Molecular Dynamics-Guided All-Atom Reconstruction of Cryo-ET Maps Reveals Mechanisms of Histone Tail-Mediated Chromatin Compaction
Bibliographic record
Abstract
Dynamics and physical state of chromatin are crucial in regulating gene expression, DNA replication, and repair. Intrinsically disordered histone tails were previously recognized as key modulators of chromatin states. However, detailed atomistic mechanisms by which histone tail dynamics are associated with chromatin compaction and higher-order chromatin organization remain poorly understood. In this work, we combine extensive all-atom molecular dynamics simulations of tri-nucleosomes with cryo-electron tomography (Cryo-ET) of native nucleosome arrays to investigate histone tail-mediated chromatin folding. Our approach offers distinct advantages as it elucidates realistic inter- and intra-nucleosomal interactions and DNA conformations derived from physics-based MD simulations, enabling a more accurate and physically grounded interpretation of Cryo-ET data. The results reveal that histone tails promote chromatin compaction and constrain tri-nucleosome unfolding via three major patterns: through histone-DNA interactions, histone H2A-H4 and H3-H4 tail-tail interactions. Notably, the distributions of MD-generated structural parameters of tri-nucleosomes with truncated histone tails were found to be in strong agreement with those of experimental open chromatin arrays with widely spaced nucleosomes, whereas the system with histone tails resembled more condensed chromatin. These findings provide mechanistic insights into how histone tails may mediate chromatin folding at the atomistic scale and underscore the dual role of histone tails in both structural compaction and inter-nucleosomal communication.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".