Identification of potent inhibitors of SARS-CoV-2 infection by combined pharmacological evaluation and cellular network prioritization

  • iScience. 2022 Sep 16;25(9):104925. doi: 10.1016/j.isci.2022.104925.
J J Patten  1 ,  Patrick T Keiser  1 ,  Deisy Morselli-Gysi  2  3 ,  Giulia Menichetti  2  3 ,  Hiroyuki Mori  1 ,  Callie J Donahue  1 ,  Xiao Gan  2  3 ,  Italo do Valle  2 ,  Kathleen Geoghegan-Barek  1 ,  Manu Anantpadma  1 ,  RuthMabel Boytz  1 ,  Jacob L Berrigan  1 ,  Sarah H Stubbs  1 ,  Tess Ayazika  1 ,  Colin O'Leary  4 ,  Sallieu Jalloh  1 ,  Florence Wagner  5 ,  Seyoum Ayehunie  6 ,  Stephen J Elledge  4 ,  Deborah Anderson  1 ,  Joseph Loscalzo  3 ,  Marinka Zitnik  7 ,  Suryaram Gummuluru  1 ,  Mark N Namchuk  8 ,  Albert-László Barabási  2  3  9 ,  Robert A Davey  1
Affiliations
  • 1. Department of Microbiology, Boston University School of Medicine and NEIDL, Boston University, Boston, MA 02118, USA.
  • 2. Network Science Institute, Northeastern University, Boston, MA 02115, USA.
  • 3. Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
  • 4. Department of Genetics, Program in Virology, Harvard Medical School, Division of Genetics, Brigham and Women's Hospital, Howard Hughes Medical Institute, Boston, MA, USA.
  • 5. Center for the Development of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
  • 6. MatTek Corporation, A BICO Company, Ashland, MA 01721, USA.
  • 7. Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
  • 8. Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA.
  • 9. Department of Network and Data Science, Central European University, Budapest 1051, Hungary.
PMID: 35992305 DOI: 10.1016/j.isci.2022.104925
Abstract

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.

Keywords
Bioinformatics; Pharmacoinformatics; Pharmacology; Virology.
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