Conformational dynamics of the TTD–PHD histone reader module of the UHRF1 epigenetic regulator reveals multiple histone-binding states, allosteric regulation, and druggability
Bibliographic record
Abstract
UHRF1 is a key mediator of inheritance of epigenetic DNA methylation patterns during cell division and is a putative target for cancer therapy. Recent studies indicate that interdomain interactions critically influence UHRF1's chromatin-binding properties, including allosteric regulation of its histone binding. Here, using an integrative approach that combines small angle X-ray scattering, NMR spectroscopy, and molecular dynamics simulations, we characterized the dynamics of the tandem tudor domain-plant homeodomain (TTD-PHD) histone reader module, including its 20-residue interdomain linker. We found that the apo TTD-PHD module in solution comprises a dynamic ensemble of conformers, approximately half of which are compact conformations, with the linker lying in the TTD peptide-binding groove. These compact conformations are amenable to cooperative, high-affinity histone binding. In the remaining conformations, the linker position was in flux, and the reader adopted both extended and compact states. Using a small-molecule fragment screening approach, we identified a compound, 4-benzylpiperidine-1-carboximidamide, that binds to the TTD groove, competes with linker binding, and promotes open TTD-PHD conformations that are less efficient at H3K9me3 binding. Our work reveals a mechanism by which the dynamic TTD-PHD module can be allosterically targeted with small molecules to modulate its histone reader function for therapeutic or experimental purposes.
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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".