The bZIP Dimer Localizes at DNA Full-Sites Where Each Basic Region Can Alternately Translocate and Bind to Subsites at the Half-Site
Bibliographic record
Abstract
Crystal structures of the GCN4 bZIP (basic region/leucine zipper) with the AP-1 or CRE site show how each GCN4 basic region binds to a 4 bp cognate half-site as a single DNA target; however, this may not always fully describe how bZIP proteins interact with their target sites. Previously, we showed that the GCN4 basic region interacts with all 5 bp in half-site TTGCG (termed 5H-LR) and that 5H-LR comprises two 4 bp subsites, TTGC and TGCG, which individually are also target sites of the basic region. In this work, we explore how the basic region interacts with 5H-LR when the bZIP dimer localizes to full-sites. Using AMBER molecular modeling, we simulated GCN4 bZIP complexes with full-sites containing 5H-LR to investigate in silico the interface between the basic region and 5H-LR. We also performed in vitro investigation of bZIP-DNA interactions at a number of full-sites that contain 5H-LR versus either subsite: we analyzed results from DNase I footprinting and electrophoretic mobility shift assay (EMSA) and from EMSA titrations to quantify binding affinities. Our computational and experimental results together support a highly dynamic DNA-binding model: when a bZIP dimer localizes to its target full-site, the basic region can alternately recognize either subsite as a distinct target at 5H-LR and translocate between the subsites, potentially by sliding and hopping. This model provides added insights into how α-helical DNA-binding domains of transcription factors can localize to their gene regulatory sequences in vivo.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".