Aryl acylamidase activity of human serum albumin with<i>o</i>-nitrotrifluoroacetanilide as the substrate
Bibliographic record
Abstract
Albumin is generally regarded as an inert protein with no enzyme activity. However, albumin has esterase activity as well as aryl acylamidase activity. A new acetanilide substrate, o-nitrotrifluoroacetanilide (o-NTFNAC), which is more reactive than the classical o-nitroacetanilide, made it possible to determine the catalytic parameters for hydrolysis by fatty-acid free human serum albumin. Owing to the low enzymatic activity of albumin, kinetic studies were performed at high albumin concentration (0.075 mM). The albumin behavior with this substrate was Michaelis-Menten like. Kinetic analysis was performed according to the formalism used for catalysis at high enzyme concentration. This approach provided values for the turnover and dissociation constant of the albumin-substrate complex: k(cat) = 0.13 +/- 0.02 min(-1) and Ks = 0.67 +/- 0.04 mM. MALDI-TOF experiments showed that unlike the ester substrate p-nitrophenyl acetate, o-NTFNAC does not form a stable adduct (acetylated enzyme). Kinetic analysis and MALDI-TOF experiments demonstrated that hydrolysis of o-NTFNAC by albumin is fully rate-limited by the acylation step (k(cat) = k2). Though the aryl acylamidase activity of albumin is low (k(cat)/Ks = 195 M(-1)min(-1)), because of its high concentration in human plasma (0.6-1 mM), albumin may participate in hydrolysis of aryl acylamides through second-order kinetics. This suggests that albumin may have a role in the metabolism of endogenous and exogenous aromatic amides, including drugs and xenobiotics.
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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) | 0.000 | 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) | 0.000 | 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".