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.