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Synthetic lethality-based prediction of anti-SARS-CoV-2 targets

  • Lipika R. Pal
  • , Kuoyuan Cheng
  • , Nishanth Ulhas Nair
  • , Laura Martin-Sancho
  • , Sanju Sinha
  • , Yuan Pu
  • , Laura Riva
  • , Xin Yin
  • , Fiorella Schischlik
  • , Joo Sang Lee
  • , Sumit K. Chanda
  • , Eytan Ruppin
  • National Institutes of Health
  • University of Maryland, College Park
  • Sanford Burnham Prebys Medical Discovery Institute
  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

Novel strategies are needed to identify drug targets and treatments for the COVID-19 pandemic. The altered gene expression of virus-infected host cells provides an opportunity to specifically inhibit viral propagation via targeting the synthetic lethal and synthetic dosage lethal (SL/SDL) partners of such altered host genes. Pursuing this disparate antiviral strategy, here we comprehensively analyzed multiple in vitro and in vivo bulk and single-cell RNA-sequencing datasets of SARS-CoV-2 infection to predict clinically relevant candidate antiviral targets that are SL/SDL with altered host genes. The predicted SL/SDL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. We further selected a focused subset of 26 genes that we experimentally tested in a targeted siRNA screen using human Caco-2 cells. Notably, as predicted, knocking down these targets reduced viral replication and cell viability only under the infected condition without harming noninfected healthy cells.

Original languageEnglish
Article number104311
JournaliScience
Volume25
Issue number5
DOIs
StatePublished - 20 May 2022
Externally publishedYes

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

  • Drugs
  • Synthetic biology
  • Virology

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