Novel thioester reagents afford efficient and specific S‐acylation of unprotected peptides under mild conditions in aqueous solution
Bibliographic record
Abstract
S-acylated peptides have many potential uses for elucidating the biophysical, structural and other properties of the numerous S-acylated proteins of mammalian cells. However, with the currently available reagents, preparation of specifically S-acylated derivatives of peptides is generally laborious or simply unfeasible. We here show that novel, easily preparable aryl and alkyl thioester derivatives of palmitic acid can mediate S-acylation of peptides corresponding to physiologically S-acylated sequences from the proteins p56(lck) and H-ras and the Po glycoprotein of peripheral myelin, with high selectivity for cysteine over other amino acid functional groups (including hydroxyl and both alpha- and epsilon-amino residues), and with much greater efficiency than is obtained using acyl-coenzyme A derivatives. Efficient and selective S-acylation can be accomplished under very mild conditions in aqueous systems containing lipid vesicles or detergent micelles, or in homogenous aqueous/acetonitrile mixtures. Using these novel thioesterifying reagents, we confirm previous suggestions that the N-terminal cysteine residue of Hedgehog proteins can exhibit rapid, uncatalyzed S-to-N acyl transfer following S-acylation to produce the N-palmitoylated amino terminus found in the mature protein. By contrast, we demonstrate that spontaneous S-to-N acyl transfer from the cysteine to the terminal glycine residue in the amino-terminal peptide of G(alphas) is far less rapid and is likely too slow to explain the physiological N-palmitoylation of the amino terminus of this protein.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".