Designing Inhibitors for the SARS CoV Main Protease as Anti-SARS Drugs
Bibliographic record
Abstract
Severe Acute Respiratory Syndrome (SARS) is a serious respiratory illness reported in parts of Asia and Canada. A novel coronavirus (CoV) has been isolated and identified as the cause of the SARS for which there is currently no effective treatment. Given the epidemic, the rapid development of efficacious antiviral drugs is needed. The key replicative enzyme SARS CoV main protease (Mpro) represents an attractive target for antiviral chemotherapy. Detailed structural study of the substrate binding cavity led to the generation of a 3-D pharmacophore. Subsets of chemical structures were extracted from the commercial databases by using the defined pharmacophore. Compound mapping to the pharmacophore were docked into the substrate-binding cavity and scored. The selected chemicals were assayed against the SARS CoV Mpro for their inhibitory activity. Three of the compounds showed significant inhibition of the SARS CoV Mpro at low micromolar concentration. This study provides potential lead compounds for specific SARS CoV protease inhibitors. It also signifies the utility of computational techniques for rapid discovery of inhibitors for novel targets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".