tetano
Editor, Senior Moderator
Sci Adv
. 2025 May 30;11(22):eads7187.
doi: 10.1126/sciadv.ads7187. Epub 2025 May 28. Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning
Galen J Correy[SUP] 1 [/SUP], Moira M Rachman[SUP] 2 [/SUP], Takaya Togo[SUP] 2 [/SUP], Stefan Gahbauer[SUP] 2 [/SUP], Yagmur U Doruk[SUP] 3 [/SUP], Maisie G V Stevens[SUP] 3 [/SUP], Priyadarshini Jaishankar[SUP] 2 [/SUP], Brian Kelley[SUP] 4 [/SUP], Brian Goldman[SUP] 4 [/SUP], Molly Schmidt[SUP] 4 [/SUP], Trevor Kramer[SUP] 4 [/SUP], Dmytro S Radchenko[SUP] 5 [/SUP], Yurii S Moroz[SUP] 5 6 7 [/SUP], Alan Ashworth[SUP] 3 [/SUP], Patrick Riley[SUP] 4 [/SUP], Brian K Shoichet[SUP] 2 [/SUP], Adam R Renslo[SUP] 2 [/SUP], W Patrick Walters[SUP] 4 [/SUP], James S Fraser[SUP] 1 [/SUP]
Affiliations
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.
. 2025 May 30;11(22):eads7187.
doi: 10.1126/sciadv.ads7187. Epub 2025 May 28. Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning
Galen J Correy[SUP] 1 [/SUP], Moira M Rachman[SUP] 2 [/SUP], Takaya Togo[SUP] 2 [/SUP], Stefan Gahbauer[SUP] 2 [/SUP], Yagmur U Doruk[SUP] 3 [/SUP], Maisie G V Stevens[SUP] 3 [/SUP], Priyadarshini Jaishankar[SUP] 2 [/SUP], Brian Kelley[SUP] 4 [/SUP], Brian Goldman[SUP] 4 [/SUP], Molly Schmidt[SUP] 4 [/SUP], Trevor Kramer[SUP] 4 [/SUP], Dmytro S Radchenko[SUP] 5 [/SUP], Yurii S Moroz[SUP] 5 6 7 [/SUP], Alan Ashworth[SUP] 3 [/SUP], Patrick Riley[SUP] 4 [/SUP], Brian K Shoichet[SUP] 2 [/SUP], Adam R Renslo[SUP] 2 [/SUP], W Patrick Walters[SUP] 4 [/SUP], James S Fraser[SUP] 1 [/SUP]
Affiliations
- PMID: 40435250
- PMCID: PMC12118597
- DOI: 10.1126/sciadv.ads7187
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.