The global depression population is showing a significant increase. Hemerocallis fulva L. is a common Traditional Chinese Medicine (TCM). Its flower buds are known to have ability to clear away heat and dampness, detoxify, and relieve depression. Ancient TCM literature shows that its roots have a beneficial effect in calming the spirit and even the temper in order to reduce the feeling of melancholy. Therefore, it is inferred that the root of Hemerocallis fulva L. can be used as a therapeutic medicine for depression. This study aims to uncover the pharmacological mechanism of the antidepressant effect of Hemerocallis Radix (HR) through network pharmacology method. During the analysis, 11 active components were obtained and screened using ADME—absorption, distribution, metabolism, and excretion— method. Furthermore, 267 HR targets and 740 depressive disorder (DD) targets were gathered from various databases. Then protein–protein interaction (PPI) network of HR and DD targets were constructed and cluster analysis was applied to further explore the connection between the targets. In addition, gene ontology (GO) enrichment and pathway analysis was applied to further verify that the biological process related to the target protein is associated with the occurrence of depression disorder. In conclusion, the most important bioactive components—anthraquinone, kaempferol, and vanillic acid—can alleviate depression symptoms by regulating MAOA, MAOB, and ESR1. The proposed network pharmacology strategy provides an integrating method to explore the therapeutic mechanism of multi-component drugs on a systematic level.

Background and objective: Based on comprehensive network-pharmacology and molecular docking analysis, this study was intended to unveil the multiple mechanisms of Si-Ni-San (SNS) in treating anxious insomnia. Methods: The compounds of SNS were meticulously analyzed, selected and standardized with references to their pharmacological attributes. The components included chaihu (Bupleurum chinense DC.), baishao (Paeonia lactiflora Pall.), zhishi (Citrus aurantium L.) and gancao (Glycyrrhiza uralensis Fisch. ex DC.). We used the Traditional Chinese Medicine System Pharmacology (TCMSP) Database, Traditional Chinese Medicines Integrated Database (TCMID), GeneCards database, therapeutic target database (TTD) and comparative toxicogenomic database (CTD) to construct the components-compounds-targets networks and used Cytoscape 3.9.1 software to visualize the outcome. Afterwards, the STRING database and Cytoscape 3.9.1 software were utilized to construct and visualize the protein-protein interaction (PPI) network analysis. In addition, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also conducted through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The molecular docking program was carried out using AutoDock 4.2 software to understand interactions between target receptors and compound ligands selected for study. Results: We thoroughly sorted and filtered 31 pharmacologically active compounds from SNS. Subsequently, several potential target genes were predicted, of which there were 59 target genes distinctly associated with anxious insomnia. The PPI analysis indicated that the core target proteins included AKT1, IL6, TNF, SLC6A4, MAOA and GABRA2. The results of our study indicated that SNS potentially remediates anxious insomnia by reducing inflammation, neurodegeneration, and cell apoptosis of neurons. In addition, GO and KEGG enrichment analysis results indicated that SNS could modulate multiple aspects of anxious insomnia through mechanisms related to pathways of neuroactive ligand-receptor interaction. These pathways include various kinds of synaptic transmission pathways, and anti-inflammatory activity associated with response pathways. When we compared the components-compounds-targets networks and the compounds-targets-synaptic pathways networks, the five active compounds, including beta-Sitosterol, Kaempferol, Tetramethoxyluteolin, Isorhamnetin and Shinpterocarpin, were selected to conduct molecular docking experiments. Eleven target proteins, (AKT1, SLC6A4, ADRB2, MAOA, ACHE, ESR1, CYP3A4, CHRNA7, GABRA2, HTR2A and NOS3), which also play significant roles in regulating serotonergic, cholinergic, dopaminergic and GABAergic systems in the PPI network, were selected to act as receptors in molecular docking trials. The results showed that docking pairs isorhamnetin-AKT1, isorhamnetin-SLC6A4, β-sitosterol-MAOA, β- sitosterol-ACHE, isorhamnetin-CHRNA7 and shinpterocarpin-GABRA2 provided the most stable conformations of ligand-receptor binding between key compounds and core target proteins in the SNS. Conclusion: In the study, we offer a computational result, revealing that SNS may alleviate sleep disorders associated with anxiety through a “multi-compounds, multi-targets, and multi-pathways” mechanism. The network-pharmacology and molecular docking outcomes could theoretically confirm the anti-anxiety and anti-insomnia effects of SNS. Although this research is purely statistical and systematic without empirical validation, it serves as a stepping stone and cornerstone for subsequent experimental investigations.