Diversity-Oriented A<sup>3</sup>-Macrocyclization for Studying Influences of Ring-Size and Shape of Cyclic Peptides: CD36 Receptor Modulators
Bibliographic record
Abstract
Cyclic peptide diversity has been broadened by elaborating the A 3 -macrocyclization to include various di-amino carboxylate components with different N ε -amine substituents. Triple-bond reduction provided new cyclic peptide macrocycles with Z -olefin and completely saturated structures. Moreover, cyclic azasulfurylpeptides were prepared by exchanging the propargylglycine (Pra) component for an amino sulfamide surrogate. Examination of such diversity-oriented methods on potent cyclic azapeptide modulators of the cluster of differentiation 36 receptor (CD36) identified the importance of the triple bond as well as the N ε -allyl lysine and azaPra residues for high CD36 binding affinity. Cyclic azapeptides which engaged CD36 effectively reduced pro-inflammatory nitric oxide and downstream cytokine and chemokine production in macrophages stimulated with a Toll-like receptor-2 agonist. Studying the triple bond and amine components in the multiple-component A 3 -macrocyclization has given a diverse array of macrocycles and pertinent information to guide the development of ideal CD36 modulators with biomedical potential for curbing macrophage-driven inflammation.
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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".