Thiopurines inhibit coronavirus Spike protein processing and incorporation into progeny virions
Bibliographic record
Abstract
There is an outstanding need for broadly acting antiviral drugs to combat emerging viral diseases. Here, we report that thiopurines inhibit the replication of the betacoronaviruses HCoV-OC43 and SARS-CoV-2. 6-Thioguanine (6-TG) disrupted early stages of infection, limiting accumulation of full-length viral genomes, subgenomic RNAs and structural proteins. In ectopic expression models, we observed that 6-TG increased the electrophoretic mobility of Spike from diverse betacoronaviruses, matching the effects of enzymatic removal of N-linked oligosaccharides from Spike in vitro. SARS-CoV-2 virus-like particles (VLPs) harvested from 6-TG-treated cells were deficient in Spike. 6-TG treatment had a similar effect on production of lentiviruses pseudotyped with SARS-CoV-2 Spike, yielding pseudoviruses deficient in Spike and unable to infect ACE2-expressing cells. Together, these findings from complementary ectopic expression and infection models strongly indicate that defective Spike trafficking and processing is an outcome of 6-TG treatment. Using biochemical and genetic approaches we demonstrated that 6-TG is a pro-drug that must be converted to the nucleotide form by hypoxanthine phosphoribosyltransferase 1 (HPRT1) to achieve antiviral activity. This nucleotide form has been shown to inhibit small GTPases Rac1, RhoA, and CDC42; however, we observed that selective chemical inhibitors of these GTPases had no effect on Spike processing or accumulation. By contrast, the broad GTPase agonist ML099 countered the effects of 6-TG, suggesting that the antiviral activity of 6-TG requires the targeting of an unknown GTPase. Overall, these findings suggest that small GTPases are promising targets for host-targeted antivirals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".