ArticleProtein engineering, design & selection : PEDS2022
Protein engineering approach to enhance activity assays of mono-ADP-ribosyltransferases through proximity.
Article in Protein engineering, design & selection : PEDS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Discovery of Fused Isoquinolinone/Triazole as a Scaffold for Tankyrase and PARP Inhibition.Journal of medicinal chemistry · 2026Article
- PARPs and ADP-ribosylation: Deciphering the complexity with molecular tools.Molecular cell · 2023Review
- [1,2,4]Triazolo[3,4-Journal of medicinal chemistry · 2023Article
- Structure-guided design and characterization of a clickable, covalent PARP16 inhibitor.Chemical science · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human mono-ADP-ribosylating PARP enzymes have been linked to several clinically relevant processes and many of these PARPs have been suggested as potential drug targets. Despite recent advances in the field, efforts to discover inhibitors have been hindered by the lack of tools to rapidly screen for high potency compounds and profile them against the different enzymes. We engineered mono-ART catalytic fragments to be incorporated into a cellulosome-based octavalent scaffold. Compared to the free enzymes, the scaffold-based system results in an improved activity for the tested PARPs due to improved solubility, stability and the proximity of the catalytic domains, altogether boosting their activity beyond 10-fold in the case of PARP12. This allows us to measure their activity using a homogeneous NAD+ conversion assay, facilitating its automation to lower the assay volume and costs. The approach will enable the discovery of more potent compounds due to increased assay sensitivity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.