CYP-Dependent Metabolism of PF9601N, A New Monoamine Oxidase-B Inhibitor, by C57BL / 6 Mouse and Human Liver Microsomes
Bibliographic record
Abstract
PURPOSE: The selective monoamine oxidase-B (MAO-B) inhibitor, l-deprenyl, is still used for treating Parkinson's patients, however, a disadvantage of its use lies in the formation of l-amphetamine and l-methamphetamine. Subsequently, this has promoted the design of a novel, more potent, MAO-B inhibitor PF9601N, which also has neuroprotective and antioxidant properties. The aim of this work was to investigate the effect of treatment with PF9601N on its own phase I hepatic metabolism. Kinetic parameters of PF9601N CYP-dependent N-dealkylation reaction was also studied and compared with those of l-deprenyl. METHODS: C57BL/6 mice were treated with PF9601N for 4 days. After CYP content and related monooxygenase activities were assayed in liver microsomes of control and treated animals. RESULTS: CYP activities, cytochrome b5 content, NADPH-cytochrome P450 reductase and various monooxygenase activities were unaffected by in vivo PF9601N treatment. With microsomes from both control and treated mice, the PF9601N-dealkylation product, FA72, was the only detected metabolite with its formation rate following an hyperbolic, Michaelis-Menten curve. Among various inhibitors, only ketoconazole inhibited the FA72 formation rate, indicating a major involvement for CYP3A. Apparent Km and Vmax values generated by human liver microsomes were similar to those found with mouse microsomes. Ketoconazole inhibition indicates that CYP3A is one of the major enzymes involved in PF9601N metabolism also by human liver microsomes. In mouse liver microsomes, the intrinsic clearance of PF9601N was significantly lower than that of l-deprenyl suggestive of an improved bioavailability for the former. CONCLUSION: The observed favourable metabolic profile may suggest suitability of PF9601N for clinical use.
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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 | 0.001 |
| 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) | 0.001 | 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".