Proteolytically Stable Cancer Targeting Peptides with High Affinity for Breast Cancer Cells
Why this work is in the frame
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Bibliographic record
Abstract
Cancer cell targeting peptides have emerged as a highly efficient approach for selective delivery of chemotherapeutics and diagnostics to different cancer cells. However, the use of α-peptides in pharmaceutical applications is hindered by their enzymatic degradation and low bioavailability. Starting with a 10-mer α-peptide 18 that we developed previously, here we report three novel analogues of 18 that are proteolytically stable and display better (up to 3.5-fold) affinity profiles for breast cancer cells compared to 18. The design strategy involved replacement of two or three amino acids in the sequence of 18 with d-residues or β(3)-amino acids. Such replacement maintained the specificity for cancer cells (MDA-MB-435, MDA-MB-231, and MCF-7) with low affinity for control noncancerous cells (MCF-10A and HUVEC), showed an increase in secondary structure, and rendered the analogues completely stable to human serum and liver homogenate from mice. The three analogues are potentially safe with minimal cellular toxicity and are efficient targeting moieties for specific drug delivery to breast cancer cells. The strategy used here may be adapted to develop peptide analogues that will target other cancer cell types.
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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) | 0.001 | 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 it