Factors Affecting Non-Enzymatic Protein Acylation by trans-3-Methylglutaconyl Coenzyme A
Bibliographic record
Abstract
The leucine catabolism pathway intermediate, trans-3-methylglutaconyl (3MGC) CoA, is considered to be the precursor of 3MGC acid, a urinary organic acid associated with specific inborn errors of metabolism (IEM). trans-3MGC CoA is an unstable molecule that can undergo a sequence of non-enzymatic chemical reactions that lead to either 3MGC acid or protein 3MGCylation. Herein, the susceptibility of trans-3MGC CoA to protein 3MGCylation was investigated. trans-3MGC CoA was generated through the activity of recombinant 3-methylcrotonyl CoA carboxylase (3MCCCase). Following enzyme incubations, reaction mixtures were spin-filtered to remove 3MCCCase. The recovered filtrates, containing trans-3MGC CoA, were then incubated in the presence of bovine serum albumin (BSA). Following this, sample aliquots were subjected to α-3MGC IgG immunoblot analysis to probe for 3MGCylated BSA. Experiments revealed a positive correlation between trans-3MGC CoA incubation temperature and 3MGCylated BSA immunoblot signal intensity. A similar correlation was observed between incubation time and 3MGCylated BSA immunoblot signal intensity. When trans-3MGC CoA hydratase (AUH) was included in incubations containing trans-3MGC CoA and BSA, 3MGCylated BSA immunoblot signal intensity decreased. Evidence that protein 3MGCylation occurs in vivo was obtained in studies with liver-specific 3-hydroxy-3-methylglutaryl (HMG) CoA lyase knockout mice. Therefore, trans-3MGC CoA is a reactive, potentially toxic metabolite, and under normal physiological conditions, lowering trans-3MGC CoA levels via AUH-mediated hydration to HMG CoA protects against aberrant non-enzymatic chemical reactions that lead to protein 3MGCylation and 3MGC acid 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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".