摘要：SummaryPharmacologically active compounds with known biological targets were evaluated for inhibition of SARS-CoV-2 infection in cell and tissue models to help identify potent classes of active small molecules and to better understand host-virus interactions. We evaluated 6,710 clinical and preclinical compounds targeting 2,183 host proteins by immunocytofluorescence-based screening to identify SARS-CoV-2 infection inhibitors. Computationally integrating relationships between small molecule structure, dose-response antiviral activity, host target, and cell interactome produced cellular networks important for infection. This analysis revealed 389 small molecules with micromolar to low nanomolar activities, representing >12 scaffold classes and 813 host targets. Representatives were evaluated for mechanism of action in stable and primary human cell models with SARS-CoV-2 variants and MERS-CoV. One promising candidate, obatoclax, significantly reduced SARS-CoV-2 viral lung load in mice. Ultimately, this work establishes a rigorous approach for future pharmacological and computational identification of host factor dependencies and treatments for viral diseases.Graphical abstractDisplay OmittedHighlights•Identified 389 SARS-CoV-2 inhibitors comprising >12 structurally similar groups•Drug-protein target network analyses reveal host dependencies•Mechanistic evaluation of virus variants in stable and primary cell cultures•Lead candidate decreases virus lung load in mouse model of diseaseBioinformatics; Pharmacoinformatics; Pharmacology; Virology
