PT  - JOURNAL ARTICLE
AU  - Mercè Llabrés
AU  - Gabriel Valiente
TI  - Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2
AID  - 10.1101/2020.07.07.191247
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.07.07.191247
4099  - http://biorxiv.org/content/early/2020/07/07/2020.07.07.191247.short
4100  - http://biorxiv.org/content/early/2020/07/07/2020.07.07.191247.full
AB  - 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 few 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.