In Vitro and In Silico Studies of Antimicrobial, and Antioxidant Activities of Chemically Characterized Essential Oil of Artemisia flahaultii L. (Asteraceae)
Bibliographic record
Abstract
The present study investigated the antioxidant and antimicrobial activities as well as characterized the chemical composition of the essential oils (EO) isolated from Artemisia flahaultii (EOF). EOF was extracted using hydro-distillation, and the chemical composition of EOF was ascertained by gas chromatography coupled with mass spectrometry (GC/MS). To assess antioxidant capacity, three tests were used: the 2,2-diphenyl-1-picrylhydrazil (DPPH), the total antioxidant capacity (TAC) and the ferric-reducing antioxidant power (FRAP) test. The antimicrobial activity of EOF was investigated using the diffusion assay and minimal inhibitory concentration assays (MICs). By use of in silico structure–activity simulations, the inhibitory potency against nicotinamide adenine dinucleotide phosphate (NADPH), physicochemical characters, pharmaco-centric properties and absorption, distribution, metabolism, excretion (ADME) characteristics of EOF were determined. GC/MS analysis reveals 25 components majorly composed of D-Limonene (22.09%) followed by β-pinene (15.22%), O-cymene (11.72%), β-vinylnaphthalene (10.47%) and benzene 2,4-pentadiynyl (9.04%). The capacity of DPPH scavenging by EOF scored an IC50 of 16.00 ± 0.20 µg/mL. TAC revealed that the examined oils contained considerable amounts of antioxidants, which were determined to be 1094.190 ± 31.515 mg ascorbic acid equivalents (AAE)/g EO. Results of the FRAP method showed that EOF exhibited activity with EC50 = 6.20 ± 0.60 µg/mL. Values for minimal inhibitory concentration (MIC) against certain clinically important pathogenic bacteria demonstrate EOF’s potent antibacterial activity. MIC values of 1.34, 1.79, and 4.47 μg/mL against E. coli, B. subtilis and S. aureus were observed respectively. EOF exhibited significant antifungal activities against two stains of fungi: F. oxysporum and C. albicans, with values of 10.70 and 2.23 μg/mL, respectively. Of the total, 25 essential oils were identified. 2,4-Di-tert-butylphenol and capillin were the most active molecules against NADPH. The ADME prediction revealed that EOF was characterized by useful physicochemical characteristics and pharmaco-centric properties. The findings of this study show that the EOF can be used as an alternative to treat microbial resistance. Based on the in silico studies, EOF can be used as an “eco-friendly” NADPH inhibitor.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".