In-Cell Synthesis of Bioorthogonal Alkene Tag S-Allyl-Homocysteine and Its Coupling with Reprogrammed Translation
Bibliographic record
Abstract
In this study, we report our initial results on in situ biosynthesis of S-allyl-l-homocysteine (Sahc) by simple metabolic conversion of allyl mercaptan in Escherichia coli, which served as the host organism endowed with a direct sulfhydration pathway. The intracellular synthesis we describe in this study is coupled with the direct incorporation of Sahc into proteins in response to methionine codons. Together with O-acetyl-homoserine, allyl mercaptan was added to the growth medium, followed by uptake and intracellular reaction to give Sahc. Our protocol efficiently combined the in vivo synthesis of Sahc via metabolic engineering with reprogrammed translation, without the need for a major change in the protein biosynthesis machinery. Although the system needs further optimisation to achieve greater intracellular Sahc production for complete protein labelling, we demonstrated its functional versatility for photo-induced thiol-ene coupling and the recently developed phosphonamidate conjugation reaction. Importantly, deprotection of Sahc leads to homocysteine-containing proteins—a potentially useful approach for the selective labelling of thiols with high relevance in various medical settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".