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Albiziae Flos (AF) has been experimentally proven to have an antidepressant effect. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of action of AF in depression has not been completely deciphered. This study used the network pharmacology method to construct a component-target-pathway network to explore the active components and potential mechanisms of action of AF. The methods included collection and screening of chemical components, prediction of depression-associated targets of the active components, gene enrichment, and network construction and analysis. Quercetin and 4 other active components were found to exert antidepressant effects mainly via monoaminergic neurotransmitters and cAMP signaling and neuroactive ligand-receptor interaction pathways. DRD2, HTR1A, and SLC6A4 were identified as important targets of the studied bioactive components of AF. This network pharmacology analysis provides guidance for further study of the antidepressant mechanism of AF.

This study explored the possible bioactive ingredients and target protein of Rostellularia procumbens (L.) Nees. The results of optical turbidimetry revealed that the ethyl acetate extraction obtained from R. procumbens (L.) Nees could inhibit platelet aggregation. Gene chip was used to investigate differentially expressed genes. According to the results of the gene chip, the targets of compounds isolated from the ethyl acetate extraction were predicted by network pharmacology. Computational studies revealed that chinensinaphthol methyl ether and neojusticin B may target the integrin αIIbβ3 protein. The results of Prometheus NT.48 and microscale thermophoresis suggested that the molecular interactions between the two compounds with purified integrin αIIbβ3 protein in the optimal test conditions were coherent with the docking results. To our best knowledge, this is the first report to state that chinensinaphthol methyl ether and neojusticin B target the integrin αIIbβ3 protein.

A pharmacological network of "component/target/pathway" for Rhizoma coptidis against type 2 diabetes (T2D) was established by network-pharmacology, and the active components of Rhizoma coptidis and its mechanism were explored. A literature-based and database study of the components of Rhizoma coptidis was carried out and screened by ADME parameters. The targets of Rhizoma coptidis were predicted by the ligand similarity method. Related pathways were analyzed with databases, and software was used to construct a "component/target/path" network. The mechanism was further confirmed by GEO database with R software. A total of 12 active components were screened from Rhizoma coptidis, involving 57 targets including MAPK1, STAT3, INSR, and 38 signaling pathways were associated with T2D. Related signaling pathways included essential pathways for T2D such as insulin resistance, and pathways that had indirect effect on T2D. It was suggested that Rhizoma coptidis may exert its effects against T2D through multi-component, multi-target, and multi-pathway forms.

Rubia cordifolia L. is widely used in Asia and its antihepatoma effect has been proved by in vitro and in vivo experiments. However, there are few studies on its specific mechanism. In the present study, the network pharmacology method was used to construct the component/target/pathway molecular regulatory network for the antihepatoma effect of Rubia cordifolia L. to explore the effective components of Rubia cordifolia L. and its potential mechanism. The chemical components of Rubia cordifolia L. were identified through literature and databases, and the components were evaluated and screened by drug likeness and pharmacokinetic characteristics (ADMET). The targets of active components were predicted according to the reverse pharmacophore matching model. The hepatic carcinoma-related genes were found in databases, and antihepatoma-related gene targets were selected through comparison. The functions of target genes and related pathways were analyzed and screened using the Database for Annotation, Visualization and Integrated Discovery, and the component/target/pathways network of antihepatoma effect of Rubia cordifolia L. was constructed using Cytoscape software. Finally, 16 active compounds were screened from Rubia cordifolia L., and 39 gene targets, including AKT1, mitogen-activated protein kinase 1, and epidermal growth factor receptor, were involved. Rubia cordifolia L. also affected the hepatitis B, phosphoinositide-3-kinase-protein kinase B, and mitogen-activated protein kinase signaling pathways. Many direct-acting tumor-related signaling pathways and indirect-acting hepatitis pathways inhibit the generation of liver cancer. The present study provided a scientific basis for further elucidating the mechanism of Rubia cordifolia L. against liver cancer.