Tryptic Stability of Synthetic Bactenecin Derivatives Is Determined by the Side Chain Length of Cationic Residues and the Peptide Conformation
Bibliographic record
Abstract
Synthetic bactenecins 1 (HHC-10) and 10 (HHC-36), with excellent activities against bacterial superbugs, display low tryptic stability. To investigate factors influencing this stability, a series of 1/10 derived peptides bearing arginine and lysine analogues with varied methylene chains as well as all-d-isomers were synthesized. Whereas incorporation of d-/l-nonproteinogenic amino acids into the turn-forming peptides did not dramatically affect the antimicrobial activities, the degree of peptide cleavage decreased significantly in peptides with the shortest length of cationic side chain and was influenced by the relative conformational stabilities of the turn structure and the stereoselectivity of tryptic digestion. The site of enzymatic cleavage was located at the less conformationally hindered position distant from the turn motif. Isothermal titration calorimetry showed strong and weak constant increments in the generated heat of enzymatic reaction of unstable and slowly degradable peptides with trypsin, respectively, and suggested a one-site binding model for the enthalpy-driven all-d-peptide-trypsin interactions.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".