Integrative Analysis of TCM Compounds

Compound chemical composition and drug targets were collected and predicted. Dangshen (Codonopsis pilosula (Franch.) Nannf), Huangqin (Scutellaria baicalensis Georgi), Baizhu (Atractylodes macrocephala Koidz), Fuling (Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb), Huangqi (Astragalus membranaceus (Fisch.) Bunge), Yiyiren (Semen Coicis), Wumei (Fructus Mume), Fangfeng (Saposhnikovia divaricata (Turcz.) Schischk), Chenpi (Citrus reticulata Blanco), Niuxi (Achyranthes bidentata Blume), and Gancao (Glycyrrhiza uralensis Fisch) were inputted to the TCMSP database (https://old.tcmsp-e.com/tcmsp.php), to collect all compounds [12 (link)]. Then, according to the pharmacokinetic principle, the suitable compounds are screened based on oral bioavailability (OB) ≥ 30% and drug-like index (DL) ≥ 0.18. Drug target data were obtained from DrugBank (https://go.drugbank.com/) and standardized using the UniProt (https://www.Uniprot.org/) database [13 (link)]. Based on GeneCards (https://www.genecards.org/) and OMIM-NCBI databases (https://www.ncbi.nlm.nih.gov/omim), IBD as keyword was used to screen disease targets, while for species selection “Homosapiens” was used. Draw Venn Diagrams tool in R software is used to process drug targets and disease targets obtained in the above steps to obtain the intersection gene targets and output Venn Diagram for display.
PPI network interaction analysis was performed on the active chemical components and core targets of Qinghua Jianpi Recipe by using the STRING database and Cytoscape3.7.1 software. According to the requirements of Cytoscape, the “source-target” data table was constructed, and the NetworkAnalyzer plug-in was used to construct the regulation network of TCM, active component, and target. In the generated regulation network, nodes represent the interaction between TCM, active component, and target, and edges represent the interaction between active the component and target disease. Furthermore, MCC algorithm of CytoHubba plug-in was used to calculate and construct PPI network of each target. Based on Bioconductor (https://www.bioconductor.org/) in the R package (https://www.r-project.org/) and clusterProfiler 3.12.0 to GO (gene ontology) core target function and KEGG pathway enrichment analysis (KEGG pathway analysis), Homo sapiens was selected and a threshold P < 0.05 was set. According to the results, the core target-critical pathway network was conducted in Cytoscape 3.7.1 software.