Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2020
Historique:
received: 02 07 2020
accepted: 24 11 2020
entrez: 7 12 2020
pubmed: 8 12 2020
medline: 20 1 2021
Statut: epublish

Résumé

Beside socio-economic issues, coronavirus pandemic COVID-19, the infectious disease caused by the newly discovered coronavirus SARS-CoV-2, has caused a deep impact in the scientific community, that has considerably increased its effort to discover the infection strategies of the new virus. Among the extensive and crucial research that has been carried out in the last months, the analysis of the virus-host relationship plays an important role in drug discovery. Virus-host protein-protein interactions are the active agents in virus replication, and the analysis of virus-host protein-protein interaction networks is fundamental to the study of the virus-host relationship. We have adapted and implemented a recent integer linear programming model for protein-protein interaction network alignment to virus-host networks, and obtained a consensus alignment of the SARS-CoV-1 and SARS-CoV-2 virus-host protein-protein interaction networks. Despite the lack of shared human proteins in these virus-host networks, and the low number of preserved virus-host interactions, the consensus alignment revealed aligned human proteins that share a function related to viral infection, as well as human proteins of high functional similarity that interact with SARS-CoV-1 and SARS-CoV-2 proteins, whose alignment would preserve these virus-host interactions.

Identifiants

pubmed: 33284827
doi: 10.1371/journal.pone.0236304
pii: PONE-D-20-20450
pmc: PMC7721128
doi:

Substances chimiques

Proteins 0
Spike Glycoprotein, Coronavirus 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0236304

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Mercè Llabrés (M)

Department of Mathematics and Computer Science, University of the Balearic Islands, Palma de Mallorca, Spain.

Gabriel Valiente (G)

Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, Barcelona, Spain.

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Classifications MeSH