Chalcone Derived from a Natural Product: An Integrated Approach of Quantum Chemical Calculations, Molecular Docking, ADME and Neuromodulation on Serotonergic Receptors in Adult Zebrafish
Bibliographic record
Abstract
Anxiety disorders are conditions characterized by heightened responses to perceived threats, resulting in symptoms that negatively affect everyday life. This study investigates the anxiolytic effect of a natural chalcone isolated from Croton anisodontus Müll.Arg. focusing on its modulation of anxiolytic activity in modulating anxiolytic activity via GABAergic and serotonergic neurotransmission in an adult zebrafish model. The acute toxicity of the chalcone was assessed during a 96-hour period, and the anxiolytic behavior of fish treated with chalcone was evaluated using light/dark tests and open field tests (n=6 animals per group). Chalcone showed no signs of toxicity for up to 96 hours of analysis. The results demonstrated a significant anxiolytic effect of the synthesized chalcone, suggesting its therapeutic potential in treating anxiety. Furthermore, the findings indicate that this anxiolytic effect is mediated by serotonergic and non-GABAergic neurotransmitter systems. From molecular docking simulations, it was possible to estimate that the 5-HT3A receptor (5-HT3AR) pathway is the most likely target way for the chalcone to act. MPO-based ADME predictions indicate that the chalcone exhibits high cellular permeability suggest that chalcone has a high cellular permeability and can distribute better in biological tissues than in blood plasma, supporting its potential to act in the CNS by crossing the blood-brain barrier. These findings enhance the understanding of contribute to understanding of chalcone's mechanisms of action and provide a solid basis for future studies aimed at developing new therapeutic strategies to develop new therapeutic approaches for anxiety disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".