Synthesis of novel ketene dithioacetals via one pot reaction: Molecular modelling in-silico Admet studies and antimicrobial activity
Bibliographic record
Abstract
A simple and efficient method for the synthesis of fifteen novel ketene dithioacetals (2-(6-amino5-cyano-4-aryl-4H-1,3-dithiin-2-ylidene) malononitrile) via a one-pot three-component reaction of activated methylene group malononitrile with carbon disulfide in the presence of arylidene malononitriles were reported. The effects of LiOH.H2O as a base at different concentrations have been investigated and can provide products in good yields at 40-50ºC temperature (54-89%). All the synthesized ketene dithioacetals compounds (MCB1-MCB15) were checked for favorable pharmacokinetic param¬eters along with toxicities which are based on drug-likeness explained by Lipinski’s rule of five by Med chem designer software correlated with that of pkCSM online tool. Explorations of synthesized ketene dithioacetals compounds for the antimicrobial study were found to be effective towards Staphylococcus aureus (MCB5 and MCB13) with a zone of inhibition at 26mm and 22mm which is compared to that of standard ciprofloxacin (26mm). This made our study to explore the inhibition mechanism with the help of molecular docking studies with possible binding energies (-6.4 to -8.9 kJ/mol) by pyrx 0.8 software to represent a good prediction of interactions between the ligand and protein (2XCT). Further evaluation of druggability and ADMET predictions compounds MCB5 and MCB13 were found to be effective. Based on the in-vitro and in-silico studies a series of ketene dithioacetals compounds may be helpful for further studying SAR and designing more potent antimicrobials.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".