Antidepressant-like effect of dehydrozingerone from Zingiber officinale by elevating monoamines in brain: in silico and in vivo studies
Bibliographic record
Abstract
BACKGROUND: Dehydrozingerone (DHZ) is an active ingredient of Zingiber officinale and structural half analogue of curcumin. In the present study, DHZ was evaluated for monoamine oxidase (MAO) inhibitory activity in silico and antidepressant activity in vivo. METHOD: The binding affinity of DHZ with MAO-A (PDB ID: 2Z5Y) was assessed using Schrodinger's Maestro followed by free energy calculation, pharmacokinetic property prediction using Qikprop and Molecular dynamics simulation using Desmond. In vivo antidepressant activity of DHZ was evaluated on C57 BL/6 male mice using Escilatopram as the standard antidepressant. Open field test (OFT), forced swimming test (FST) and tail suspension test (TST) were used to evaluate the antidepressant effect of the drugs on days 1 and 7. Following the behavioural study, neurotransmitters (noradrenaline, dopamine and serotonin) were estimated using liquid chromatography-mass spectrometry. RESULTS: DHZ demonstrated a greater binding affinity for the MAO-A enzyme compared to moclobemide in silico. Immobility in TST and FST were significantly (p < 0.05) reduced in vivo with 100mg/kg DHZ as compared to respective controls. DHZ treatment was more effective 1 h post treatment compared to vehicle control. A significant increase in levels of neurotransmitters was observed in mice brain homogenate in response to DHZ treatment, reassuring its antidepressant-like potential. CONCLUSION: DHZ demonstrated MAO-A inhibition in silico, and the increased neurotransmitter levels in the brain in vivo were associated with an antidepressant-like effect.
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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) | 0.001 | 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".