Key result
In vivo structural mapping of the SARS-CoV-2 RNA genome identified functionally impactful structural features and predicted several dozen host cell proteins that bind to the viral RNA.
Why the study?
The failure to identify effective interventions for COVID-19 was attributed to an incomplete understanding of SARS-CoV-2 and its host cell infection process.
In vivo structural mapping of the SARS-CoV-2 RNA genome identifies novel structural features and host cell binding proteins, providing potential targets for antiviral therapeutics.
This is the authors' abstract. We don't add key points for this paper.
SUMMARY SARS-CoV-2 is an RNA virus of the Coronaviridae family that is the causal pathogen of the ongoing Coronavirus Disease 2019 pandemic. There are currently no antiviral drugs or vaccines to treat COVID-19, and the failure to identify effective interventions can be blamed on our incomplete understanding of the nature of this virus and its host cell infection process. Here, we experimentally determined structural maps of the SARS-CoV-2 RNA genome in infected human cells and also characterized in vitro refolded RNA structures for SARS-CoV-2 and 6 other coronaviruses. Our in vivo data confirms several structural elements predicted from theoretical analysis and goes much further in revealing many previously unknown structural features that functionally impact viral translation and discontinuous transcription in cells. Importantly, we harnessed our in vivo structure data alongside a deep-learning tool and accurately predicted several dozen functionally related host cell proteins that bind to the SARS-CoV-2 RNA genome, none of which were known previously. Thus, our in vivo structural study lays a foundation for coronavirus RNA biology and indicates promising directions for the rapid development of therapeutics to treat COVID-19. HIGHLIGHTS We mapped the in vivo structure and built secondary structural models of the SARS-CoV-2 RNA genome We discovered functionally impactful structural features in the RNA genomes of multiple coronaviruses We predicted and validated host cell proteins that bind to the SARS-CoV-2 RNA genome based on our in vivo RNA structural data using a deep-learning tool
May nominate new SARS-CoV-2 RNA targets for antivirals; animal data leaves open human translation.
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Sun et al. (2020) studied SARS-CoV-2. icSHAPE structural mapping and PrismNet deep learning was evaluated on In vivo RNA secondary structure of SARS-CoV-2 and host protein binding predictions. In vivo structural mapping of the SARS-CoV-2 RNA genome identified functionally impactful structural features and predicted several dozen host cell proteins that bind to the viral RNA.
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