Inhibitory effects of phenolic compounds from blueberry leaf on <i>α</i>‐amylase and <i>α</i>‐glucosidase: kinetics, mode of action, and molecular interactions
Bibliographic record
Abstract
Abstract Background The interactions between blueberry leaf polyphenols (BLPs) and digestive enzymes were analyzed using multiple techniques to gain insights into their inhibitory effects on enzyme kinetics and modes of action. Results 3‐ O ‐Caffeoylquinic acid (3‐CQA) was the most abundant compound identified. Quercetin (QR) exhibited the strongest inhibitory activity against α ‐amylase ( α ‐AMY) and α ‐glucosidase ( α ‐GLU). The BLP extracts acted as typical mixed‐type inhibitors for both digestive enzymes, showing stronger inhibition of α ‐GLU (IC50 = 7.36 ± 0.03 μg mL −1 ) than α ‐AMY (IC50 = 12.52 ± 0.65 μg mL −1 ). Stern–Volmer plots showed static quenching of enzyme fluorescence intensity. The quenching and binding constants of α ‐GLU were higher than those of α ‐AMY, showing greater affinity of the former for BLP. The conformational changes of 3‐CQA and QR in the BLP were studied at the molecular level. The stability of the complexes formed followed this order: α ‐GLU‐3‐CQA > α ‐AMY‐QR > α ‐GLU‐QR > α ‐AMY‐3‐CQA. This trend supported the observation that QR had a greater impact on α ‐AMY conformation, whereas 3‐CQA more effectively altered α ‐GLU. Conclusion These findings elucidated the inhibitory mechanisms of BLP on glucose‐regulating enzymes, providing novel insights relevant for the treatment of diabetes. © 2025 Society of Chemical Industry.
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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 | 0.001 |
| 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".