Ticlopidine in Its Prodrug Form Is a Selective Inhibitor of Human NTPDase1
Bibliographic record
Abstract
Nucleoside triphosphate diphosphohydrolase-1 (NTPDase1), like other ectonucleotidases, controls extracellular nucleotide levels and consequently their (patho)physiological responses such as in thrombosis, inflammation, and cancer. Selective NTPDase1 inhibitors would therefore be very useful. We previously observed that ticlopidine in its prodrug form, which does not affect P2 receptor activity, inhibited the recombinant form of human NTPDase1 (K i = 14 μM). Here we tested whether ticlopidine can be used as a selective inhibitor of NTPDase1. We confirmed that ticlopidine inhibits NTPDase1 in different forms and in different assays. The ADPase activity of intact HUVEC as well as of COS-7 cells transfected with human NTPDase1 was strongly inhibited by 100 µM ticlopidine, 99 and 86%, respectively. Ticlopidine (100 µM) completely inhibited the ATPase activity of NTPDase1 in situ as shown by enzyme histochemistry with human liver and pancreas sections. Ticlopidine also inhibited the activity of rat and mouse NTPDase1 and of potato apyrase. At 100 µM ticlopidine did not affect the activity of human NTPDase2, NTPDase3, and NTPDase8, nor of NPP1 and NPP3. Weak inhibition (10-20%) of NTPDase3 and -8 was observed at 1 mM ticlopidine. These results show that ticlopidine is a specific inhibitor of NTPDase1 that can be used in enzymatic and histochemistry assays.
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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) | 0.001 | 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".