SARS-CoV2 Docking Dataset
- ORNL-OLCF
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): 5832â5852.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE; ORNL Laboratory Directed Research and Development (LDRD)
- Contributing Organization:
- 50159092,50159094,50445429
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1783186
- Country of Publication:
- United States
- Language:
- English
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