Identifying potential therapeutic targets of a natural product Jujuboside B for insomnia through network pharmacology

Knowledge of the interactome improves the understanding of disease metabolism. Biological information about interactions among genes and their protein products, computationally extracted in the context of SysBiomics, can hint at molecular causes of diseases, be essential for understanding biological systems, and provide clues for new therapeutic approaches. Quick and efficient access to this data have become critical issues for biologists. We have implemented a computational platform that integrates pathway, protein-protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for insomnia and intervention effects of Jujuboside B (JuB). The interaction data were imported into Cytoscape software, a popular bioinformatics package for biological network visualization and data integration, for screening the central nodes of the network, exploiting functional study of the central node genes, exploring the mechanism of insomnia. Results showed that seven differentially expressed genes confirmed by Cytoscape as the central nodes of the network in insomnia had interactions, forming a complicated interaction network (77 nodes, 96 edges). Among gene nodes, HBA1, LEP, MAOA, PRNP, GHRL, CLOCK and SLC6A4 were verified as the genes with maximal differential expressions. Of note, we further observed that the HBA1, LEP, SLC6A4 and MAOA were JuB target genes. The interaction network of the differentially expressed genes, especially the central nodes of this network, can provide clues to the insomnia, early diagnosis and molecular targeted therapy. Our findings demonstrate that the integration of interaction network in genomic space can not only speed the genome-wide identification of drug targets but also find new applications for the existing drugs.