N- to C-Peptide Synthesis, Arguably the Future for Sustainable Production
Bibliographic record
Abstract
The advancement of peptide production was revolutionized by the introduction of solid-phase synthesis in the C- to N-direction, from carboxylate to amine. This foundational technique in modern peptide science has facilitated numerous academic and industrial applications. However, C- to N-solid-phase peptide synthesis (C-N-SPPS) is associated with high process mass intensity and poor atom economy. A major drawback of C-N-SPPS is its dependence on atom-intensive protecting groups, such as fluorenylmethyloxycarbonyl (Fmoc), along with the excessive use of protected amino acids and coupling reagents. In contrast, synthesizing peptides in the N- to C-direction, from amine to carboxylate, presents an opportunity to reduce reliance on protective strategies and could offer a more efficient approach to peptide manufacturing. Notably, effective amide bond formation in the N- to C-direction has been achieved through techniques involving thioesters, vinyl esters, and transamidation, allowing for peptide synthesis with minimal epimerization. This review explores N- to C-peptide synthesis, highlighting its advantages as a more sustainable alternative for peptide production.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".