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

  • J. J. Patten
  • , Patrick T. Keiser
  • , Deisy Morselli-Gysi
  • , Giulia Menichetti
  • , Hiroyuki Mori
  • , Callie J. Donahue
  • , Xiao Gan
  • , Italo do Valle
  • , Kathleen Geoghegan-Barek
  • , Manu Anantpadma
  • , Ruth Mabel Boytz
  • , Jacob L. Berrigan
  • , Sarah H. Stubbs
  • , Tess Ayazika
  • , Colin O'Leary
  • , Sallieu Jalloh
  • , Florence Wagner
  • , Seyoum Ayehunie
  • , Stephen J. Elledge
  • , Deborah Anderson
  • Joseph Loscalzo, Marinka Zitnik, Suryaram Gummuluru, Mark N. Namchuk, Albert László Barabási, Robert A. Davey*
*Corresponding author for this work
  • Boston University
  • Northeastern University
  • Harvard University
  • Howard Hughes Medical Institute
  • Broad Institute
  • MatTek Corporation

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Article number104925
JournaliScience
Volume25
Issue number9
DOIs
StatePublished - 16 Sep 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Bioinformatics
  • Pharmacoinformatics
  • Pharmacology
  • Virology

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