Antioxidant, Enzyme and Molecular Docking Tyrosinase Inhibitory Activities of Major Polyphenols in <i>Boscia coriacea</i> Graells, <i>Grewia erythraea</i> (Schweinf.) Chiov., <i>Ochradenus baccatus</i> Delile, and <i>Orthosiphon pallidus</i> Royle Ex Benth.
Bibliographic record
Abstract
Boscia coriacea Graells (BC), Grewia erythraea (Schweinf.) Chiov. (GE), Ochradenus baccatus Delile (OB), and Orthosiphon pallidus Royle ex Benth. (OP) are medicinal plants used in Djibouti. They were evaluated to determine their total phenolic content (TPC), flavonoid content (TFC), and phytochemical profile using HPLC-MS/MS. Additionally, their antioxidant capacity was assessed through five various methods. Enzymatic activities were also measured, focusing on acetylcholinesterase (AChE), butyrylcholinesterase (BChE), α-amylase, α-glucosidase, and tyrosinase. OP extract had the highest TPC and exhibited the best antioxidant capacity, whereas OB and BC extracts had the highest TFC. Twenty-seven compounds were identified and quantified by LCMS. GE extract demonstrated the highest AChE activity, whereas OP extract had the highest BChE activity. BC was most active against α-amylase and α-glucosidase, and only GE and OP extracts showed tyrosinase inhibition in vitro. In silico analysis, the compounds were optimized and docked to the human tyrosinase-related protein 1 using AutoDock Vina, with absorption, distribution, metabolism, and elimination to evaluate their suitability based on key therapeutic criteria. Chlorogenic, neochlorogenic, gallic acids, and quercetin emerged as promising tyrosinase inhibitors. These plants can be a viable source in the prevention and treatment related to tyrosinase enzyme inhibition.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".