The bZIP Targets Overlapping DNA Subsites within a Half-Site, Resulting in Increased Binding Affinities
Bibliographic record
Abstract
We previously reported that the wt bZIP, a hybrid of the GCN4 basic region and C/EBP leucine zipper, not only recognizes GCN4 cognate site AP-1 (TGACTCA) but also selectively targets noncognate DNA sites, in particular the C/EBP site (TTGCGCAA). In this work, we used electrophoretic mobility shift assay and DNase I footprinting to investigate the factors driving the high affinity between the wt bZIP and the C/EBP site. We found that on each strand of the C/EBP site, the wt bZIP recognizes two 4 bp subsites, TTGC and TGCG, which overlap to form the effective 5 bp half-site (TTGCG). The affinity of the wt bZIP for the overall 5 bp half-site is >or=10-fold stronger than that for either 4 bp subsite. Our results suggest that interactions of the wt bZIP with both subsites contribute to the strong affinity at the overall 5 bp half-site and, consequently, the C/EBP site. Accordingly, we propose that the wt bZIP undergoes conformational changes to slide between the two overlapping subsites on the same DNA strand and establish sequence-selective contacts with the different subsites. The proposed binding mechanism expands our understanding of what constitutes an actual DNA target site in protein-DNA interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".