New α-glucosidase inhibitors and antioxidants in optimized <i>Psychotria malayana</i> Jack leaves extract identified by gC-MS-based metabolomics and <i>in silico</i> molecular docking
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our earlier research demonstrated α-glucosidase inhibitory (AGI) and antioxidant activities of the optimised extract of Psychotria malayana leaves. It was reported having numerous compounds, although it was unclear which compounds exhibit the bioactivities as well as their binding interaction to the enzyme. This study aimed to identify the compounds possessing AGI and antioxidant activities in the extract utilising GC-MS-based metabolomics, and to analyse the ligand-enzyme binding interactions via in-silico molecular docking. A partial least square was employed to correlate the metabolite profile and bioactivities. The loading plot reveals the bioactive compounds in this extract. The AGI activity of 1-cyclohexene-1-carboxylic, propanoic, butanedioic and D-gluconic acid together with the antioxidant activity of some compounds were reported for the first time through this study. The docking study reveals that all compounds, except for 1-cyclohexene-1-carboxylic acid, exhibit binding to the enzyme’s catalytic site. This discovery demonstrates the potential of this plant for diabetes therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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