Identifying Human Interactors of SARS-CoV-2 Proteins and Drug Targets for COVID-19 using Network-Based Label Propagation

COVID-19, the disease caused by the coronavirus SARS-CoV-2, has inflicted considerable suffering on the human population. In this paper, we aim to significantly expand the resources available to biological and clinical researchers who are developing therapeutic targets for drug development and repositioning. Taking a genome-scale, systems-level view of virus-host interactions, we adapt and specialize network label propagation methods to prioritize drug targets based on their probability to inhibit host-pathogen interactions or their downstream signaling targets. In particular, our results suggest that we can predict human proteins that interact with SARS-CoV-2 proteins with high accuracy. Moreover, the top-ranking proteins scored by our methods are enriched in biological processes that are relevant to the virus. We discuss cases where our methodology generates promising insights, including the potential role of HSPA5 in viral entry, the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs. Several drugs that we discuss are already undergoing clinical trials to test their efficacy against COVID-19. We make the prioritized list of human proteins and drug targets broadly available as a general resource for repositioning of existing and approved drugs as anti-COVID-19 agents or for novel drug development.