This study presents a network-based methodology for drug repurposing to address the 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2). The approach integrates systems pharmacology and network medicine, leveraging the human protein-protein interaction (PPI) network to identify potential antiviral drugs. Phylogenetic analyses reveal that 2019-nCoV/SARS-CoV-2 shares high sequence identity with SARS-CoV (79.7%). Network proximity analyses of drug targets and HCoV-host interactions prioritize 16 potential repurposable drugs, including melatonin, mercaptopurine, and sirolimus. Additionally, three drug combinations (sirolimus plus dactinomycin, mercaptopurine plus melatonin, and temefine plus emodin) are identified using the "Complementary Exposure" pattern, where drugs target separate neighborhoods in the human interactome network. The study offers a rapid and systematic approach to identify candidate repurposable drugs and drug combinations for 2019-nCoV/SARS-CoV-2, with the potential to minimize the translational gap between preclinical testing and clinical outcomes.This study presents a network-based methodology for drug repurposing to address the 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2). The approach integrates systems pharmacology and network medicine, leveraging the human protein-protein interaction (PPI) network to identify potential antiviral drugs. Phylogenetic analyses reveal that 2019-nCoV/SARS-CoV-2 shares high sequence identity with SARS-CoV (79.7%). Network proximity analyses of drug targets and HCoV-host interactions prioritize 16 potential repurposable drugs, including melatonin, mercaptopurine, and sirolimus. Additionally, three drug combinations (sirolimus plus dactinomycin, mercaptopurine plus melatonin, and temefine plus emodin) are identified using the "Complementary Exposure" pattern, where drugs target separate neighborhoods in the human interactome network. The study offers a rapid and systematic approach to identify candidate repurposable drugs and drug combinations for 2019-nCoV/SARS-CoV-2, with the potential to minimize the translational gap between preclinical testing and clinical outcomes.