Double Stranded DNA Binding Stapled Peptides: An Emerging Tool for Transcriptional Regulation
Bibliographic record
Abstract
Stapled peptides have rapidly established themselves as a powerful technique to mimic α-helical interactions with a short peptide sequence. There are many examples of stapled peptides that successfully disrupt α-helix-mediated protein-protein interactions, with an example currently in clinical trials. DNA-protein interactions are also often mediated by α-helices and are involved in all transcriptional regulation processes. Unlike DNA-binding small molecules, which typically lack DNA sequence selectivity, DNA-binding proteins bind with high affinity and high selectivity. These are ideal candidates for the design DNA-binding stapled peptides. Despite the parallel to protein-protein interaction disrupting stapled peptides and the need for sequence specific DNA binders, there are very few DNA-binding stapled peptides. In this review we examine all the known DNA-binding stapled peptides. Their design concepts are compared to stapled peptides that disrupt protein-protein interactions and based on the few examples in the literature, DNA-binding stapled peptide trends are discussed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".