Interactions of a DNA-bound Transcriptional Activator with the TBP-TFIIA-TFIIB-Promoter Quaternary Complex
Bibliographic record
Abstract
Site-specific protein-DNA photo-cross-linking was used to show that, when bound to its cognate site at various distances upstream of the TATA element, the chimeric transcriptional activator GAL4-VP16 can physically interact with a TATA box-binding protein (TBP)- transcription factor IIA (TFIIA)-TFIIB complex assembled on the TATA element. This result implies DNA bending and looping of promoter DNA as a result of the physical interaction between GAL4-VP16 and an interface of the TBP-TFIIA-TFIIB complex. This protein-protein interaction on promoter DNA minimally requires the presence of one GAL4 binding site and the formation of a quaternary complex containing TBP, TFIIB, and TFIIA on the TATA element. Notably, the topology of the TBP-TFIIA-TFIIB-promoter complex is not altered significantly by the interaction with DNA-bound activators. We also show that the ability of GAL4-VP16 to activate transcription through a single GAL4 binding site varies according to its precise location and orientation relative to the TATA element and that it can approach the efficiency obtained with multiple binding sites. Taken together, our results indicate that the spatial positioning of the DNA-bound activation domain is important for efficient activation, possibly by maximizing its interactions with the transcriptional machinery including the TBP-TFIIA-TFIIB-promoter quaternary complex.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".