Highly Potent and Selective Ectonucleotide Pyrophosphatase/Phosphodiesterase I Inhibitors Based on an Adenosine 5′-(α or γ)-Thio-(α,β- or β,γ)-methylenetriphosphate Scaffold
Bibliographic record
Abstract
Aberrant nucleotide pyrophosphatase/phosphodiesterase-1 (NPP1) activity is associated with chondrocalcinosis, osteoarthritis, and type 2 diabetes. The potential of NPP1 inhibitors as therapeutic agents, and the scarceness of their structure-activity relationship, encouraged us to develop new NPP1 inhibitors. Specifically, we synthesized ATP-α-thio-β,γ-CH2 (1), ATP-α-thio-β,γ-CCl2 (2), ATP-α-CH2-γ-thio (3), and 8-SH-ATP (4) and established their resistance to hydrolysis by NPP1,3 and NTPDase1,2,3,8 (<5% hydrolysis) (NTPDase = ectonucleoside triphosphate diphosphohydrolase). Analogues 1-3 at 100 μM inhibited thymidine 5'-monophosphate p-nitrophenyl ester hydrolysis by NPP1 and NPP3 by >90% and 23-43%, respectively, and only slightly affected (0-40%) hydrolysis of ATP by NTPDase1,2,3,8. Analogue 3 is the most potent NPP1 inhibitor currently known, Ki = 20 nM and IC50 = 0.39 μM. Analogue 2a is a selective NPP1 inhibitor with Ki = 685 nM and IC50 = 0.57 μM. Analogues 1-3 were found mostly to be nonagonists of P2Y1/P2Y2/P2Y11 receptors. Docking analogues 1-3 into the NPP1 model suggested that activity correlates with the number of H-bonds with binding site residues. In conclusion, we propose analogues 2a and 3 as highly promising NPP1 inhibitors.
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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".