Discovery of Potent Angiotensin-Converting Enzyme Inhibitors in Pomegranate as a Treatment for Hypertension
Bibliographic record
Abstract
Pomegranate ( Punica granatum L.) is associated with numerous health benefits due to its high levels of antioxidant polyphenolic substances. Since pomegranate extract has been shown to inhibit angiotensin-converting enzyme (ACE), the potential inhibitory effect of most of its main constituents against ACE is unknown. Therefore, we tested the activities of 24 major compounds, the majority of which significantly inhibited ACE. Notably, pedunculagin, punicalin, and gallagic acid were the most effective ACE inhibitors with IC 50 values of 0.91, 1.12, and 1.77 μM, respectively. As demonstrated in molecular docking studies, compounds block ACE by forming multiple hydrogen bonds and hydrophobic interactions with catalytic residues and zinc ions in ACE’s C- and N-domains, consequently inhibiting ACE’s catalytic activity. Also, the most active pedunculagin stimulated nitric oxide (NO) production, activated the endothelial nitric oxide synthase enzyme (eNOS), and significantly increased eNOS protein expression levels up to 5.3-fold in EA.hy926 cells. Furthermore, pedunculagin increased in cellular calcium (Ca 2+ ) concentration promoted eNOS enzyme activation and reduced the production of reactive oxygen species (ROS). In addition, the active compounds improved glucose uptake in insulin-resistant C2C12 skeletal muscle cells in a dose-dependent manner. The results of these computational, in vitro, and cellular experiments provide further evidence to the traditional medicine that involves using pomegranates to treat cardiovascular diseases like hypertension.
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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".