Theoretical anti-tuberculosis activity and molecular docking investigation of N-silylated heterocyclic compounds with benzyl chloride catalyzed by ammonium sulfate-doped red algae
Bibliographic record
Abstract
In this charge we designated a Hilbert-Johnson process by coupling of heterocyclic N-silylated with benzyl chloride at 100°C using the calcined red algae (CRA) doped with ammonium sulfate (AS), AS@CRA as a heterogeneous catalyst. The resulting examination systems, which included atomic absorption, BET methodology and X-ray diffraction (XRD), scanning electron microscopy (SEM/EDX), and Fourier transform infrared spectroscopy (FT-IR), were employed to describe these catalysts. The effect of catalyst and alkylated agent were extensively studied. This catalyst can also be recycled several times in this condensation, and lastly, we suggested a probable answer mechanism for this process. Moreover, our molecular docking investigation revealed the anti-tuberculosis potential of the synthesized compounds. Notably, the drug isoniazid exhibited higher binding energies compared to the products 2a, 2b, and 2c. Additionally, the ADME study suggests that highly efficacious synthetic compounds may possess anti-tuberculosis properties.
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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".