In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs

Abstract

SARS-CoV-2 is the cause of the ongoing Coronavirus Disease 2019 (COVID-19) pandemic. Understanding of the RNA virus and its interactions with host proteins could improve therapeutic interventions for COVID-19. Using icSHAPE, we determined the structural landscape of SARS-CoV-2 RNA in infected human cells and from refolded RNAs, as well as of the regulatory untranslated regions of SARS-CoV-2 and six other coronaviruses. We validated several structural elements predicted in silico and discovered structural features that affect the translation and abundance of subgenomic viral RNAs in cells. The structural data informed a deep learning tool to predict 42 host proteins that bind to SARS-CoV-2 RNA. Strikingly, antisense oligonucleotides targeting the structural elements and FDA-approved drugs inhibiting the SARS-CoV-2 RNA binding proteins dramatically reduced SARS-CoV-2 infection in cells derived from human liver and lung tumors. Our findings thus shed light on coronavirus and reveal multiple candidate therapeutics for COVID-19 treatment.

A map of the SARS-CoV-2 RNA structurome

“…Under the current genome annotation (NC_045512.2) much of the previous 3′ UTR sequence is now found within an upstream open reading frame named ORF10 (however, this has been recently reported as being an untranslated ORF ( 79 )). ’s model partially recapitulates a recent model of the region ( 68 ) (blue pairs; Supplementary Figure S1A ) detecting the BSL and the non-pseudoknotted pairs of the pseudoknot stem (though this pseudoknot has recently been called into question ( 17 , 20 , 75 )). The overall metrics for the region however, including high ensemble diversity values and positive Δ G ° z -scores ( Supplementary Table S1 ) suggest the region is locally unstructured and/or highly dynamic.…”

“…The overall metrics for the region however, including high ensemble diversity values and positive Δ G ° z -scores ( Supplementary Table S1 ) suggest the region is locally unstructured and/or highly dynamic. Indeed, while portions are structurally conserved ( 18 , 20 ) much of the 3′ UTR has been shown to form long range interactions beyond the BSL and pseudoknot structures ( 75 ). As such, the model predicts the downstream region (composed of the HVR and s2m) to be mostly absent of locally structured elements.…”

“…The SHAPE reactivity datasets for the Incarnato ( 18 ), Pyle ( 17 ) and Zhang ( 20 ) labs are publicly available at http://www.incarnatolab.com/datasets/SARS_Manfredonia_2020.php , https://github.com/pylelab/SARS-CoV-2_SHAPE_MaP_structure , and http://rasp.zhanglab.net/ respectively. The DMS reactivity dataset from the Rouskin Lab ( 19 ), was obtained by request.…”

Arginine methylation of SARS-Cov-2 nucleocapsid protein regulates RNA binding, its ability to suppress stress granule formation, and viral replication

“…Few components, however, were identified that target the later phases of the viral life cycle, such as vRNP formation, phase separation for genome packaging, encapsidation and assembly of virions. A recent study identified ~50 host RBPs binding SARS-CoV-2 genomic RNA and the knockdown of some of these RBPs inhibited viral replication [70]. As SARS-CoV-2 N protein and cellular RBPs are substrates of PRMT1 [31], our findings suggest that type I PRMT inhibitors or increasing methylarginine readers may regulate N function in vRNP packaging and assembly into virions.…”

Current Strategies of Antiviral Drug Discovery for COVID-19

“…Using deep learning algorithm based on the information of the viral genomic structure, they predicted 42 host binding proteins on SARS-CoV-2 RNA, such as DDX24, NPM1. Further, they identified antisense oligonucleotides (ASOs) targeting viral RNA structure units and FDA-approved drugs Deguelin, Nilotinib, and Sorafenib inhibiting the predicted RNA binding protein expression and showed these compounds decreased SARS-CoV-2 infection in human cells ( Sun et al, 2021 ).…”