Flavonoids as dual-target inhibitors against α-glucosidase and α-amylase: a systematic review of in vitro studies
Bibliographic record
Abstract
Diabetes mellitus remains a major global health burden and great attention is directed at natural therapeutics. This systematic review aimed to evaluate the potential of flavonoids as antidiabetic agents through their ability to inhibit α-amylase and α-glucosidase, two key starch digestive enzymes. Six scientific databases were queried up until August 21, 2022, for in vitro studies reporting the IC50 results of purified flavonoids on α-amylase or α-glucosidase, along with the respective data of acarbose control. A total of 339 articles were assessed as eligible and subjected to the data extraction process, resulting in 1643 retrieved structures, 177 compounds of which showed both inhibitions against α-amylase and α-glucosidase. Quality assessment was conducted following a modified CONSORT checklist. The structureactivity relationships revealed that a double bond C2=C3 and a keto group C4=O is essential for simultaneous inhibition. The hydroxyl group at C3 is favourable for α-glucosidase inhibition but detrimental to the effect against α-amylase. Further notable features which affect α-glucosidase and α-amylase inhibition were also discussed. Several limitations were considered, including the inconsistency among included studies, language restriction, and the contemporaneity of the review. In conclusion, the systematic review has summarized some crucial findings in the investigation of flavonoids as dual-target inhibitors against α-glucosidase and α-amylase and proposed several orientations for future research.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| 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 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".