Structural characterization of interactions between transactivation domain 1 of the p65 subunit of NF-κB and transcription regulatory factors
Bibliographic record
Abstract
p65 is a member of the NF-κB family of transcriptional regulatory proteins that functions as the activating component of the p65-p50 heterodimer. Through its acidic transactivation domain (TAD), p65 has the capacity to form interactions with several different transcriptional regulatory proteins, including TFIIB, TFIIH, CREB-binding protein (CBP)/p300 and TAFII31. Like other acidic TADs, the p65 TAD contains two subdomains (p65TA1 and p65TA2) that interact with different regulatory factors depending on the target gene. Despite its role in controlling numerous NF-κB target genes, there are no high-resolution structures of p65TA1 bound to a target transcriptional regulatory factor. In this work, we characterize the interaction of p65TA1 with two factors, the Tfb1/p62 subunit of TFIIH and the KIX domain of CBP. In these complexes, p65TA1 transitions into a helical conformation that includes its characteristic ΦXXΦΦ motif (Φ = hydrophobic amino acid). Structural and functional studies demonstrate that the two binding interfaces are primarily stabilized by three hydrophobic amino acids within the ΦXXΦΦ motif and these residues are also crucial to its ability to activate transcription. Taken together, the results provide an atomic level description of how p65TA1 is able to bind different transcriptional regulatory factors needed to activate NF-κB target genes.
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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 | 0.001 |
| 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".