Network-based Drug Repurposing for Human Coronavirus

Yadi Zhou; Yuan Hou; Jiayu Shen; Yin Huang; William Martin; Feixiong Cheng

Although sizeable efforts were made for assembling large-scale, experimentally reported drug-target networks from publicly available databases, the network data may be incomplete and some drug-protein interactions may be functional associations, instead of physical bindings. We may use computational approaches to systematically predict the drug-target interactions further [24, 69] . In addition, the collected virus-host interactions are far from complete and the quality can be influenced by multiple factors, including different experimental assays and human cell line models. We may computationally predict a new virus-host interactome for HCoVs using sequence-based and structure-based approaches [70] . The current systems pharmacology model cannot separate therapeutic antiviral effects from those predictions due to lack of detailed pharmacological effects of drug targets and unknown functional consequences of virushost interactions. Drug targets representing nodes within cellular networks are often intrinsically coupled with both therapeutic and adverse profiles [71] , as drugs can inhibit or activate protein functions (including antagonists versus agonists). Comprehensive identification of the virus-host interactome for 2019-nCoV, with specific biological effects using functional genomics assays [72, 73] , will significantly improve the accuracy of current network-based methodologies.