Unraveling enantioselective metabolism: Human cytochrome P450s in arachidonic acid biotransformation
Bibliographic record
Abstract
Arachidonic acid (AA) is a polyunsaturated essential fatty acid and a precursor for eicosanoids. It is metabolized by cyclooxygenases, lipoxygenases, and cytochrome P450 (P450) enzymes, which convert AA into hydroxyeicosatetraenoic acids (HETEs) and epoxyeicosatrienoic acids (EETs), chiral eicosanoids with distinct biological activities. Although racemic HETEs and EETs have been studied in cardiovascular diseases, the enantiospecific roles of their enantiomers and the enantioselectivity of P450 enzymes remain largely unexplored. This study aimed to investigate the enantioselective metabolism of AA by human recombinant P450 enzymes, focusing on the formation of R/S-HETEs and (R, S)/(S,R)-EETs. Metabolites were analyzed using liquid chromatography electrospray ionization mass spectrometry. CYP1A2 exhibited the highest activity in forming R-midchain HETEs, followed by CYP3A4. CYP2C19 was the most active enzyme in producing R-subterminal HETEs, with CYP1A2 and CYP1A1, CYP4F3B, and CYP2E1 ranking second. Similarly, CYP2C19 showed the highest activity in generating S-midchain and S-subterminal HETEs, with CYP3A4, CYP2C8, CYP1A1, and CYP1A2 contributing to varying degrees. For EETs, CYP2C19 and CYP1A2 primarily catalyzed the formation of both (R, S)/(S, R)-EETs. These findings emphasize the significant roles of CYP2C19 and CYP1A2 in the regio- and stereoselective metabolism of HETEs and EETs, highlighting their contributions to lipid signaling and potential physiological implications. SIGNIFICANT STATEMENT: This work highlights the importance of profiling P450 with respect to their enantioselectivity in arachidonic acid metabolism. The findings indicate that major P450 differ in the magnitude of their hydroxyeicosatetraenoic acid and epoxyeicosatrienoic acid formation rates, which is a significant for studying diseases that is known to be influenced by alterations in these pathways. Altered enantioselectivity could have implications in diseases such as hypertension, cancer, inflammation, and cardiovascular disorders.
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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 | 0.000 | 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 | 0.000 |
| 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 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".