One-dimensional diffusion of TrpR along DNA enhances its affinity for the operator by chemical ratchet mechanism
Bibliographic record
Abstract
Abstract Several DNA-binding proteins show the affinities for their specific DNA sites that positively depend on the length of DNA harboring the sites, i. e. antenna effect. DNA looping can cause the effect for proteins with two or more DNA binding sites, i. e. the looping mechanism. One-dimensional diffusion also has been suggested to cause the effect for proteins with single DNA sites, the diffusion mechanism, which could violate detailed balance. We addressed which mechanism is possible for E. coli TrpR showing 104-fold antenna effect with a single DNA binding site. When a trpO-harboring DNA fragment was connected to a nonspecific DNA with biotin-avidin connection, the otherwise sevenfold antenna effect disappeared. This result denies the looping mechanism with an unknown second DNA binding site. The 3.5-fold repression by TrpR in vivo disappeared when a tight LexA binding site was introduced at various sites near the trpO, suggesting that the binding of LexA blocks one-dimensional diffusion causing the antenna effect. These results are consistent with the chemical ratchet recently proposed for TrpR-trpO binding to solve the deviation from detailed balance, and evidence that the antenna effect due to one-dimensional diffusion exists in cells.
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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) | 0.002 | 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".