Caffeic Acid Phenethyl Ester and Its Amide Analogue Are Potent Inhibitors of Leukotriene Biosynthesis in Human Polymorphonuclear Leukocytes
Bibliographic record
Abstract
BACKGROUND: 5-lipoxygenase (5-LO) catalyses the transformation of arachidonic acid (AA) into leukotrienes (LTs), which are important lipid mediators of inflammation. LTs have been directly implicated in inflammatory diseases like asthma, atherosclerosis and rheumatoid arthritis; therefore inhibition of LT biosynthesis is a strategy for the treatment of these chronic diseases. METHODOLOGY/PRINCIPAL FINDINGS: Analogues of caffeic acid, including the naturally-occurring caffeic acid phenethyl ester (CAPE), were synthesized and evaluated for their capacity to inhibit 5-LO and LTs biosynthesis in human polymorphonuclear leukocytes (PMNL) and whole blood. Anti-free radical and anti-oxidant activities of the compounds were also measured. Caffeic acid did not inhibit 5-LO activity or LT biosynthesis at concentrations up to 10 µM. CAPE inhibited 5-LO activity (IC(50) 0.13 µM, 95% CI 0.08-0.23 µM) more effectively than the clinically-approved 5-LO inhibitor zileuton (IC(50) 3.5 µM, 95% CI 2.3-5.4 µM). CAPE was also more effective than zileuton for the inhibition of LT biosynthesis in PMNL but the compounds were equipotent in whole blood. The activity of the amide analogue of CAPE was similar to that of zileuton. Inhibition of LT biosynthesis by CAPE was the result of the inhibition of 5-LO and of AA release. Caffeic acid, CAPE and its amide analog were free radical scavengers and antioxidants with IC(50) values in the low µM range; however, the phenethyl moiety of CAPE was required for effective inhibition of 5-LO and LT biosynthesis. CONCLUSIONS: CAPE is a potent LT biosynthesis inhibitor that blocks 5-LO activity and AA release. The CAPE structure can be used as a framework for the rational design of stable and potent inhibitors of LT biosynthesis.
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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 | 0.000 |
| 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) | 0.002 | 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".