Antiviral Potential of the Antimicrobial Drug Atovaquone\nagainst SARS-CoV‑2 and Emerging Variants of Concern
Bibliographic record
Abstract
The\nantimicrobial medication malarone (atovaquone/proguanil) is\nused as a fixed-dose combination for treating children and adults\nwith uncomplicated malaria or as chemoprophylaxis for preventing malaria\nin travelers. It is an inexpensive, efficacious, and safe drug frequently\nprescribed around the world. Following anecdotal evidence from 17\npatients in the provinces of Quebec and Ontario, Canada, suggesting\nthat malarone/atovaquone may present some benefits in protecting against\nCOVID-19, we sought to examine its antiviral potential in limiting\nthe replication of SARS-CoV-2 in cellular models of infection. In\nVeroE6 expressing human TMPRSS2 and human lung Calu-3 epithelial cells,\nwe show that the active compound atovaquone at micromolar concentrations\npotently inhibits the replication of SARS-CoV-2 and other variants\nof concern including the alpha, beta, and delta variants. Importantly,\natovaquone retained its full antiviral activity in a primary human\nairway epithelium cell culture model. Mechanistically, we demonstrate\nthat the atovaquone antiviral activity against SARS-CoV-2 is partially\ndependent on the expression of TMPRSS2 and that the drug can disrupt\nthe interaction of the spike protein with the viral receptor, ACE2.\nAdditionally, spike-mediated membrane fusion was also reduced in the\npresence of atovaquone. In the United States, two clinical trials\nof atovaquone administered alone or in combination with azithromycin\nwere initiated in 2020. While we await the results of these trials,\nour findings in cellular infection models demonstrate that atovaquone\nis a potent antiviral FDA-approved drug against SARS-CoV-2 and other\nvariants of concern in vitro.
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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 | 0.000 | 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 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".