Pharmacological inhibitors to identify roles of cathepsin K in cell-based studies: a comparison of available tools
Bibliographic record
Abstract
Cathepsin K (Cat K) degrades bone type I collagen and is a target for the pharmacological treatment of osteoporosis. Further roles for Cat K have been recently described, some of which are supported by the use of purportedly selective Cat K inhibitors in human and rodent cell-based assays. Twelve commercial and non-commercial Cat K inhibitors were profiled against a panel of purified human, rat, and mouse cysteine cathepsins and in two cell-based enzyme occupancy assays for activity against Cat K, B, and L. Ten inhibitors, including the carbohydrazide Cat K inhibitor II (Boc-Phe-Leu-NHNH-CO-NHNH-Leu-Z), the non-covalent K4b, and the epoxide NC-2300, have either little Cat K selectivity, or appear poorly cell penetrant. The amino-acetonitrile-containing inhibitors L-873724 and odanacatib show greater than 100-fold human Cat K enzyme selectivity and have similar IC(50) values against each cathepsin in cell-based and enzyme assays. The basic inhibitor balicatib has greater cellular potencies than expected on the basis of purified enzyme assays. The accumulation of [(14)C]-balicatib in fibroblasts is blocked by prior treatment of the cells with NH(4)Cl, consistent with balicatib having lysosomotropic properties. These results support the use of L-873724 and odanacatib as tools to identify novel roles for Cat K using human cell-based systems, but suggest using caution in the interpretation of studies employing the other compounds.
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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 | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".