Insulin–Mimetic Dihydroxanthyletin-Type Coumarins from Angelica decursiva with Protein Tyrosine Phosphatase 1B and α-Glucosidase Inhibitory Activities and Docking Studies of Their Molecular Mechanisms
Bibliographic record
Abstract
As a traditional medicine, Angelica decursiva has been used for the treatment of many diseases. The goal of this study was to evaluate the potential of four natural major dihydroxanthyletin-type coumarins—(+)-trans-decursidinol, Pd-C-I, Pd-C-II, and Pd-C-III—to inhibit the enzymes, protein tyrosine phosphatase 1B (PTP1B) and α-glucosidase. In the kinetic study of the PTP1B enzyme’s inhibition, we found that (+)-trans-decursidinol, Pd-C-I, and Pd-C-II led to competitive inhibition, while Pd-C-III displayed mixed-type inhibition. Moreover, (+)-trans-decursidinol exhibited competitive-type, and Pd-C-I and Pd-C-II mixed-type, while Pd-C-III showed non-competitive type inhibition of α-glucosidase. Docking simulations of these coumarins showed negative binding energies and a similar proximity to residues in the PTP1B and α-glucosidase binding pocket, which means they are closely connected and strongly binding with the active enzyme site. In addition, dihydroxanthyletin-type coumarins are up to 40 µM non-toxic in HepG2 cells and have substantially increased glucose uptake and decreased expression of PTP1B in insulin-resistant HepG2 cells. Further, coumarins inhibited ONOO−-mediated albumin nitration and scavenged peroxynitrite (ONOO−), and reactive oxygen species (ROS). Our overall findings showed that dihydroxanthyletin-type coumarins derived from A. decursiva is used as a dual inhibitor for enzymes, such as PTP1B and α-glucosidase, as well as for insulin susceptibility.
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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".