Virtual screening of novel pyridine derivatives as effective inhibitors of DNA gyrase (GyrA) of salmonella typhi
Bibliographic record
Abstract
In a bid to discovering novel antibiotics to combat growing trend of multi-drug resistance strains of Salmonella typhi, 48 new pyridine derivatives with significant inhibitory activities against the aforementioned bacterium were subjected to molecular docking against DNA gyrase protease of the bacterium, drug likeness evaluation and pharmacokinetics profiling. All the 48 leads displayed better binding affinity values when compared with Amoxicillin, Ciprofloxacin, Ceftriaxone, Ampicillin, and chloramphenicol, the standard antibiotics used herein for quality assurance. Furthermore, the majority of the compounds were, however, screened out due to their poor pharmacokinetics profiles and drug-likeness. Only five compounds emerged as the most promising leads and they include C4 with binding affinity of -8.0 kcal/mol, C8 (-8.6 kcal/mol), C9 (-8.1 kcal/mol), C26 (-8.3 kcal/mol), and C27 (-8.0 kcal/mol). These compounds not only displayed better binding affinity when compared with the reference antibiotics but also exhibit different modes of interactions with the target protease of the bacterium making them more potent and drug like. Toxicity evaluation of the leads also revealed that the compounds are neither tumorigenic nor mutagenic. In view of the excellent binding affinity, high pharmacokinetics profile and positive drug-likeness of the novel ligands, we recommend these promising compounds for in vitro and in vivo studies in order to discover novel antibiotics that could curb the dangerous trend of multiple drug resistance by Salmonella typhi.
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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".