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Abstract (may include machine translation)
Pharmacologically 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.
Original language | English |
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Article number | 104925 |
Journal | iScience |
Volume | 25 |
Issue number | 9 |
DOIs | |
State | Published - 16 Sep 2022 |
Keywords
- Bioinformatics
- Pharmacoinformatics
- Pharmacology
- Virology
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DYNASNET: Dynamics and Structure of Networks
Barabási, A.-L. (PI) & Kertész, J. (Researcher)
European Commission - H2020 - European Research Council -Synergy Grant
1/09/19 → 28/02/27
Project: Research