Identifying Human Interactors of SARS-CoV-2 Proteins and Drug Targets for COVID-19 using Network-Based Label Propagation
Motivated by the critical need to identify new treatments for COVID- 19, we present a genome-scale, systems-level computational approach to prioritize drug targets based on their potential to regulate host- virus interactions or their downstream signaling targets. We adapt and specialize network label propagation methods to this end. We demonstrate that these techniques can predict human-SARS-CoV- 2 protein interactors with high accuracy. The top-ranked proteins that we identify are enriched in host biological processes that are potentially coopted by the virus. We present cases where our methodology generates promising insights such as the potential role of HSPA5 in viral entry. We highlight the connection between endoplasmic reticulum stress, HSPA5, and anti-clotting agents. We identify tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs. Drugs that we discuss are already undergoing clinical trials to test their efficacy against COVID-19. Our prioritized list of human proteins and drug targets is available as a general resource for biological and clinical researchers who are repositioning existing and approved drugs or developing novel therapeutics as anti-COVID-19 agents.