The complex interactions of p53 with target DNA: we learn as we go
Bibliographic record
Abstract
The most import biological function of the tumor suppressor p53 is that of a sequence-specific transactivator. In response to a variety of cellular stress stimuli, p53 induces the transcription of an ever-increasing number of target genes, leading to growth arrest and repair, or to apoptosis. Long considered as a "latent" DNA binder that requires prior activation by C-terminal modification, recent data provide strong evidence that the DNA binding activity of p53 is strongly dependent on structural features within the target DNA and is latent only if the target DNA lacks a certain structural signal code. In this review we discuss evidence for complex interactions of p53 with DNA, which are strongly dependent on the dynamics of DNA structure, especially in the context of chromatin. We provide a model of how this complexity may serve to achieve selectivity of target gene regulation by p53 and how DNA structure in the context of chromatin may serve to modulate p53 functions.
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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) | 0.001 | 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 | 0.001 |
| 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".