Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19
Jesse W. Wotring,
Charles J. Zhang,
Sean M. McCarty,
Namrata S. Kadambi,
Anya T. Amin,
Teresa R. O’Meara,
Carla D. Pretto,
Jason R. Spence,
Konstantinos D. Alysandratos,
Darrell N. Kotton,
Samuel K. Handelman,
Christiane E. Wobus,
Kevin J. Weatherwax,
George A. Mashour,
Matthew J. O’Meara,
Jonathan Z. Sexton
Posted 27 May 2020
bioRxiv DOI: 10.1101/2020.05.27.117184
Posted 27 May 2020
The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Unfortunately, traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious single agents and combination therapies against SARS-CoV-2. Quantitative high-content morphological profiling was coupled with an AI-based machine learning strategy to classify features of cells for infection and stress. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 17 dose-responsive compounds with antiviral efficacy. In particular, we discovered that lactoferrin is an effective inhibitor of SARS-CoV-2 infection with an IC50 of 308 nM and that it potentiates the efficacy of both remdesivir and hydroxychloroquine. Lactoferrin also stimulates an antiviral host cell response and retains inhibitory activity in iPSC-derived alveolar epithelial cells, a model for the primary site of infection. Given its safety profile in humans, these data suggest that lactoferrin is a readily translatable therapeutic option for COVID-19. Additionally, several commonly prescribed drugs were found to exacerbate viral infection and warrant follow up studies. We conclude that morphological profiling for drug repurposing is an effective strategy for the selection and optimization of drugs and drug combinations as viable therapeutic options for COVID-19 pandemic and other emerging infectious diseases. ### Competing Interest Statement The authors have declared no competing interest. * MOI : multiplicity of infection UMAP : uniform manifold approximation and projection COVID-19 : Coronavirus Disease-2019 MOA : mechanism of action ROI : region of interest iAEC2 : induced pluripotent stem cell (iPSC)-derived alveolar epithelial type 2 cells HCQ : hydroxychloroquine
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