Inhibition of the 3CL Protease and SARS-CoV-2 Replication by Dalcetrapib
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) 3CL protease is a promising target for inhibition of viral replication by interaction with a cysteine residue (Cys145) at its catalytic site. Dalcetrapib exerts its lipid-modulating effect by binding covalently to cysteine 13 of a cholesteryl ester transfer protein. Because 12 free cysteine residues are present in the 3CL protease, we investigated the potential of dalcetrapib to inhibit 3CL protease activity and SARS-CoV-2 replication. Molecular docking investigations suggested that dalcetrapib-thiol binds to the catalytic site of the 3CL protease with a delta G value of −8.5 kcal/mol. Dalcetrapib inhibited both 3CL protease activity in vitro and viral replication in Vero E6 cells with IC 50 values of 14.4 ± 3.3 μM and an EC 50 of 17.5 ± 3.5 μM (mean ± SD). Near-complete inhibition of protease activity persisted despite 1000-fold dilution after ultrafiltration with a nominal dalcetrapib-thiol concentration of approximately 100 times below the IC 50 of 14.4 μM, suggesting stable protease–drug interaction. The inhibitory effect of dalcetrapib on the SARS-CoV-2 3CL protease and viral replication warrants its clinical evaluation for the treatment of COVID-19.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".