Glycogen Phosphorylase-a is a Common Target for Anti-Diabetic Effect of Iridoid and Secoiridoid Glycosides
Bibliographic record
Abstract
PURPOSE: Diabetes mellitus is characterized by hyperglycemia resulting from defects in insulin secretion, action or both. The use of medicinal plants for the treatment of diabetes mellitus dates back from the Ebers papyrus of about 1550 B.C. One of the major problems with herbal drugs is that the active ingredients are not well defined. It is important to know the active components and their molecular interactions which will help to analyze their therapeutic efficacy and also to standardize the product. There are a number of medicinal plants known for their anti-diabetic effect that possess similarities in their active chemical components, e.g. iridoid and secoiridoid glycosides. METHODS: In this study, we have compared the structure of various iridoid and secoiridoid glycosides to design a novel pharmacophore. We further developed a structure-activity relationship for the inhibition of glycogen phosphorylase-a. CONCLUSION: By using docking studies, we are proposing, for the first time, that inhibition of glycogen phosphorylase-a activity is a common target for iridoids and secoiridoids to elicit anti-diabetic effects. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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) | 0.002 | 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".