Colorectal cancer (CRC) is the third most diagnosed cancer worldwide and is a significant cause of cancer-related deaths. Previous studies have observed that Coptis chinensis (CC) and Mume Fructus (MF) are effective against CRC, enteritis, and intestinal dysbiosis, but the chemical and pharmacological mechanisms remain poorly understood. In this study, we employed pharmacological network analysis to reveal mechanisms underlying the therapeutic effect of CC and MF against CRC. All compounds and targeted genes were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). Differentially expressed genes (DEGs) were identified based on GSE146587, GSE156720, and GSE184093 datasets. A protein-protein interaction (PPI) network was constructed to identify putative target genes of CC and MF. Ten key targeted genes were identified, including CCND1, ICAM1, IL1B, IL-6, MMP1, MMP3, MMP9, MYC, SERPINE1, and VEGFA. Among these genes, six (ICAM1, IL1B, IL-6, MMP1, MMP3, MMP9, and SERPINE1) were positively correlated with levels of effector memory CD4 T cells and natural killer T cells, and three (CCND1, MYC, and VEGFA) were negatively correlated with type 17 T helper cells and CD56dim natural killer cells. Molecular docking analysis showed that four compounds of CC and MF (kaempferol, oleanolic acid, quercetin, and ursolic acid) could affect CRC by interacting with target genes. Our study proved that pharmacological analysis could reliably assess the mechanism of traditional Chinese medicines for treating cancer.

Background. Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder with complex pathogenesis. Currently, the pathogenesis of ASD is not fully understood. Moreover, current treatments do not effectively alleviate the primary symptoms of ASD social disorder (SCDA). Jiawei Yinhuo Tang (JWYHT) is an improved version of the classic prescription Yinhuo Tang. Although this medication has been shown to improve social behavior in ASD patients, the mechanism by which it works remains unknown. Methods. In this study, network pharmacology bioinformatics analysis was used to identify the key targets, biological functions, and signal pathways of JWYHT in SCDA. Then, molecular docking and molecular dynamic simulation were used to validate the activity and stability of the active ingredient and the target protein during the binding process. Results. The analysis identified 157 key targets and 9 core targets of JWYHT (including proto-oncogene (FOS), caspase 3 (CASP3), mitogen-activated protein kinase-3 (MAPK3), interleukin-6 (IL6), mitogen-activated protein kinase-1 (MAPK1), tumor necrosis factor (TNF), mitogen-activated protein kinase-8 (MAPK8), AKT serine/threonine kinase 1 (AKT1), and 5-hydroxytryptamine receptor 1B (5HT1B)) in SCDA. In addition, the Kyoto Encyclopedia of Gene and Genome results, as well as the staggering network analyses, revealed 20 biological processes and 20 signal pathways targeted by JWYHT in SCDA. Finally, molecular docking analysis was used to determine the binding activity of the main active components of JWYHT to the key targets. The binding activity and stability of methyl arachidonate and MAPK8 were demonstrated using molecular dynamics simulation. Conclusion. This study demonstrates that JWYHT regulates neuronal development, synaptic transmission, intestinal and cerebral inflammatory response, and other processes in SCDA.

Introduction. The objective of our study is to explore the potential active ingredients and activity of Ginseng and Astragalus decoction (GAD) in the treatment of malignant pleural effusion (MPE) by using network pharmacology and molecular docking technologies. Methods. The active ingredients and corresponding targets of Ginseng and Astragalus were extracted from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The relevant targets of malignant pleural effusion (MPE) were searched in the disease databases. Overlapping targets of Ginseng and Astragalus and the corresponding targets of MPE were obtained to define the effective target of GAD for the treatment of MPE. The STRING database was applied to construct a predicted protein-protein interaction network for intersected targets. The Cytoscape software was used to screen key targets with a therapeutic potential. Using the Metascape database, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis on the targets identified in the study. PyMOL and AutoDock Vina were used to molecularly dock the selected key components to their respective key targets for MPE treatment. Results. The core target network revealed 22 main active ingredients, 26 main targets, and 16 signaling pathways in GAD. Molecular docking revealed 6 targets (AKT serine/threonine kinase 1, intercellular adhesion molecule, Jun proto-oncogene, peroxisome proliferator activated receptor gamma, prostaglandin-endoperoxide synthase 2, and tumor necrosis factor) that could partially dock with kaempferol, frutinone A, ginsenoside RH2, formononetin, and quercetin. Conclusions. Several components, targets, and signaling pathways of GAD contribute to the treatment of MPE, which suggests a rationale for further investigation on GAD’s active molecule and mechanism of action in the clinical application of MPE.