Optimization of Microbial Specificity in Cyclic Peptides by Modulation of Hydrophobicity within a Defined Structural Framework
Bibliographic record
Abstract
In the present study we have utilized the structural framework of the analog GS14K4 (cyclo(VKLd-KVd-YPL KVKLd-YP, where d denotes a d-amino acid)), to examine the role of hydrophobicity in microbial activity and specificity. The hydrophobicity of GS14K4 was systematically altered by residue replacements in the hydrophobic sites of the molecule to produce a series of analogs that were either less or more hydrophobic than the parent compound. Circular dichroism spectroscopy and reversed-phase high performance liquid chromatography analysis showed that the molecules were structurally similar and only differed in overall hydrophobicity. The hydrophobicity of GS14K4 was found to be the midpoint for hemolytic activity, with more hydrophobic analogs exhibiting increased hemolytic activity and less hydrophobic analogs showing decreased hemolytic activity. For antimicrobial activity there were differences between the hydrophobicity requirements against Gram-positive and Gram-negative microorganisms. The hydrophobicity of GS14K4 was sufficient for maximum activity against Gram-negative microorganisms and yeast, with no further increases in activity occurring with increasing hydrophobicity. With Gram-positive microorganisms significant increases in activity with increasing hydrophobicity were seen in three of the six microorganisms tested. A therapeutic index (calculated as a measure of specificity of the peptides for the microorganisms over human erythrocytes) served to define the boundaries of a therapeutic window within which lay the optimum peptide hydrophobicity for each microorganism. The therapeutic window was found to be at a lower hydrophobicity level for Gram-negative microorganisms than for Gram-positive microorganisms, although the limits were more variable for the latter. Our results show that the balance between activity and specificity in the present cyclic peptides can be optimized for each microorganism by systematic modulation of hydrophobicity.
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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".