Drug repositioning, also known as conventional drug in novel use, is the discovery of new indications or novel use of the drug. It has received more and more attention not only in the research and development of western medicine, but also gradually become popular in the research field of Chinese medicine. The new phase of drug repositioning research is based on computer technology, and its research methods and techniques keep up with the time. Network pharmacology is playing more and more important role in the study of drug repositioning. At present, the strategies used in the study of traditional Chinese medicine repositioning include small molecules (or ligands), drug targets and network theory. In this paper, the concept, research status, application status of Chinese medicinals repositioning and application status and strategy of network pharmacology are reviewed, in order to provide references for the study of drug repositioning in Chinese medicinal.
Big data technology is an inevitable result of the information age, which not only promotes the development of biomedical science, but also opens up new paths for the development of traditional Chinese medicine (TCM). This paper introduced the application status of big data technology in the field of TCM in recent years, and put forward some thinkings and prospects so as to provide new insights and methods for the future development direction of TCM.
Objective To explore the mechanism of action of Xiao chengqitang in the treatment of ulcerative colitis (UC) by network pharmacology. Methods From January 17th to January 20th, 2022, the active components and action targets of Xiao chengqitang (Radix Rhei Et Rhizome, Magnolia Officinalis Rehd Et Wils and Aurantii Fructus Immaturus) were obtained from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. “Ulcerative Colitis” was used as a search term to retrieve related targets of UC from GeneCards database, to obtain the targets for the treatment of UC using Xiao chengqitang. Then, Cytoscape 3.7.2 software was used for further topological analysis and the Chinese medicine compound-target network of genes was constructed. At the same time, protein-protein interaction network of Xiao chengqitang for the treatment of UC was constructed by STRING database. In addition, targets of Xiao chengqitang for the treatment of UC were applied for gene ontology (GO) analysis, as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Results A total of 26 major active ingredients of Xiao chengqitang were obtained after screening, corresponding to 122 drug targets, 4837 disease targets for UC and 86 drug-disease common targets. According to protein-protein interaction network topology analysis parameters, 10 key therapeutic targets were screened, namely RAC-alpha serine/threonine-protein kinase, cellular tumor antigen p53, tumor necrosis factor-α, interleukin-6, caspase-3, prostaglandin-endoperoxidesynthases 2, transcription factor AP-1, vascular endothelial growth factor A, myc proto-oncogene protein and interleukin-1β. The results of GO and KEGG analysis indicated that the therapeutic targets of Xiao chengqitang for UC were mainly enriched in phosphatidylinositol 3-kinase-protein kinase B signaling pathway, inflammatory bowel disease, nuclear factor κB signaling pathway, calcium signaling pathway and peroxisome proliferators-activated receptor signaling pathway. Conclusions The potential mechanism of Xiao chengqitang in the treatment of UC may be that Xiao chengqitang acts on key therapeutic targets such as RAC-alpha serine/threonine-protein kinase, cellular tumor antigen p53, tumor necrosis factor-α, interleukin-6, prostaglandin-endoperoxidesynthases 2, vascular endothelial growth factor A and interleukin-1β, and participates in the regulation of phosphatidylinositol 3-kinase-protein kinase B signaling pathway, nuclear factor κB signaling pathway and calcium signaling pathway.
Objective To explore the potential molecular mechanism of Rhodiola crenulata (RC) for type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) by network pharmacology and molecular docking. Methods The target genes of T2DM and AD, the effective active components and targets of RC were identified through multiple public databases during March to August, 2022. The main active components and core genes of RC anti T2DM-AD were screened. The key genes were enrichment analyzed by gene ontology function and Kyoto gene and Kyoto Encyclopedia of Genes and Genomes. AutoDock Vina was used for molecular docking and binding energy calculation. Results A total of 5189 T2DM related genes and 1911 AD related genes were obtained, and the intersection result showed that there were 1418 T2DM-AD related genes. There were 48 active components of RC and 617 corresponding target genes. There were 220 crossing genes between RC and T2DM-AD. The main active components of RC anti T2DM-AD included kaempferol, velutin, and crenulatin. The key genes for regulation include ESR1, EGFR, and AKT1, which were mainly enriched in the hypoxia-inducible factor-1 signal pathway, estrogen signal pathway, and vascular endothelial growth factor signal pathway. The docking binding energies of the main active components of RC and key gene molecules were all less than −1.2 kcal/mol (1 kcal=4.2 kJ). Conclusions RC may play a role in influencing T2DM and AD by regulating the hypoxia-inducible factor-1 signaling pathway, estrogen signaling pathway, and vascular endothelial growth factor signaling pathway.