Structural diversity of the epigenetics pocketome
Bibliographic record
Abstract
Protein families involved in chromatin-templated events are emerging as novel target classes in oncology and other disease areas. The ability to discover selective inhibitors against chromatin factors depends on the presence of structural features that are unique to the targeted sites. To evaluate challenges and opportunities toward the development of selective inhibitors, we calculated all pair wise structural distances between 575 structures from the protein databank representing 163 unique binding pockets found in protein domains that write, read or erase post-translational modifications on histones, DNA, and RNA. We find that the structural similarity of binding sites does not always follow the sequence similarity of protein domains. Our analysis reveals increased risks of activity across target-class for compounds competing with the cofactor of protein arginine methyltransferases, lysine acetyltransferases, and sirtuins, while exploiting the conformational plasticity of a protein target is a path toward selective inhibition. The structural diversity landscape of the epigenetics pocketome can be explored via an open-access graphic user interface at thesgc.org/epigenetics_pocketome.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".