Chemical probes targeting epigenetic proteins: Applications beyond oncology
Bibliographic record
Abstract
Epigenetic chemical probes are potent, cell-active, small molecule inhibitors or antagonists of specific domains in a protein; they have been indispensable for studying bromodomains and protein methyltransferases. The Structural Genomics Consortium (SGC), comprising scientists from academic and pharmaceutical laboratories, has generated most of the current epigenetic chemical probes. Moreover, the SGC has shared about 4 thousand aliquots of these probes, which have been used primarily for phenotypic profiling or to validate targets in cell lines or primary patient samples cultured in vitro. Epigenetic chemical probes have been critical tools in oncology research and have uncovered mechanistic insights into well-established targets, as well as identify new therapeutic starting points. Indeed, the literature primarily links epigenetic proteins to oncology, but applications in inflammation, viral, metabolic and neurodegenerative diseases are now being reported. We summarize the literature of these emerging applications and provide examples where existing probes might be used.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".