Conformational Modulation of in Vitro Activity of Cyclic RGD Peptides via Aziridine Aldehyde-Driven Macrocyclization Chemistry
Bibliographic record
Abstract
Here, we demonstrate a conjugation strategy whereby cyclic RGD-containing macrocycles are prepared using aziridine aldehydes, isocyanides, and linear peptides, followed by conjugation to a cysteamine linker. Our method involves site-selective aziridine ring-opening with the nucleophilic sulfhydryl group of cysteamine. Fluorescein was then efficiently conjugated to the primary amine of cysteamine by NHS-chemistry. This strategy may be expanded to provide easy access to a wide variety of fluorescent dyes or radiometal chelators. Modeling studies showed that aziridine aldehyde cyclization chemistry stabilized the RGD motif into the required bioactive conformation and that this cyclization chemistry modulated the geometry of macrocycles of different residue lengths. In vitro studies showed that cPRGDA and cPRGDAA both selectively bound to α(V)β(3)-overexpressing U87 glioblastoma cells, and that cPRGDA had a better binding affinity compared to cPRGDAA. The improved binding affinity of cPRGDA was attributed to the fixed Pro-C(α)-Asp-C(α) distance surrounding the stabilized RGD motif in cPRGDA.
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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".