Dataset for Automated Discovery of Noncovalent Inhibitors of SARS-CoV-2 Main Protease by Consensus Deep Docking of 40 Billion Small Molecules

Repository for computational and experimental data resulting for a deep learning-accelerated, structure-based virtual screening campaign of 40 billion small molecules against the SARS-CoV-2 main protease (Mpro). The repository contains ligand structures used for pharmacophore generation, docking poses of experimentally confirmed active inhibitors and docking grid, raw experimental data for determination of half-maximal inhibitory concentration (IC50), and computational data from the virtual screening and filtering procedure as well as related analysis scripts. Refer to the article "Automated Discovery of Noncovalent Inhibitors of SARS-CoV-2 Main Protease by Consensus Deep Docking of 40 Billion Small Molecules" published in Chemical Science for more information.