Broad-Spectrum Antiviral Efficacy of 7-Deaza-7-Fluoro-2’-C-Methyladenosine Against Multiple Coronaviruses <i>In Vitro</i> and <i>In Vivo</i>
Bibliographic record
Abstract
Abstract The Coronaviridae family has been implicated in several major epidemics over the past two decades, including those caused by SARS-CoV, MERS-CoV, and, most recently, SARS-CoV-2. The COVID-19 pandemic, driven by SARS-CoV-2, has led to over seven million deaths worldwide and has been associated with prolonged symptoms, chronic sequelae, and substantial socioeconomic disruptions. The limited availability of effective antiviral treatments, coupled with the ability of coronaviruses to mutate and evade immune defenses, underscores the urgent need for innovative antiviral agents. This study explores the efficacy of the nucleoside analogue DFMA as a potential antiviral agent against multiple Coronaviridae family members, including SARS-CoV-2 and two strains of murine hepatitis viruses (MHV-3 and MHV-A59). In vitro analyses demonstrated that DFMA effectively reduced the viral load in the supernatant of infected cells and enhanced cell viability for both MHV-3 and MHV-A59. Against SARS-CoV-2, DFMA showed a significant reduction in viral load, with a calculated Selectivity Index (SI) of 6.2. In vivo investigations further confirmed the antiviral potential of DFMA. In three distinct murine models—a severe COVID-19 model using MHV-3, a mild COVID-19 model employing MHV-A59, and a transgenic K18-hACE2 mouse model infected with SARS-CoV-2—DFMA administration significantly reduced viral loads in the lungs of infected mice. Additionally, DFMA mitigated inflammatory responses in all models by lowering levels of key inflammatory mediators, such as CXCL1, CCL2, and IL-6. These findings suggest that DFMA possesses broad-spectrum antiviral activity against coronaviruses and may serve as a promising therapeutic candidate for current and future coronavirus outbreaks. Further research is warranted to elucidate its mechanism of action and evaluate its efficacy in clinical settings. Importance Coronaviruses have caused significant outbreaks over the past two decades. Since 2020, COVID-19 has resulted in millions of deaths and lasting global impacts. The limited availability of effective antivirals and the virus’s ability to mutate and evade vaccines and monoclonal antibody therapy emphasize the urgent need for new treatments. This study investigates DFMA, a promising antiviral candidate, targeting SARS-CoV-2 and two related coronaviruses.Our promising results demonstrated significant antiviral activity of DFMA, not only against SARS-CoV-2 but also against other similar coronaviruses, indicating potential future use against COVID-19 and other possible coronavirus-related diseases.
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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) | 0.000 | 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 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".