A Novel Class of Nonpeptidic Biaryl Inhibitors of Human Cathepsin K
Bibliographic record
Abstract
A novel series of nonpeptidic biaryl compounds was identified as potent and reversible inhibitors of cathepsin K. The P2-P3 amide bond of a known amino acetonitrile dipeptide 1 was replaced with a phenyl ring, thereby giving rise to this biaryl series that retained potency vs cathepsin K and showed an improved selectivity profile against other cathepsins. Structural modification within this series resulted in the identification of compound (R)-2, a potent human cathepsin K inhibitor (IC(50) = 3 nM) that is selective versus cathepsins B (IC(50) = 3950 nM), L (IC(50) = 3725 nM), and S (IC(50) = 2010 nM). In an in vitro assay involving rabbit osteoclasts and bovine bone, compound (R)-2 inhibited bone resorption with an IC(50) of 95 nM. It was shown that, unlike some peptidic nitrile inhibitors of cysteine proteases, the nitrile moiety of (R)-2 is not converted to the corresponding amide 3 by cathepsin K. This indicates that this class of nonpeptidic nitrile inhibitors is unlikely to be hydrolyzed by cysteine proteases. Furthermore, the inhibition of cathepsin K by compound (R)-2 was shown to be fully reversible and not observably time-dependent. To demonstrate the efficacy of compound (R)-2 in vivo, it was administered to ovariectomized (OVX) rhesus monkeys at 20 mg/kg, po once daily for 8 days, and a urinary marker of bone turnover, N-telopeptide of type I collagen (uNTx), was measured. During the eight-day dosing period, the mean reduction by compound (R)-2 in uNTx was 80% (p < 0.001). This demonstrates that inhibition of cathepsin K leads to an inhibition of this bone resorption marker in OVX rhesus monkeys and strongly suggests that inhibition of cathepsin K is a viable therapeutic approach for the treatment of osteoporosis.
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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) | 0.000 | 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 | 0.001 |
| 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".