Effect of Ring Size on Conformation and Biological Activity of Cyclic Cationic Antimicrobial Peptides
Bibliographic record
Abstract
In a series of cyclic peptides based on GS10, an analogue of gramicidin S (GS), the ring size was varied from 10 to 16 amino acids. Alternative addition of basic and hydrophobic amino acids to the original GS10 construct generated a variety of even-numbered rings, i.e., GS10 [cyclo-(VKLdYPVKLdYP)], GS12 [cyclo-(VKLKdYPKVKLdYP)], GS14 [cyclo-(VKLKVdYPLKVKLdYP), and GS16 [cyclo-(VKLKVKdYPKLKVKLdYP)] (d stands for d-enantiomers). The odd-numbered analogues (11-, 13-, and 15-mers) were derived from these four peptides by either addition or deletion of single basic (Lys) or hydrophobic (Leu or Val) amino acids. The resulting peptides, divided into three groups on the basis of peptide ring size (10- to 12-meric, 13- and 14-meric, and 15- and 16-meric), illustrated a diverse spectrum of biological activity correlated to their ring size, degree of beta-structure disruption, charge, hydrophobicity, amphipathicity, and affinity for lipid membranes. Two of these peptides with potent antimicrobial activities and high therapeutic indexes (4.5- to 10-fold compared with GS) are promising candidates for development of broad-spectrum antibiotics.
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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 | 0.001 |
| 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".