The SARS-CoV-2 pandemic has caused widespread illness, loss of life, and socioeconomic disruption that is unlikely to resolve until vaccines are widely adopted, and effective therapeutic treatments become established. Here, a well curated and annotated library of 6710 clinical and preclinical molecules, covering diverse chemical scaffolds and known host targets was evaluated for inhibition of SARS-CoV-2 infection in multiple infection models. Multi-concentration, high-content immunocytofluorescence-based screening identified 172 strongly active small molecules, including 52 with submicromolar potencies. The active molecules were extensively triaged by in vitro mechanistic assays, including human primary cell models of infection and the most promising, obatoclax, was tested for in vivo efficacy. Structural and mechanistic classification of compounds revealed known and novel chemotypes and potential host targets involved in each step of the virus replication cycle including BET proteins, microtubule function, mTOR, ER kinases, protein synthesis and ion channel function. In the mouse disease model obatoclax effectively reduced lung virus load by 10-fold. Overall, this work provides an important, publicly accessible, foundation for development of novel treatments for COVID-19, establishes human primary cell-based pharmacological models for evaluation of therapeutics and identifies new insights into SARS-CoV-2 infection mechanisms. Significance: A bioinformatically rich library of pharmacologically active small molecules with diverse chemical scaffolds and including known host targets were used to identify hundreds of SARS-CoV-2 replication inhibitors using in vitro, ex vivo, and in vivo models. Extending our previous work, unbiased screening demonstrated a propensity for compounds targeting host proteins that interact with virus proteins. Representatives from multiple chemical classes revealed differences in cell susceptibility, suggesting distinct dependencies on host factors and one, Obatoclax, showed 90% reduction of lung virus loads in the mouse disease model. Our findings and integrated analytical approaches will have important implications for future drug screening and how therapies are developed against SARS-CoV-2 and other viruses.