SARS-CoV2 Docking Dataset
10.13139/OLCF/1783186Description: 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.
Published: 2021-05-27 10:57:05 Download DatasetDataset Properties
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Authors |
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Project Identifier | 32102676 |
Dataset Type | AS Animations/Simulations |
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Software Needed | python/pandas |
Originating Organizations | Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) |
Sponsoring Organizations | Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21);USDOE; ORNL Laboratory Directed Research and Development (LDRD) |
Other Contributing Organizations | 50159092,50159094,50445429 |
DOE Contract | DE-AC05-00OR22725 |
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Acknowledgements
Papers using this dataset are requested to include the following text in their acknowledgements:
*Support for 10.13139/OLCF/1783186 is provided by the U.S. Department of Energy, project 32102676 under Contract DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.