Structural Bases for Hesperetin Derivatives: Inhibition of Protein Tyrosine Phosphatase 1B, Kinetics Mechanism and Molecular Docking Study
Bibliographic record
Abstract
In the present study, we investigated the structure-activity relationship of naturally occurring hesperetin derivatives, as well as the effects of their glycosylation on the inhibition of diabetes-related enzyme systems, protein tyrosine phosphatase 1B (PTP1B) and α-glycosidase. Among the tested hesperetin derivatives, hesperetin 5-O-glucoside, a single-glucose-containing flavanone glycoside, significantly inhibited PTP1B with an IC50 value of 37.14 ± 0.07 µM. Hesperetin, which lacks a sugar molecule, was the weakest inhibitor compared to the reference compound, ursolic acid (IC50 = 9.65 ± 0.01 µM). The most active flavanone hesperetin 5-O-glucoside suggested that the position of a sugar moiety at the C-5-position influences the PTP1B inhibition. It was observed that the ability to inhibit PTP1B is dependent on the nature, position, and number of sugar moieties in the flavonoid structure, as well as conjugation. In the kinetic study of PTP1B enzyme inhibition, hesperetin 5-O-glucoside led to mixed-type inhibition. Molecular docking studies revealed that hesperetin 5-O-glucoside had a higher binding affinity with key amino residues, suggesting that this molecule best fits the PTP1B allosteric site cavity. The data reported here support hesperetin 5-O-glucoside as a hit for the design of more potent and selective inhibitors against PTP1B in the search for a new anti-diabetic treatment.
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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) | 0.000 | 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) | 0.001 | 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".