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.First author draf