Regulation of Cytochrome P450 by Posttranslational Modification
Bibliographic record
Abstract
Cytochrome P450s are a family of enzymes represented in all kingdoms with expression in many species. Over 3,000 enzymes have been identified in nature. Humans express 57 putatively functional enzymes with a variety of critical physiological roles. They are involved in the metabolic oxidation, peroxidation, and reduction of many endogenous and exogenous compounds including xenobiotics, steroids, bile acids, fatty acids, eicosanoids, environmental pollutants, and carcinogens [Nelson, D. R., Kamataki, T., Waxman, D. J., Guengerich, F. P., Estabrook, R. W., Feyereisen, R., Gonzalez, F. J., Coon, M. J., Gunsalus, I. C., Gotoh, O. (1993) The P450 superfamily: update on new sequences, gene mapping, accession numbers, early trivial names of enzymes, and nomenclature. DNA Cell Biol. 12(1):1-51.] The development of numerous diseases and disorders including cancer and cardiovascular and endocrine dysfunction has been linked to P450s. Several levels of regulation, including transcription, translation, and posttranslational modification, participate in maintaining the proper function of P450s. Modifications including phosphorylation, glycosylation, nitration, and ubiquitination have been described for P450s. Their physiological significance includes modulation of enzyme activity, targeting to specific cellular compartments, and tagging for proteasomal degradation. Knowledge of P450 posttranslational regulation is derived from studies with relatively few enzymes. In many cases, there is only enough evidence to suggest the occurrence and a possible role for the modification. Thus, many P450 enzymes have not been fully characterized. With the introduction of current proteomics tools, we are primed to answer many important questions regarding regulation of P450 in response to a posttranslational modification. This review considers regulation of P450 in a context that describes the potential role and physiological significance of each modification.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".