Novel pseudonucleosides and sulfamoyl-oxazolidinone <i>β</i> - <i>D</i> -glucosamine derivative as anti-COVID-19: design, synthesis, and <i>in silico</i> study
Bibliographic record
Abstract
New pseudonucleosides containing cyclic sulfamide moiety and sulfamoyl β-D-glucosamine derivative are described. These pseudonucleosides are synthesized in good yields starting from chlorosulfonyl isocyanate and β-D-glucosamine hydrochloride in five steps; (protection, acetylation, removal of the Boc group, sulfamoylation, and cyclization). Further, novel glycosylated sulfamoyloxazolidin-2-one is prepared in three steps; carbamoylation, sulfamoylation, and intramolecular cyclization. The structures of the synthesized compounds were confirmed by usual spectroscopic and spectrometric methods NMR, IR, MS, and EA. Interesting molecular docking of the prepared pseudonucleosides and (Beclabuvir, Remdesivir) drugs with SARS-CoV-2/Mpro (PDB:5R80) was conducted using the same parameters for a fair comparison. A low binding affinity of the synthesized compounds compared to the Beclabuvir and other analysis showed that pseudonucleosides have the ability to inhibit SARS-CoV-2. After the motivating results of molecular docking study, the complex between the SARS-CoV-2 Mpro and compound 7 was subjected to 100 ns molecular dynamics (MD) simulation using Desmond module of Schrodinger suite, during which the receptor-ligand complex showed substantial stability after 10 ns of MD simulation. Also, we studied the prediction of absorption, distribution, properties of metabolism, excretion, and toxicity (ADMET) of the synthesized compounds.Communicated by Ramaswamy H. Sarma
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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".