Development of Homogeneous Nonradioactive Methyltransferase and Demethylase Assays Targeting Histone H3 Lysine 4
Bibliographic record
Abstract
Histone posttranslational modifications are among the epigenetic mechanisms that modulate chromatin structure and gene transcription. Histone methylation and demethylation are dynamic processes controlled respectively by histone methyltransferases (HMTs) and demethylases (HDMs). Several HMTs and HDMs have been implicated in cancer, inflammation, and diabetes, making them attractive targets for drug therapy. Hence, the discovery of small-molecule modulators for these two enzyme classes has drawn significant attention from the pharmaceutical industry. Herein, the authors describe the development and optimization of homogeneous LANCE Ultra and AlphaLISA antibody-based assays for measuring the catalytic activity of two epigenetic enzymes acting on lysine 4 of histone H3: SET7/9 methyltransferase and LSD1 demethylase. Both the SET7/9 and LSD1 assays were designed as signal-increase assays using biotinylated peptides derived from the N-terminus of histone H3. In addition, the SET7/9 assay was demonstrated using full-length histone H3 protein as substrate in the AlphaLISA format. Optimized assays in 384-well plates are robust (Z' factors ≥0.7) and sensitive, requiring only nanomolar concentrations of enzyme and substrate. All assays allowed profiling of known SET7/9 and LSD1 inhibitors. The results demonstrate that the optimized LANCE Ultra and AlphaLISA assay formats provide a relevant biochemical screening approach toward the identification of small-molecule inhibitors of HMTs and HDMs that could lead to novel epigenetic therapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".