Systematic Identification of Methyllysine-Driven Interactions for Histone and Nonhistone Targets
Bibliographic record
Abstract
An important issue in epigenetic research is to understand how the numerous methylation marks associated with histone and certain nonhistone proteins are recognized and interpreted by the hundreds of chromatin-binding modules (CBMs) in a cell to control chromatin state, gene expression, and other cellular functions. We have assembled a peptide chip that represents known and putative lysine methylation marks on histones and p53 and probed the chip for binding to a group of CBMs to obtain a comprehensive interaction network mediated by lysine methylation. Interactions revealed by the peptide array screening were validated by in-solution binding assays. This study not only recapitulated known interactions but also uncovered new ones. A novel heterochromatin protein 1 beta (HP1β) chromodomain-binding site on histone H3, H3K23me, was discovered from the peptide array screen and subsequently verified by mass spectrometry. Data from peptide pull-down and colocalization in cells suggest that, besides the H3K9me mark, H3K23me may play a role in facilitating the recruitment of HP1β to the heterochromatin. Extending the peptide array and mass spectrometric approach presented here to more histone marks and CBMs would eventually afford a comprehensive specificity and interaction map to aid epigenetic studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".