Use of 7-Ethoxycoumarin to Monitor Multiple Enzymes in the Human CYPI, CYP2, and CYP3 Families
Bibliographic record
Abstract
Chapters 10-20 describe assay methods for determining enzyme activities that are frequently employed as markers for specific cytochrome P450 (P450) enzymes in human tissues. However, under certain circumstances, e.g., when the objective is to verify that individual cDNA-expressed P450 enzymes are expressed in catalytically active form, it is often advantageous to assay the panel of enzymes using a “general” P450 substrate, one that is metabolized by multiple P450 enzymes. An example of a general P4.50 substrate is 7-ethoxycoumarin. Enzyme kinetic analysis with human liver microsomes indicates that 7-ethoxycoumarin is metabolized by at least two P450 enzymes or by two groups of P450 enzymes that are kinetically distmguishable (, ). The apparent Km and maximal specific activity (i.e., specific activity at saturating substrate concentration) values for 7-ethoxycoumarin O-deethylation by human liver microsomes are 11–27 µM and 0.05–0.21 nmol/min/mg microsoma1 protein, respectively, for the low Km component. By contrast, for the high Km component, the apparent Km is approx 150 µM and the maximal specific activity is 0.35–0.95 nmol/min/mg microsomal protein (). Experiments with recombinant human P450s have shown that multiple enzymes in the human CYP1, CYP2, and CYP3 families are active catalysts of 7-ethoxycoumarin O-deethylation (). Consequently, the 7-ethoxycoumarin O-deethylase assay has been used to verify the catalytic activity of a panel of recombinant human P450s in the CYPl, CYP2 and CYP3 families (, , ).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".