Acyl transfer from carboxylate, carbonate, and thiocarbonate esters to enzymatic and nonenzymatic thiolates
Bibliographic record
Abstract
Transglutaminases (EC 2.3.2.13) (TGases) catalyze calcium-dependent acyl transfer reactions between peptide-bound glutamine residues as acyl donors and peptide-bound lysine residues as acyl acceptors, resulting in the formation of intermolecular ε-(γ-glutamyl)lysine crosslinks. The mechanistic details of its "ping-pong" transamidation reaction remain unknown. In particular, few studies have been published probing the nucleophilicity of TGase using acyl-donor substrates of varied electrophilicity. Herein we report the synthesis of activated esters of carbonates, carbamates, and thiocarbonates and their reactions with simple thiols, as a nonenzymatic point of reference, and with the catalytic cysteine residue of guinea pig liver TGase. Our kinetic results show that the simple substitution of a side chain methylene unit by oxygen or sulphur had a surprising effect on both substrate affinity and acylation reactivity. Furthermore, they provide unexpected insight into the importance of a side chain heteroatom for conferring affinity for tissue TGase as well as revealing an interesting class of irreversible inhibitors.Key words: enzyme kinetics, enzyme inhibition, transglutaminase, acyl-transfer reactions, carbamate, thiocarbonate, carbonate.
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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) | 0.000 | 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 | 0.000 |
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 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".