Designing a Network Proximity-Based Drug Repurposing Strategy for COVID-19.

COVID-19 drug repurposing network medicine network-based pharmacologic (drug) therapy

Journal

Frontiers in cell and developmental biology
ISSN: 2296-634X
Titre abrégé: Front Cell Dev Biol
Pays: Switzerland
ID NLM: 101630250

Informations de publication

Date de publication:
2020
Historique:
received: 24 03 2020
accepted: 07 09 2020
entrez: 30 10 2020
pubmed: 31 10 2020
medline: 31 10 2020
Statut: epublish

Résumé

The ongoing COVID-19 pandemic still requires fast and effective efforts from all fronts, including epidemiology, clinical practice, molecular medicine, and pharmacology. A comprehensive molecular framework of the disease is needed to better understand its pathological mechanisms, and to design successful treatments able to slow down and stop the impressive pace of the outbreak and harsh clinical symptomatology, possibly via the use of readily available, off-the-shelf drugs. This work engages in providing a wider picture of the human molecular landscape of the SARS-CoV-2 infection via a network medicine approach as the ground for a drug repurposing strategy. Grounding on prior knowledge such as experimentally validated host proteins known to be viral interactors, tissue-specific gene expression data, and using network analysis techniques such as network propagation and connectivity significance, the host molecular reaction network to the viral invasion is explored and exploited to infer and prioritize candidate target genes, and finally to propose drugs to be repurposed for the treatment of COVID-19. Ranks of potential target genes have been obtained for coherent groups of tissues/organs, potential and distinct sites of interaction between the virus and the organism. The normalization and the aggregation of the different scores allowed to define a preliminary, restricted list of genes candidates as pharmacological targets for drug repurposing, with the aim of contrasting different phases of the virus infection and viral replication cycle.

Identifiants

pubmed: 33123533
doi: 10.3389/fcell.2020.545089
pmc: PMC7573309
doi:

Types de publication

Journal Article

Langues

eng

Pagination

545089

Informations de copyright

Copyright © 2020 Stolfi, Manni, Soligo, Vergni and Tieri.

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Auteurs

Paola Stolfi (P)

National Research Council (CNR), Institute for Applied Computing (IAC), Rome, Italy.

Luigi Manni (L)

National Research Council (CNR), Institute of Translational Pharmacology (IFT), Rome, Italy.

Marzia Soligo (M)

National Research Council (CNR), Institute of Translational Pharmacology (IFT), Rome, Italy.

Davide Vergni (D)

National Research Council (CNR), Institute for Applied Computing (IAC), Rome, Italy.

Paolo Tieri (P)

National Research Council (CNR), Institute for Applied Computing (IAC), Rome, Italy.

Classifications MeSH