A Fluorescence Polarization Assay for Macrodomains Facilitates the Identification of Potent Inhibitors of the SARS-CoV-2 Macrodomain.
Ananya AnmangandlaSadhan JanaKewen PengShamar D WallaceSaket Rahul BagdeBryon S DrownJiashu XuPaul J HergenrotherJ Christopher FrommeHening LinPublished in: ACS chemical biology (2023)
Viral macrodomains, which can bind to and/or hydrolyze adenine diphosphate ribose (ADP-ribose or ADPr) from proteins, have been suggested to counteract host immune response and be viable targets for the development of antiviral drugs. Therefore, developing high-throughput screening (HTS) techniques for macrodomain inhibitors is of great interest. Herein, using a novel tracer TAMRA-ADPr , an ADP-ribose compound conjugated with tetramethylrhodamine, we developed a robust fluorescence polarization assay for various viral and human macrodomains including SARS-CoV-2 Macro1, VEEV Macro, CHIKV Macro, human MacroD1, MacroD2, and PARP9 Macro2. Using this assay, we validated Z8539 (IC 50 6.4 μM) and GS441524 (IC 50 15.2 μM), two literature-reported small-molecule inhibitors of SARS-CoV-2 Macro1. Our data suggest that GS441524 is highly selective for SARS-CoV-2 Macro1 over other human and viral macrodomains. Furthermore, using this assay, we identified pNP-ADPr (ADP-ribosylated p -nitrophenol, IC 50 370 nM) and TFMU-ADPr (ADP-ribosylated trifluoromethyl umbelliferone, IC 50 590 nM) as the most potent SARS-CoV-2 Macro1 binders reported to date. An X-ray crystal structure of SARS-CoV-2 Macro1 in complex with TFMU-ADPr revealed how the TFMU moiety contributes to the binding affinity. Our data demonstrate that this fluorescence polarization assay is a useful addition to the HTS methods for the identification of macrodomain inhibitors.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- endothelial cells
- high throughput
- small molecule
- immune response
- photodynamic therapy
- pluripotent stem cells
- systematic review
- magnetic resonance imaging
- single molecule
- magnetic resonance
- dendritic cells
- electronic health record
- inflammatory response
- anti inflammatory
- coronavirus disease
- single cell
- dna damage
- machine learning
- capillary electrophoresis