Network-based Drug Repurposing for Human Coronavirus

Abstract

AbstractHuman Coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle east respiratory syndrome coronavirus (MERS-CoV), and 2019 novel coronavirus (2019-nCoV), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV. Drug repurposing, represented as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV has the highest nucleotide sequence identity with SARS-CoV (79.7%) among the six other known pathogenic HCoVs. Specifically, the envelope and nucleocapsid proteins of 2019-nCoV are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and known HCoV-host interactions in the human protein-protein interactome, we computationally identified 135 putative repurposable drugs for the potential prevention and treatment of HCoVs. In addition, we prioritized 16 potential anti-HCoV repurposable drugs (including melatonin, mercaptopurine, and sirolimus) that were further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. Finally, we showcased three potential drug combinations (including sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the ‘Complementary Exposure’ pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human protein-protein interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations toward future clinical trials for HCoVs.