A chemiluminescence-based method for identification of histone lysine methyltransferase inhibitors
Bibliographic record
Abstract
Methylation of lysine residues, catalyzed by histone methyltransferase (HMT) enzymes, is one of many modifications of core histone proteins that regulate transcription and chromatin structure. G9a is the predominant HMT in mammalian euchromatin and recent data suggest that it is required to perpetuate a malignant phenotype in cancer cells and is implicated in metastasis, supporting this HMT as a therapeutic target for cancer and other diseases associated with epigenetic regulation. Of the methods currently used to measure methyltransferase activity, many involve a separation step or utilize coupling enzymes complicating implementation and data interpretation. Here we describe a homogeneous assay to measure G9a HMT activity using the chemiluminescence-based AlphaScreen immunoassay technology. Methylation of biotinylated-histone peptide is measured through specific antibody-based detection, in conjunction with streptavidin-coated donor and secondary antibody-coated acceptor beads. The method is particularly well suited for detection of inhibitors acting by the desired histone peptide competitive mechanism and is applicable to testing other HMTs, demonstrated here with the G9a homolog EHMT1, also known as GLP.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".