This study presents an integrative, network-based drug repurposing methodology for identifying potential repurposable drugs and drug combinations targeting 2019-nCoV/SARS-CoV-2. The approach combines a systems pharmacology-based network medicine platform to quantify 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/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). The envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, with sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV–host interactions in the human interactome, 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) were prioritized and validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. Three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) were identified, captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV–host subnetwork, but target separate neighborhoods in the human interactome network. The study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2. However, further preclinical experiments and clinical trials are required to verify the clinical benefits of these network-predicted candidates before clinical use. The study also highlights the importance of network-based approaches in drug repurposing and drug combination identification for the treatment of viral infections.This study presents an integrative, network-based drug repurposing methodology for identifying potential repurposable drugs and drug combinations targeting 2019-nCoV/SARS-CoV-2. The approach combines a systems pharmacology-based network medicine platform to quantify 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/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). The envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, with sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV–host interactions in the human interactome, 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) were prioritized and validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. Three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) were identified, captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV–host subnetwork, but target separate neighborhoods in the human interactome network. The study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2. However, further preclinical experiments and clinical trials are required to verify the clinical benefits of these network-predicted candidates before clinical use. The study also highlights the importance of network-based approaches in drug repurposing and drug combination identification for the treatment of viral infections.