Optimization of on-resin palladium-catalyzed Sonogashira cross-coupling reaction for peptides and its use in a structure–activity relationship study of a class B GPCR ligand
Bibliographic record
Abstract
Class B G protein-coupled receptors are activated by their cognate ligands following a two-step binding model involving a specific network of ligand-receptor intermolecular interactions. In particular, a N-capping structure present in the ligand would contribute significantly to position the N-terminal segment of the ligand once bound to its receptor. The aim of the current study was to implement the use of Pd-catalyzed Sonogashira coupling for the investigation of this structural motif. First, we have developed and evaluated various Sonogashira-based procedures for on-resin post-synthesis modification using a Leu-enkephalin derivative as a model peptide. Next, we have prepared a small library of PACAP-based analogs and evaluated the pharmacological profile of a few of them using a competitive binding assay, as well as functional and survival assays. Notably, our results suggest that the modification of the N-capping region could alter the binding specificity of PACAP without altering its biological activity, thereby opening the way for the design of more selective compounds. Finally, the possibility to achieve sequential multiple point substitutions via the Sonogashira cross-coupling method, during solid phase peptide synthesis, was also evaluated. Altogether, we demonstrated the versatility of such a procedure for the incorporation of various mono- and multiple alkyne-derived modifications during solid phase peptide synthesis and confirmed its usefulness for the structure-activity study of a class B GPCR ligand.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".