HTRF-based assay for detection of mono-ADP-ribosyl hydrolyzing macrodomains and inhibitor screening
Bibliographic record
Abstract
The COVID-19 pandemic has highlighted the lack of effective, ready-to-use antivirals for the treatment of viruses with pandemic potential. The development of a diverse drug portfolio is therefore crucial for pandemic preparedness. Viral macrodomains are attractive therapeutic targets as they are suggested to play an important role in evading the innate host immune response, making them critical for viral pathogenesis. Macrodomains function as erasers of mono-ADP-ribosylation (deMARylation), a post-translational modification that is involved in interferon signaling. Herein, we report the development of a modular HTRF-based assay, that can be used to screen for inhibitors of various viral and human macrodomains. We characterized the five most promising small molecule SARS-CoV-2 Mac1 inhibitors recently reported in the literature for potency and selectivity and conducted a pilot screen demonstrating HTS suitability. The ability to directly detect enzymatic activity makes the DeMAR assay a valuable addition to the existing tools for macrodomain drug discovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".