Stretching Peptides to Generate Small Molecule β-Strand Mimics
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Advances in the modulation of protein–protein interactions (PPIs) enable both characterization of PPI networks that govern diseases and design of therapeutics and probes. The shallow protein surfaces that dominate PPIs are challenging to target using standard methods, and approaches for accessing extended backbone structures are limited. Here, we incorporate a rigid, linear, diyne brace between side chains at the i to i+ 2 positions to generate a family of low-molecular-weight, extended-backbone peptide macrocycles. NMR and density functional theory studies show that these stretched peptides adopt stable, rigid conformations in solution and can be tuned to explore extended peptide conformational space. The diyne brace is formed in excellent conversions (>95%) and amenable to high-throughput synthesis. The minimalist structure-inducing tripeptide core (<300 Da) is amenable to further synthetic elaboration. Diyne-braced inhibitors of bacterial type 1 signal peptidase demonstrate the utility of the technique.
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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) | 0.002 | 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".