Large Library Docking and Biophysical Analysis of Small-Molecule TMPRSS2 Inhibitors
Bibliographic record
Abstract
Transmembrane protease serine-2 (TMPRSS2) is an essential host entry factor in human airways for SARS-CoV-2 and influenza A/B and has presented as a target for antiviral drug development; however, no clinically viable oral small-molecule TMPRSS2 inhibitors have been developed to date. Here, we perform two large-scale docking campaigns to identify covalent and noncovalent TMPRSS2 small-molecule inhibitors using a homology model and crystal structure. We establish a pipeline to rapidly screen TMPRSS2 inhibitors and then interrogate the potency, selectivity, and biophysical properties of covalent and noncovalent inhibition using enzyme kinetics on synthetic peptide and protein substrates and differential scanning fluorimetry. Furthermore, we established a readily crystallizable form of TMPRSS2 protein that produced high-resolution crystal structures with nafamostat, ‘157, and 6-amidino-2-naphthol . A novel noncovalent inhibitor scaffold is biochemically validated as a potential avenue for developing TMPRSS2-selective inhibitors.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | medium |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".