Inhibition of Furin/Proprotein Convertase-catalyzed Surface and Intracellular Processing by Small Molecules
Bibliographic record
Abstract
Furin is a ubiquitously expressed proprotein convertase (PC) that plays a vital role in numerous disease processes including cancer metastasis, bacterial toxin activation (e.g. anthrax and Pseudomonas), and viral propagation (e.g. avian influenza and human immunodeficiency virus). To identify small molecule inhibitors of furin and related processing enzymes, we performed high-throughput screens of chemical diversity libraries utilizing both enzyme-based and cell-based assays. The screens identified partially overlapping sets of compounds that were further characterized for affinity, mechanism, and efficacy in additional cellular processing assays. Dicoumarols were identified as a class of compounds that inhibited furin non-competitively and reversibly with Ki values in the micromolar range. These compounds inhibited furin/furin-like activity both at the cell surface (protecting against anthrax toxin) and in the secretory pathway (blocking processing of the metastasis factor membrane-type 1 matrix metalloproteinase/MT1-MMP) at concentrations close to Ki values. Compounds tested exhibited distinct patterns of inhibition of other furin-family PCs (rat PACE4, human PC5/6 and human PC7), showing that dicoumarol derivatives might be developed as either generic or selective inhibitors of the PCs. The extensive clinical use, high bioavailability and relatively low toxicity of dicoumarols suggests that the dicoumarol structure will be a good starting point for development of drug-like inhibitors of furin and other PCs that can act both intracellularly and at the cell surface.
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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 | 0.000 |
| 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".