SARS-CoV2 Docking Dataset
- Rogers, David M. | Oak Ridge National Laboratory
- Glaser, Jens | Oak Ridge National Laboratory
- Agarwal, Rupesh | Oak Ridge National Laboratory
- Vermaas, Josh | Oak Ridge National Laboratory
- Smith, Micholas | Oak Ridge National Laboratory
- Parks, Jerry | Oak Ridge National Laboratory
- Cooper, Connor | Oak Ridge National Laboratory
- Sedova, Ada | Oak Ridge National Laboratory
- Boehm, Swen | Oak Ridge National Laboratory
- Baker, Matthew | Oak Ridge National Laboratory
- Smith, Jeremy | Oak Ridge National Laboratory
Overview
Description
Description: Small-molecule conformations and docking scores for 1.4 billion molecules docked against 6 protein targets from SARS-CoV2: MPro 5R84, MPro 6WQF, NSP15 6WLC, PLPro 7JIR, Spike 6M0J, and a hand-optimized model of the RNA-dependent RNA polymerase. Docking was carried out using the Autodock-GPU program performing 20 independent structure minimizations per dock - saving 3 results per molecule. Scores reported include the Autodock free energy estimate as well as RF3 and VS-DUD-E v2 machine-learned rescoring models. Protein structure files and maps in the format input to Autodock-GPU are included. Literature Ref: Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19, J. Chem. Inf. Model. 2020, 60(12): 5832–5852.
Funding Resources
DOE Contract Number
DE-AC05-00OR22725Originating Research Organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Other Contributing Organizations
50159092,50159094,50445429Sponsoring Organization
Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21);USDOE; ORNL Laboratory Directed Research and Development (LDRD)Project Identifier
32102676Related Resources
- Cites (DOI): https://doi.org/10.1021/acs.jcim.0c01010
- IsSupplementedBy (DOI): https://doi.org/10.13139/OLCF/1650650
- IsSupplementedBy (DOI): https://doi.org/10.13139/OLCF/1657844
- IsSupplementedBy (DOI): https://doi.org/10.13139/OLCF/1657847
Details
DOI
10.13139/OLCF/1783186Release Date
May 27, 2021Dataset
Dataset Type
AS Animations/SimulationsSoftware
python/pandasAcknowledgements
Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
Category
- 36 MATERIALS SCIENCE,
- 59 BASIC BIOLOGICAL SCIENCES,
- 60 APPLIED LIFE SCIENCES
Keywords
- COVID-19,
- SARS CoV-2,
- docking,
- small-molecules