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4. COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning

Author

Anna Carbery, Annette von Delft, Boris Kovar, Vishwanath Swamy, Ronen Gabizon, Nathan Wright, Charlie Weatherall, Susana Tomasio, Hannah E. Bruce Macdonald, Daniel Zaidmann, Ailsa Powell, P. Gehrtz, Noam Erez, Walter Ward, Vladimir Psenak, Finny S. Varghese, Edward J Griffen, Halina Mikolajek, Sharon Melamed, Emma Cattermole, A. Aimon, Elad Bar-David, Louise Dunnett, Maneesh Pingle, Warren Thompson, Efrat Resnick, William G. Glass, Mark Daniel Calmiano, J. L. Kiappes, Lizbe Koekemoer, Mariana Vaschetto, Andrew Jajack, Nir London, Martin Walsh, Beth MacLean, Charline Giroud, Haim Levy, Anastassia L. Kantsadi, Vladas Oleinikovas, Andrew Thompson, Vincent A. Voelz, Assa Sittner, Tomer Israely, John Spencer, Itai Glinert, Matthew F. D. Hurley, Richard Foster, T.J. Gorrie-Stone, Aarif Shaikh, Gijs J. Overheul, Conor Francis Wild, Michael Fairhead, Benjamin Ian Perry, David Owen, Michelle L. Hill, Peter W. Kenny, Sarma Bvnbs, Galit Cohen, Ralph P. Robinson, Jakir Pinjari, Carina Gileadi, Amir Ben-Shmuel, Shay Weiss, Victor L. Rangel, Matthew C. Robinson, Anthony Tumber, D. Fearon, Jag Paul Heer, Boaz Politi, Nicole Zitzmann, Claire Strain-Damerell, Tika R. Malla, Oleg M. Michurin, Peter K. Eastman, Christopher J. Schofield, Matthew Wittmann, Jin Pan, Eric Jnoff, Shirly Duberstein, Mihaela D. Smilova, Haim Barr, Ronald P. van Rij, Joseph E. Coffland, Garrett M. Morris, Austin Clyde, Khriesto A. Shurrush, Einat B. Vitner, Ruby Pai, Alessandro Contini, St Patrick Reid, Jose Brandao Neto, Lisa Cox, Tatiana Matviiuk, Jiye Shi, Sam Horrell, Ioannis Vakonakis, Aaron Morris, Hadeer Zidane, Juliane Brun, Yfat Yahalom-Ronen, Hadas Tamir, R. Skyner, Tobias John, John D. Chodera, Nir Paran, Alex Dias, Dominic Rufa, Willam McCorkindale, Reut Puni, Hagit Achdout, Rachael Tennant, Holly Foster, Tim Dudgeon, Bruce A. Lefker, Rambabu N. Reddi, Marian V. Gorichko, Frank von Delft, Alpha A. Lee, Milan Cvitkovic, T. Krojer, Demetri Moustakas, Oleg Fedorov, Robert C. Glen, Jason C. Cole, Petra Lukacik, Matteo P. Ferla, Melissa L Bobby, Adam Smalley, Jim Bennett, Melody Jane Morwitzer, and Alice Douangamath

Subjects
Open science, Protease, Computer science, business.industry, Drug discovery, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), medicine.medical_treatment, Crowdsourcing, Machine learning, computer.software_genre, Enzymatic Assays, medicine, Ic50 values, Artificial intelligence, business, Throughput (business), computer
Abstract

Herein we provide a living summary of the data generated during the COVID Moonshot project focused on the development of SARS-CoV-2 main protease (Mpro) inhibitors. Our approach uniquely combines crowdsourced medicinal chemistry insights with high throughput crystallography, exascale computational chemistry infrastructure for simulations, and machine learning in triaging designs and predicting synthetic routes. This manuscript describes our methodologies leading to both covalent and non-covalent inhibitors displaying protease IC50 values under 150 nM and viral inhibition under 5 uM in multiple different viral replication assays. Furthermore, we provide over 200 crystal structures of fragment-like and lead-like molecules in complex with the main protease. Over 1000 synthesized and ordered compounds are also reported with the corresponding activity in Mpro enzymatic assays using two different experimental setups. The data referenced in this document will be continually updated to reflect the current experimental progress of the COVID Moonshot project, and serves as a citable reference for ensuing publications. All of the generated data is open to other researchers who may find it of use.

Published
2020
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