Novel Imidazole Derivative AOMI: Enhanced Antibacterial/Anti-Biofilm Properties and Mechanistic Insights
Bibliographic record
Abstract
The research delves into the creation and assessment of an innovative imidazole derivative, AOMI, which shows remarkable antibacterial and anti-biofilm capabilities.The synthesis and evaluation of 2-(2-(anthracen-9-yl)-5-oxoimidazolidin-1-yl)-1methyl-1H-imidazol-4(5H)-one (AOMI), a new imidazole derivative with strong antibacterial and anti-biofilm capabilities, are investigated in this study using molecular docking experiments.AOMI was created by reacting anthracene-9-carbaldehyde with creatinine to obtain the Schiff base (E)-2-(anthracen-9-ylmethyleneamino)-1-methyl-1Himidazol-4(5H)-one (AMMI).The use of techniques like FTIR, 1 H NMR, and 13 C NMR allowed for the confirmation of the produced compounds' structures.The antibacterial tests showed that AOMI was highly effective against S. aureus and E. coli when mixed with amoxicillin, with inhibition zones as large as 22.25 0.30 mm.It should be noted that AOMI outperformed amoxicillin in terms of anti-biofilm activity and had a minimum inhibitory concentration (MIC) of 200 g/mL.Furthermore, DPPH experiments demonstrated that AOMI exhibited antioxidant activity, with scavenging rates reaching a maximum of 79.10% at the dose that was tested.According to the molecular docking data, there were strong contacts with the target protein's active site residues through electrostatic and hydrogen bonding interactions, as evidenced by a binding energy of -30.5897 kcal/mol and an RMSD value of 2.4709 .We need to learn more about how AOMI works and make more imidazole derivatives since these results suggest that it could be a very good way to treat bacterial infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".