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Cell Discovery· 2020Q1

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Yadi Zhou, Yuan Hou, Jiayu Shen, Yin Huang et al.

Short summary

This study presents a network medicine platform that identified 16 potential anti-HCoV repurposable drugs, including melatonin, mercaptopurine, and sirolimus, and three drug combinations for SARS-CoV-2.

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Key points

  • A network medicine platform was used to identify potential anti-HCoV repurposable drugs.
  • Phylogenetic analysis confirmed high sequence identity between 2019-nCoV/SARS-CoV-2 and SARS-CoV.
  • 16 potential anti-HCoV repurposable drugs were prioritized, including melatonin, mercaptopurine, and sirolimus.
  • Three potential drug combinations with complementary targets were identified.

AI-generated from the title and abstract; the full text is not read.

Abstract

Abstract Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV–host interactome and drug targets in the human protein–protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV–host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the “ Complementary Exposure ” pattern: the targets of the drugs both hit the HCoV–host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

The authors' abstract, as published at the source. Cell Discovery, 2020 · DOI ↗

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Field: Computational Theory and Mathematics

Computational Theory and MathematicsComputer Science