Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography-based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline-FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC<sub>50</sub>). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC<sub>50</sub>. Further optimization led to analogs with IC<sub>50</sub> values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

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Publication Details

Journal
Science Advances
Published
2025-05-28
DOI
https://doi.org/10.1126/sciadv.ads7187
Citations
17
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
12.90
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article

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

Patrick Riley, Yurii S. Moroz, Brian Goldman, Brian K. Shoichet et al.
17 citations
Science Advances
RNA and protein synthesis mechanisms
12.90
article

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

Patrick Riley, Yurii S. Moroz, Brian Goldman, Brian K. Shoichet, Stefan Gahbauer, Yagmur Umay Doruk, G.J. Correy, Adam R. Renslo, James S. Fraser, Takaya Togo, Dmytro S. Radchenko, Alan Ashworth, Trevor J. Kramer, W. Patrick Walters, Moira M. Rachman, Molly Schmidt, Brian Kelley, Priyadarshini Jaishankar, Maisie GV Stevens
article en
17 citations

Abstract

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography-based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline-FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC<sub>50</sub>). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC<sub>50</sub>. Further optimization led to analogs with IC<sub>50</sub> values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science AdvancesVol. 11(22)
University of California, San Francisco (US), Taras Shevchenko National University of Kyiv (UA), Relay Therapeutics (United States) (US), UCSF Helen Diller Family Comprehensive Cancer Center (US), Enamine (Ukraine) (UA)
Openalex Percentile: Top 1%
RNA and protein synthesis mechanisms
12.90
DOIOpen Access PDFOpenAlex
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