High-affinity chromodomains engineered for improved detection of histone methylation and enhanced CRISPR-based gene repression
Bibliographic record
Abstract
Histone methylation is an important post-translational modification that plays a crucial role in regulating cellular functions, and its dysregulation is implicated in cancer and developmental defects. Therefore, systematic characterization of histone methylation is necessary to elucidate complex biological processes, identify biomarkers, and ultimately, enable drug discovery. Studying histone methylation relies on the use of antibodies, but these suffer from lot-to-lot variation, are costly, and cannot be used in live cells. Chromatin-modification reader domains are potential affinity reagents for methylated histones, but their application is limited by their modest affinities. We used phage display to identify key residues that greatly enhance the affinities of Cbx chromodomains for methylated histone marks and develop a general strategy for enhancing the affinity of chromodomains of the human Cbx protein family. Our strategy allows us to develop powerful probes for genome-wide binding analysis and live-cell imaging. Furthermore, we use optimized chromodomains to develop extremely potent CRISPR-based repressors for tailored gene silencing. Our results highlight the power of engineered chromodomains for analyzing protein interaction networks involving chromatin and represent a modular platform for efficient gene silencing.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".