The Path to Therapeutic Furin Inhibitors: From Yeast Pheromones to SARS-CoV-2
Bibliographic record
Abstract
The spurious acquisition and optimization of a furin cleavage site in the SARS-CoV-2 spike protein is associated with increased viral transmission and disease, and has generated intense interest in the development and application of therapeutic furin inhibitors to thwart the COVID-19 pandemic. This review summarizes the seminal studies that informed current efforts to inhibit furin. These include the convergent efforts of endocrinologists, virologists, and yeast geneticists that, together, culminated in the discovery of furin. We describe the pioneering biochemical studies which led to the first furin inhibitors that were able to block the disease pathways which are broadly critical for pathogen virulence, tumor invasiveness, and atherosclerosis. We then summarize how these studies subsequently informed current strategies leading to the development of small-molecule furin inhibitors as potential therapies to combat SARS-CoV-2 and other diseases that rely on furin for their pathogenicity and progression.
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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 | 0.001 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".