High-Affinity Fluorogenic Substrate for Tissue Transglutaminase Reveals Enzymatic Hysteresis
Bibliographic record
Abstract
Transglutaminases (TGases) are a family of calcium-dependent enzymes primarily known for their ability to cross-link proteins. Transglutaminase 2 (TG2) is one isozyme in this family whose role is multifaceted. TG2 can act not only as a typical transamidase through its catalytic core but also as a G-protein via its GTP binding site. These two discrete activities are tightly regulated by both environmental stimuli and redox reactions. Ubiquitously expressed in humans, TG2 has been implicated in numerous disease pathologies that require extensive investigation. The catalytic activity of TG2 can be monitored through various mechanisms, including hydrolysis, transamidation, or cleavage of isopeptide bonds. Activity assays are required to monitor the activity of this isozyme not only for studying its transamidation reaction but also for validation of therapeutics designed to abolish this activity. Herein, we present the design, synthesis, and evaluation of a new TG2 activity substrate based on a previously optimized inhibitor scaffold. The substrate APH7 exhibits excellent affinity, selectivity, and reactivity with TG2 ( K M = 3.0 μM). Furthermore, its application also allowed the discovery of unique hysteresis at play within the catalytic activity and inhibition reactivity of TG2.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".