Antibiofilm and quorum sensing inhibitory activity of<i>Achyranthes aspera</i>on cariogenic<i>Streptococcus mutans</i>: An<i>in vitro</i>and<i>in silico</i>study
Bibliographic record
Abstract
CONTEXT: Traditionally, many cultures use chewing sticks for oral hygiene maintenance. When properly used, these chewing sticks are found to be efficient due to the combined effect of mechanical cleaning, enhanced salivation and the antimicrobial action of leached out plant compounds. OBJECTIVE: Achyranthes aspera L. (Amaranthaceae), an ethanomedicinal herb was evaluated for its potential to inhibit growth and biofilm formation by cariogenic isolate Streptococcus mutans as an alternative means of caries management by quorum quenching (QQ). MATERIALS AND METHODS: Biofilm forming cariogenic isolates were isolated and their susceptibility to the petroleum ether, benzene, methanol, aqueous extracts of A. aspera was evaluated. Gas chromatography-mass spectrometry (GC-MS), phytochemical analyses and structure-based virtual screening for their quorum sensing (QS) inhibitory activities, drug-likeness and bioavailability were also carried out. RESULTS: The biofilm inhibition percentage obtained for methanol, benzene, petroleum ether and aqueous extracts (125 µg/mL) were ≤94%, ≤74%, ≤62% ≤42%, respectively. GC-MS analyses indicated 61 compounds, of which betulin recorded efficient interaction exhibiting comparable binding energy of -8.72 with S. mutans glycosyltransferase (GTF-SI) whereas 3,12-oleandione exhibited binding energy -5.92 with OmpR subfamily QS regulatory DNA-binding response regulator. Computer-assisted molecular descriptor and Lipinski's rule violation calculation uncovered the presence of more drug-like compounds. DISCUSSION AND CONCLUSION: Anticaries bioactive compounds of A. aspera with higher QS response regulator binding energy, low toxicity and optimal pharmacokinetic properties were revealed. These compounds with possible QQ ability hold the potential for use as anticaries drug leads and antibiofilm preventative medicine.
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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".