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 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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".