Identification of Novel Inhibitors of the SARS Coronavirus Main Protease 3CL<sup>pro</sup>
Bibliographic record
Abstract
SARS (severe acute respiratory syndrome) is caused by a newly discovered coronavirus. A key enzyme for the maturation of this virus and, therefore, a target for drug development is the main protease 3CL(pro) (also termed SARS-CoV 3CL(pro)). We have cloned and expressed in Escherichia coli the full-length SARS-CoV 3CL(pro) as well as a truncated form containing only the catalytic domains. The recombinant proteins have been characterized enzymatically using a fluorescently labeled substrate; their structural stability in solution has been determined by differential scanning calorimetry, and novel inhibitors have been discovered. Expression of the catalytic region alone yields a protein with a reduced catalytic efficiency consistent with the proposed regulatory role of the alpha-helical domain. Differential scanning calorimetry indicates that the alpha-helical domain does not contribute to the structural stability of the catalytic domains. Analysis of the active site cavity reveals the presence of subsites that can be targeted with specific chemical functionalities. In particular, a cluster of serine residues (Ser139, Ser144, and Ser147) was identified near the active site cavity and was susceptible to being targeted by compounds containing boronic acid. This cluster is highly conserved in similar proteases from other coronaviruses, defining an attractive target for drug development. It was found that bifunctional aryl boronic acid compounds were particularly effective at inhibiting the protease, with inhibition constants as strong as 40 nM. Isothermal titration microcalorimetric experiments indicate that these inhibitors bind reversibly to 3CL(pro) in an enthalpically favorable fashion, implying that they establish strong interactions with the protease molecule, thus defining attractive molecular scaffolds for further optimization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".