Japanese encephalitis is a zoonotic disease caused by the Japanese encephalitis virus (JEV). It is mainly epidemic in Asia with an estimated 69,000 cases occurring per year. However, no approved agents are available for the treatment of JEV infection, and existing vaccines cannot control various types of JEV strains. Drug repurposing is a new concept for finding new indication of existing drugs, and, recently, the concept has been used to discover new antiviral agents. Identifying host proteins involved in the progress of JEV infection and using these proteins as targets are the center of drug repurposing for JEV infection. In this study, based on the gene expression data of JEV infection and the phenome-wide association study (PheWAS) data, we identified 286 genes that participate in the progress of JEV infection using systems biology methods. The enrichment analysis of these genes suggested that the genes identified by our methods were predominantly related to viral infection pathways and immune response-related pathways. We found that bortezomib, which can target these genes, may have an effect on the treatment of JEV infection. Subsequently, we evaluated the antiviral activity of bortezomib using a JEV-infected mouse model. The results showed that bortezomib can lower JEV-induced lethality in mice, alleviate suffering in JEV-infected mice and reduce the damage in brains caused by JEV infection. This work provides an agent with new indication to treat JEV infection.

Due to synergistic effects, combinatorial drugs are widely used for treating complex diseases. However, combining drugs and making them synergetic remains a challenge. Genetic disease genes are considered a promising source of drug targets with important implications for navigating the drug space. Most diseases are not caused by a single pathogenic factor, but by multiple disease genes, in particular, interacting disease genes. Thus, it is reasonable to consider that targeting epistatic disease genes may enhance the therapeutic effects of combinatorial drugs. In this study, synthetic lethality gene pairs of tumors, similar to epistatic disease genes, were first targeted by combinatorial drugs, resulting in the enrichment of the combinatorial drugs with cancer treatment, which verified our hypothesis. Then, conventional epistasis detection software was used to identify epistatic disease genes from the genome wide association studies (GWAS) dataset. Furthermore, combinatorial drugs were predicted by targeting these epistatic disease genes, and five combinations were proven to have synergistic anti-cancer effects on MCF-7 cells through cell cytotoxicity assay. Combined with the three-dimensional (3D) genome-based method, the epistatic disease genes were filtered and were more closely related to disease. By targeting the filtered gene pairs, the efficiency of combinatorial drug discovery has been further improved.

Natural medicines have attracted wide attention in recent years. It is of great significance to clarify the pharmacological mechanisms of natural medicines. In prior studies, we established a method for elucidating pharmacological mechanisms of natural products contained in connectivity map (cMap), in terms of module profiles of gene expression in chemical treatments. In this study, we explore whether this methodology is applicable to dissecting the pharmacological mechanisms of natural medicines beyond the agents contained in cMap. First, the gene expression profiles of curcumin (a typical isolated natural medicine) and Si-Wu-Tang (a classic traditional Chinese medicine formula) treatments were merged with those of cMap-derived 1309 agents, respectively. Then, a biclustering analysis was performed using FABIA method to identify gene modules. The biological functions of gene modules provide preliminary insights into pharmacological mechanisms of both natural medicines. The module profile can be characterized by a binary vector, which allowed us to compare the expression profiles of natural medicines with those of cMap-derived agents. Accordingly, we predicted a series of pharmacological effects for curcumin and Si-Wu-Tang by the indications of cMap-covered drugs. Most predictions were supported by experimental observations, suggesting the potential use of this method in natural medicine dissection.