Quinazoline‐4‐piperidine sulfamides are specific inhibitors of human <scp>NPP</scp>1 and prevent pathological mineralization of valve interstitial cells
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Ectonucleotide pyrophosphatase/PDE1 (NPP1) is an ectoenzyme, which plays a role in several disorders including calcific aortic valve disease (CAVD). So far, compounds that have been developed as inhibitors of NPP1 lack potency and specificity. Quinazoline-4-piperidine sulfamides (QPS) have been described as potent inhibitors of NPP1. However, their mode of inhibition as well as their selectivity and capacity to modify biological processes have not been investigated. EXPERIMENTAL APPROACH: In the present series of experiments, we have evaluated the efficacy of two derivatives, QPS1-2, in inhibiting human NPP1, and we have evaluated the effect of the most potent derivative (QPS1) on other ectonucleotidases as well as on the ability of this compound to prevent phosphate-induced mineralization of human primary aortic valve interstitial cells (VICs). KEY RESULTS: The QPS1 derivative is a potent (Ki 59.3 ± 5.4 nM) and selective non-competitive inhibitor of human NPP1. Moreover, QPS1 also significantly inhibited the K121Q NPP1 gene variant (Ki 59.2 ± 14.5 nM), which is prevalent in the general population. QPS1 did not significantly alter the activity of other nucleotide metabolizing ectoenzymes expressed at the cell surface, namely NPP3, NTPDases (1-3), ecto-5'-nucleotidase and ALP. Importantly, QPS1 in the low micromolar range (≤10 μM) prevented phosphate-induced mineralization of VICs and lowered the rise of osteogenic genes as expected for NPP1 inhibition. CONCLUSIONS AND IMPLICATIONS: We have provided evidence that QPS1 is a potent and selective non-competitive inhibitor of NPP1 and that it prevented pathological mineralization in a cellular model.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".