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DOE OSTI · 1783186

SARS-CoV2 Docking Dataset

Rogers, David M.·Glaser, Jens·Agarwal, Rupesh·Vermaas, Josh·Smith, Micholas·Parks, Jerry·Cooper, Connor·Sedova, Ada·Boehm, Swen·Baker, Matthew·Smith, Jeremy
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Abstract

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.

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36 MATERIALS SCIENCE59 BASIC BIOLOGICAL SCIENCES60 APPLIED LIFE SCIENCESCOVID-19dockingSARS CoV-2small-molecules

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Rogers, David M., Glaser, Jens, Agarwal, Rupesh, Vermaas, Josh, Smith, Micholas, Parks, Jerry, Cooper, Connor, Sedova, Ada, Boehm, Swen, Baker, Matthew, Smith, Jeremy. 2021-05-27. SARS-CoV2 Docking Dataset. https://doi.org/10.13139/olcf%2F1783186

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