Molecular Study of Acalypha indica to Leptin, Alpha Glucosidase, and its Antihyperglycemic Effect on Alpha Glucosidase
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Bibliographic record
Abstract
The purpose of this study is to find potential inhibitors of leptin as a proinflammatory adipokine and alpha glucosidase as an enzyme that mediate hyperglycaemia; to alter the chronic complications of obesity from herbal Acalypha indica (Ai). This study was conducted using in silico molecular docking to evaluate the Ai compounds interaction with leptin and alpha glucosidase. The in vitro assay to alpha glucosidase was done to explore antihyperglycemic effect of Ai, as hyperglycaemia is the key process of chronic complication of obesity. Material and Methods: Protein target were leptin and alpha glucosidase; compounds from Ai plant were repundusinic, mauritanin, hesperetin, acaindinin, and glucogalin in pdb format. Molecular docking using autodock vinna. In vitro assay of Ai antihyperglycemic activity was done to alpha glucosidase and was define as IC50 level. Result: The results from the docking analysis demonstrated that compounds from Ai roots contain antihyperglycemic-antiobesity activity which acted by inhibiting leptin and alpha glucosidase receptors. Repundusininc and mauritanin compounds contain hydrogen bond with the greatest leptin enhancer activity on Ser9, Thr35, Glu8, Ser9, Thr25, Gln111, Lys211, Leu7 for repundisinic and Glu8, Thr25, Gly112 and Leu7 for mauritanin. Hesperetin, acaindinin and glucogallin were the most identical compounds with similar affinity binding value to alpha glucosidase. Ai roots was already proven as anti-hyperglycemic-antiobesity which was further confirmed by in vitro assay to alpha glucosidase (IC50 19,429 g/ml.). Conclusion: The results demonstrated that Ai have anti hyperglycaemic-antiobesity effects and was found to be potentially as antihyperglycemic by in vitro assay to alpha glucosidase.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it