Improved anticancer potency by head‐to‐tail cyclization of short cationic anticancer peptides containing a lipophilic <i>β</i><sup>2,2</sup>‐amino acid
Bibliographic record
Abstract
We have recently reported a series of synthetic anticancer heptapeptides (H-KKWβ(2,2) WKK-NH(2) ) containing a central achiral and lipophilic β(2,2) -amino acid that display low toxicity against non-malignant cells and high proteolytic stability. In the present study, we have further investigated the effects of increasing the rigidity and amphipathicity of two of our lead heptapeptides by preparing a series of seven to five residue cyclic peptides containing the two most promising β(2,2) -amino acid derivatives as part of the central lipophilic core. The peptides were tested for anticancer activity against human Burkitt's lymphoma (Ramos cells), haemolytic activity against human red blood cells (RBC) and cytotoxicity against healthy human lung fibroblast cells (MRC-5). The results demonstrated a considerable increase in anticancer potency following head-to-tail peptide cyclization, especially for the shortest derivatives lacking a tryptophan residue. High-resolution NMR studies and molecular dynamics simulations together with an annexin-V-FITC and propidium iodide fluorescent assay showed that the peptides had a membrane disruptive mode of action and that the more potent peptides penetrated deeper into the lipid bilayer. The need for new anticancer drugs with novel modes of action is demanding, and development of short cyclic anticancer peptides with an overall rigidified and amphipathic structure is a promising approach to new anticancer agents.
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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".