Antioxidant and antimicrobial effects of essential oils from two salvia species with in vitro and in silico analysis targeting 1AJ6 and 1R4U proteins
Bibliographic record
Abstract
The Middle Atlas is a Moroccan territory that serves as an abode to plants with incredible biodiversity, of which aromatic and medicinal plants that have been of folkloric use are a significant component. However, their effective utilization in modern medicine requires the characterization of their phytochemicals to facilitate their entry into drug discovery pipelines. Hence, this study aimed to characterize and investigate the antioxidant activity and antimicrobial effects of the essential oils (EOs) of Salvia lavandulifolia subsp. mesatlantica and Salvia officinalis L. by use of in vitro and in silico assays. Ten phytochemicals were identified in the EOs of S. lavandulifolia, while twenty phytochemicals were identified in S. officinalis. Camphor was the most abundant compound in both species, comprising 26.70% and 39.24% of the EOs of S. lavandulifolia and S. officinalis, respectively. The EOs of both plants exhibited significant DPPH free radical scavenging activity, with S. lavandulifolia and S. officinalis showing estimated scavenging rates of 92.97% and 75.20%, respectively. In terms of Ferric Reducing Antioxidant Power (FRAP), S. officinalis demonstrated a higher value (72.08%) compared to that of S. lavandulifolia (64.61%). Evaluation of the antimicrobial effects of the EOs of S. officinalis and S. lavandulifolia against microorganisms revealed bactericidal activities against Proteus mirabilis and Bacillus subtilis at low concentrations. It showed bactericidal activities against Staphylococcus aureus and Candida albicans at a relatively higher concentration. Molecular docking of antioxidant and antimicrobial proteins offers significant insights into ligand-protein interactions, facilitating the development of innovative therapeutics from the current study. Ultimately, this study identified the phytochemical composition of S. lavandulifolia and S. officinalis and highlighted their potential for therapeutic discovery.
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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 | 0.001 |
| 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".