Chemical probes targeting epigenetic proteins: Applications beyond oncology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it