Use of recombinant human ferrochelatase as a sensitive bioassay for N-alkylprotoporphyrin IX formed after interaction of porphyrinogenic xenobiotics with rat liver microsomes
Bibliographic record
Abstract
Several porphyrinogenic xenobiotics elicit mechanism-based inactivation of cytochrome P450 (CYP) isozymes, leading to the formation of N-alkylprotoporphyrin IX (N-alkylPP), a potent inhibitor of ferrochelatase, the terminal enzyme in heme biosynthesis. Recognizing their role in experimental porphyria, our long term objective is the establishment of an appropriate in vitro system for the detection and quantification of N-alkylPPs, formed in human liver after the administration of potential porphyrinogenic compounds. In a previous study, we used a combination of thin-layer chromatography and UV-visible spectrophotometry to isolate and identify N-alkylPPs after incubating porphyrinogenic compounds with rat liver microsomes. However, the overall yield of N-alkylPPs was low, and it was concluded that in vitro systems, such as human lymphoblastoid microsomal preparations containing single cDNA-expressed human cytochrome P450 (CYP) isozymes, do not contain sufficient CYP for in vitro studies designed to isolate N-alkylPP. In the present study we demonstrate that purified recombinant human ferrochelatase (FC) provides an extremely sensitive bioassay system for N-alkylPPs and is capable of detecting N-alkylPP in the 10-6nmol range. Therefore, we propose that this bioassay system might allow the use of human lymphoblastoid microsomal preparations containing single cDNA-expressed human CYP isozymes to detect N-alkylPP produced after mechanism-based (catalysis-based) CYP inactivation. If this is found to be correct it will facilitate identification of potentially porphyrinogenic drugs prior to administration to humans.Key words: ferrochelatase, N-alkylprotoporphyrin IX, porphyria, mechanism-based inactivation.
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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 | 0.001 | 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 | 0.000 | 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 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".