Folding in Place: Design of β-Strap Motifs to Stabilize the Folding of Hairpins with Long Loops
Bibliographic record
Abstract
Despite their pivotal role in protein function and antibody binding affinity, β-hairpins bearing long non-canonical loops are a challenge to modern synthesis because of the large entropic penalty associated with their folding. Little is known about the contribution and impact of stabilizing motifs on the folding of β-hairpins of variable length and plasticity. Here we report a direct comparison between these b-straps thermodynamics and their thermal stability behavior using several local spectroscopic probes of the folding/unfolding landscape. The judicious cooperative interactions crafted in β-Strap RW(VW)•••(WV/H)WE (strap = strand + cap) greatly stabilized hairpins with up to 10-residue loops lacking an innate nucleating-turn locus (Tm up to 52 oC; 88 ± 1% folded at 291 K). The present design of novel β-straps aims to provide the foundation to study new classes of long hairpins and ultimately offer an attractive alternative to macrocyclic peptides for the mimicry of functional loops from proteins and antibodies.
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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 | 0.001 |
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".