Dual Antimicrobial and Antiproliferative Activity of TcPaSK Peptide Derived from a Tribolium castaneum Insect Defensin
Bibliographic record
Abstract
Antimicrobial peptides (AMPs) found in the innate immune system of a wide range of organisms might prove useful to fight infections, due to the reported slower development of resistance to AMPs. Increasing the cationicity and keeping moderate hydrophobicity of the AMPs have been described to improve antimicrobial activity. We previously found a peptide derived from the Tribolium castaneum insect defensin 3, exhibiting antrimicrobial activity against several human pathogens. Here, we analyzed the effect against Staphyloccocus aureus of an extended peptide (TcPaSK) containing two additional amino acids, lysine and asparagine, flanking the former peptide fragment in the original insect defensin 3 protein. TcPaSK peptide displayed higher antimicrobial activity against S. aureus, and additionally showed antiproliferative activity against the MDA-MB-231 triple negative breast cancer cell line. A SWATH proteomic analysis revealed the downregulation of proteins involved in cell growth and tumor progression upon TcPaSK cell treatment. The dual role of TcPaSK peptide as antimicrobial and antiproliferative agent makes it a versatile molecule that warrants exploration for its use in novel therapeutic developments as an alternative approach to overcome bacterial antibiotic resistance and to increase the efficacy of conventional cancer treatments.
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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) | 0.000 | 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 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".