Identifying Human Interactors of SARS-CoV-2 Proteins and Drug Targets for COVID-19 using Network-Based Label Propagation
Year: 2020
Type: article
Abstract: Motivated by the critical need to identify new treatments for COVID-19, \nwe present a genome-scale, systems-level computational approach \nto prioritize drug targets based on their potential to regulate host- \nvirus interactions or their downstream signaling targets. We adapt \nand specialize network label propagation methods to this end. We \ndemonstrate that these techniques can predict human-SARS-CoV-2 \nprotein interactors with high accuracy. The top-ranked proteins \nthat we identify are enriched in host biological processes that are \npotentially coopted by the virus. We present cases where our \nmethodology generates promising insights such as the potential role of \nHSPA5 in viral entry. We highlight the connection between \nendoplasmic reticulum stress, HSPA5, and anti-clotting agents. We \nidentify tubulin proteins involved in ciliary assembly that are \ntargeted by anti-mitotic drugs. Drugs that we discuss are already \nundergoing clinical trials to test their efficacy against COVID-19. Our \nprioritized list of human proteins and drug targets is available as \na general resource for biological and clinical researchers who are \nrepositioning existing and approved drugs or developing novel \ntherapeutics as anti-COVID-19 agents.
Source: VTechWorks (Virginia Tech)
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3033738744