In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs
Author(s) -
Lei Sun,
Pan Li,
Xiaohui Ju,
Jian Rao,
Wenze Huang,
Lili Ren,
Shaojun Zhang,
Tuanlin Xiong,
Kui Xu,
Xiaolin Zhou,
Mingli Gong,
Eric A. Miska,
Qiang Ding,
Jianwei Wang,
Qiangfeng Cliff Zhang
Publication year - 2021
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2021.02.008
Subject(s) - biology , rna , coronavirus , subgenomic mrna , in silico , coronaviridae , virology , computational biology , untranslated region , translation (biology) , genome , gene , genetics , messenger rna , covid-19 , disease , infectious disease (medical specialty) , medicine , pathology
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.
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