV-2 spike RBD with P337A mutation bound to monoclonal antibody S309 (907.0 µs)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-with-p337a-mutation-bound-to-monoclonal-antibody-s309
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

17. tools & applications:

    • Title: SARS-CoV-2 spike RBD bound to monoclonal antibody S2H97 (623.7 us)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-bound-to-monoclonal-antibody-s2h97
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

18. tools & applications:

    • Title: SARS-CoV-2 spike RBD (without glycosylation) (1.9 ms)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-apo-sars-cov-2-spike-rbd-without-glycosylation
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

19. tools & applications:

    • Title: SARS-CoV-2 spike RBD (with glycosylation) (1.8 ms)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-apo-sars-cov-2-spike-rbd-with-glycosylation
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

20. tools & applications:

    • Title: SARS-CoV-2 spike RBD with N501Y mutation bound to human ACE2 (953.7 µs)
    • URL: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-with-n501y-mutation-bound-to-human-ace2
    • AuthorName: The Chodera lab at the Memorial Sloan Kettering Cancer Center
    • AuthorURL: https://choderalab.org

Publication:

1. publication:

   • Title: SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome
   • URL: https://doi.org/10.1101/2020.06.27.175430
   • AuthorName: 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

2. publication:

   • Title: Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity
   • URL: https://doi.org/10.1016/j.cell.2021.01.037
   • AuthorName: Emma C. Thomson, Laura E, Rosen, James G. Shepherd, et al.

3. publication:

   • Title: SARS-CoV-2 RBD antibodies that maximize breadth and resistance to escape
   • URL: https://doi.org/10.1038/s41586-021-03807-6
   • AuthorName: Tyler N. Starr, Nadine Czudnochowski, Zhuoming Liu, et al.