Identification of novel antifungal agents: antimicrobial evaluation, SAR, ADME–Tox and molecular docking studies of a series of imidazole derivatives
Bibliographic record
Abstract
Thirty-four imidazole-based compounds synthesized by one-pot catalytic method were evaluated for their antifungal and antibacterial activities against several fungal and bacterial strains. None of the compounds had antibacterial activity. Interestingly, compounds 1, 2, 3, 10 and 15 displayed a strong antifungal activity against all the tested fungal species, while compounds 5, 7, 9, 11, 21 and 27 showed a moderate antifungal activity. To better understand the biological activity of the most active compounds ADME–Tox and molecular docking studies were carried out. Interestingly, compounds 1, 2, 3, 7, 10 and 15 showed excellent bioavailability. In addition, compounds 1, 2 and 3, exhibited good toxicity profiles. Docking studies of the two most active compounds 2 (IC50 of 95 ± 7.07 μM) and 10 (IC50 of 235 ± 7.07 μM) suggested that they might act by inhibiting the fungal lanosterol 14α-demethylase. Therefore, these novel antifungal agents merit further characterization for the development of new antifungal therapeutics.
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 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 | 0.000 |
| 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".