Rapid peptide synthesis using a methylimidazolium sulfinyl fluoride salt
Bibliographic record
Abstract
Peptide couplings have been a subject of investigation for over a century, with modern research seeking to discover new methodologies that minimize purification steps, minimize reagent expense, and/or decrease reaction times. Of the numerous coupling reagents available, sulfur(IV) fluorides have potential as they can effectively transform carboxylic acids to reactive intermediates, and the sulfite by-products can be removed through aqueous washes. Here we demonstrate the formation and capture of key acyl fluorosulfite intermediates for peptide couplings in 15 min total, without epimerization or column chromatography for purification. Dipeptides were obtained in 40–94% yields. This approach was expanded to longer chains through iterative couplings, with oligopeptides obtained in 24–57% yields, each within 2 days. Mechanistic studies indicate the reaction does not proceed through acyl fluoride intermediates, and instead involves nucleophilic catalysis. The mild conditions are tolerant of a wide range of protecting groups of canonical and non-canonical amino acids. Peptides have been known to be important therapeutics; however, minimizing purification steps, reagent expense, and reaction times in modern peptide coupling methods remains challenging. Here, the authors use sulfur(IV) fluorides as a coupling reagent, demonstrating the formation and capture of key acyl fluorosulfite intermediates for rapid peptide couplings, without epimerization or column chromatography for purification, achieving 40–94% yields for dipeptides and 24–57% yields for oligopeptide formation.
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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 | 0.001 | 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".