Design and Characterization of a Multifunctional pH‐Triggered Peptide C8 for Selective Anticancer Activity
Bibliographic record
Abstract
Most drug delivery systems have been developed for efficient delivery to tumor sites via targeting and on-demand strategies, but the carriers rarely execute synergistic therapeutic actions. In this work, C8, a cationic, pH-triggered anticancer peptide, is developed by incorporating histidine-mediated pH-sensitivity, amphipathic helix, and amino acid pairing self-assembly design. We designed C8 to function as a pH-responsive nanostructure whose cytotoxicity can be switched on and off by its self-assembly: Noncytotoxic β-sheet fibers at high pH with neutral histidines, and positively charged monomers with membrane lytic activity at low pH. The selective activity of C8, tested for three different cancer cell lines and two noncancerous cell lines, is shown. Based on liposome leakage assays and multiscale computer simulations, its physical mechanisms of pore-forming action and selectivity are proposed, which originate from differences in the lipid composition of the cellular membrane and changes in hydrogen bonding. C8 is then investigated for its potential as a drug carrier. C8 forms a nanocomplex with ellipticine, a nonselective model anticancer drug. It selectively targets cancer cells in a pH-responsive manner, demonstrating enhanced efficacy and selectivity. This study provides a novel powerful strategy for the design and development of multifunctional self-assembling peptides for therapeutic and drug delivery applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".