Computational Network Pharmacology-Based Strategy to Capture Key Functional Components and Decode the Mechanism of Chai-Hu-Shu-Gan-San in Treating Depression

Potential antidepressant effects of Traditional Chinese botanical drug formula Chaihu-Shugan-San and its active ingredients

Background: Depression is a severe mental disorder that poses a significant threat to both the physical and mental wellbeing of individuals. Currently, there are various methods for treating depression, including traditional Chinese herbal formulations like Chaihu-Shugan-San (CSS), which have shown effective antidepressant effects in both clinical and animal research. Objective: This review aims to provide a comprehensive synthesis of evidence related to CSS, considering both preclinical and clinical studies, to uncover its potential multi-level, multi-pathway, and multi-target mechanisms for treating depression and identify its active ingredients. Methods: A thorough search was conducted in electronic databases, including PubMed, MEDLINE, Web of Science, Google Scholar, CNKI, and Wanfang, using keywords such as "Chaihu Shugan" and "depression" to retrieve relevant literature on CSS and its active ingredients. The review process adhered to the PRISMA guidelines. Results: This review consolidates the mechanisms underlying antidepressant effects of CSS and its active ingredients. It emphasizes its involvement in the regulation of monoaminergic neurotransmitter systems, synaptic plasticity, and the hypothalamic-pituitary-adrenal axis, among other aspects. Conclusion: CSS exerts a pivotal role in treating depression through various pathways, including the monoaminergic neurotransmitter system, the hypothalamic-pituitary-adrenal axis, synaptic plasticity, inflammation, brain-derived neurotrophic factor levels, and the brain-gut axis. This review facilitates a comprehensive understanding of the current state of CSS research, fostering an in-depth exploration of the etiological mechanisms of depression and the potential discovery of novel antidepressant drugs.

Insight into Nephrotoxicity and Processing Mechanism of Arisaema erubescens (Wall.) Schott by Metabolomics and Network Analysis

Background

Arisaematis Rhizome (AR) has been used as a damp-drying, phlegm-resolving, wind-expelling, pain-alleviating, and swelling-relieving drug for thousands of years. However, the toxicity limits its clinical applications. Therefore, AR is usually processed (Paozhi in Chinese) prior to clinical use. In this study, the integration of ultra-high performance liquid chromatography-quadrupole/ time-of-flight mass spectrometry-based metabolomics and network analysis was adopted to investigate the metabolic shifts induced by AR and explore the processing mechanism.

Materials and Methods

Extracts of crude and processed AR products (1g/kg) were intragastrically administered to rats once daily for four consecutive weeks. The renal function was evaluated by blood urea nitrogen, creatinine, interleukin-1 beta (IL-1β) and tumor necrosis factor-alpha (TNF-α), malondialdehyde (MDA), super oxide dismutase (SOD), the ratio of glutathione/glutathione disulfide (GSH/GSSH), glutathione peroxidase (GSH-Px) and histopathological examination. Furthermore, the chemical composition of AR was clarified by ultra-high performance liquid chromatography-quadrupole/ time-of-flight mass spectrometry, after which the integration of metabolomics and network analysis was adopted to investigate the metabolic shifts induced by AR and explore the processing mechanism.

Results

Crude AR caused renal damage by stimulating inflammation and oxidative stress, as confirmed by the increased production of IL-1β, TNF-α and MDA, and decreased levels of SOD, GSH/GSSH and GSH-Px. Processing with ginger juice, alumen and bile juice alleviated the damage to kidney. Metabolomics results showed that a total of 35 potential biomarkers enriched in amino acid metabolism, glycerophospholipid metabolism, fatty acid-related pathways, etc. were deduced to be responsible for the nephrotoxicity of AR and the toxicity-reducing effect of processing.

Conclusion

This work provided theoretical and data support for the in-depth study of the processing mechanism, showing that processing reduces AR nephrotoxicity through multiple metabolic pathways.

Screening of key functional components of Taohong Siwu Decoction on ischemic stroke treatment based on multiobjective optimization approach and experimental validation

BACKGROUND

Taohong Siwu Decoction (THSWD) is a widely used traditional Chinese medicine (TCM) prescription in the treatment of ischemic stroke. There are thousands of chemical components in THSWD. However, the key functional components are still poorly understood. This study aimed to construct a mathematical model for screening of active ingredients in TCM prescriptions and apply it to THSWD on ischemic stroke.

METHODS

Botanical drugs and compounds in THSWD were acquired from multiple public TCM databases. All compounds were initially screened by ADMET properties. SEA, HitPick, and Swiss Target Prediction were used for target prediction of the filtered compounds. Ischemic stroke pathological genes were acquired from the DisGeNet database. The compound-target-pathogenic gene (C-T-P) network of THSWD was constructed and then optimized using the multiobjective optimization (MOO) algorithm. We calculated the cumulative target coverage score of each compound and screened the top compounds with 90% coverage. Finally, verification of the neuroprotective effect of these compounds was performed with the oxygen-glucose deprivation and reoxygenation (OGD/R) model.

RESULTS

The optimized C-T-P network contains 167 compounds, 1,467 predicted targets, and 1,758 stroke pathological genes. And the MOO model showed better optimization performance than the degree model, closeness model, and betweenness model. Then, we calculated the cumulative target coverage score of the above compounds, and the cumulative effect of 39 compounds on pathogenic genes reached 90% of all compounds. Furthermore, the experimental results showed that decanoic acid, butylphthalide, chrysophanol, and sinapic acid significantly increased cell viability. Finally, the docking results showed the binding modes of these four compounds and their target proteins.

CONCLUSION

This study provides a methodological reference for the screening of potential therapeutic compounds of TCM. In addition, decanoic acid and sinapic acid screened from THSWD were found having potential neuroprotective effects first and verified with cell experiments, however, further in vitro and in vivo studies are needed to explore the precise mechanisms involved.

Quantification of promoting efficiency and reducing toxicity of Traditional Chinese Medicine: A case study of the combination of Tripterygium wilfordii hook. f. and Lysimachia christinae hance in the treatment of lung cancer

Traditional Chinese medicine (TCM) usually acts in the form of compound prescriptions in the treatment of complex diseases. The herbs contained in each prescription have the dual nature of efficiency and toxicity due to their complex chemical component, and the principle of prescription is usually to increase efficiency and reduce toxicity. At present, the studies on prescriptions have mainly focused on the consideration of the material basis and possible mechanism of the action mode, but the quantitative research on the compatibility rule of increasing efficiency and reducing toxicity is still the tip of the iceberg. With the extensive application of computational pharmacology technology in the research of TCM prescriptions, it is possible to quantify the mechanism of synergism and toxicity reduction of the TCM formula. Currently, there are some classic drug pairs commonly used to treat complex diseases, such as Tripterygium wilfordii Hook. f. with Lysimachia christinae Hance for lung cancer, Aconitum carmichaelii Debeaux with Glycyrrhiza uralensis Fisch. in the treatment of coronary heart disease, but there is a lack of systematic quantitative analysis model and strategy to quantitatively study the compatibility rule and potential mechanism of synergism and toxicity reduction. To address this issue, we designed an integrated model which integrates matrix decomposition and shortest path propagation, taking into account both the crosstalk of the effective network and the propagation characteristics. With the integrated model strategy, we can quantitatively detect the possible mechanisms of synergism and attenuation of Tripterygium wilfordii Hook. f. and Lysimachia christinae Hance in the treatment of lung cancer. The results showed the compatibility of Tripterygium wilfordii Hook. f. and Lysimachia christinae Hance could increase the efficacy and decrease the toxicity of lung cancer treatment through MAPK pathway and PD-1 checkpoint pathway in lung cancer.

Radix Salvia miltiorrhiza for Ankylosing Spondylitis: Determining Potential Inflammatory Molecular Targets and Mechanism Using Network Pharmacology

Radix Salvia miltiorrhiza (RSM) is widely used for the clinical improvement of inflammatory diseases. However, the actions of RSM in the treatment of ankylosing spondylitis (AS) have not been fully explored. Therefore, this study was designed to use retrospective clinical data mining approach to understand the effects of RSM on AS-related immuno-inflammatory processes, use network pharmacology to predict therapeutic targets of RSM, and to further investigate the pharmacological molecular mechanism in vitro. RSM treatment has a long-term correlation with the improvement of AS-related immuno-inflammatory indicators through computational models. We established protein-protein interaction networks, conducted KEGG analysis to enrich significant TNF pathways, and finally obtained three core targets of RSM in the treatment of AS, namely, prostaglandin endoperoxide synthase 2 (PTGS2), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-alpha). Screening of RSM active ingredients with node degree greater than 20 yielded cryptotanshinone and tanshinone IIA, and previous studies have reported their anti-inflammatory effects. In vitro, both cryptotanshinone and tanshinone IIA significantly inhibited the expressions of PTGS2, IL-6, and TNF-α in peripheral blood mononuclear cells in AS patients. In conclusion, cryptotanshinone and tanshinone IIA, which are the active components of RSM, may inhibit the activation of TNF signaling pathway in AS patients by downregulating the expression of PTGS2, IL-6, and TNF-α. These findings illustrate that RSM may be a promising therapeutic candidate for AS, but further validation is required.

Uncovering Hidden Mechanisms of Different Prescriptions Treatment for Osteoporosis via Novel Bioinformatics Model and Experiment Validation

Osteoporosis (OP) is a systemic disease susceptible to fracture due to the decline of bone mineral density and bone mass, the destruction of bone tissue microstructure, and increased bone fragility. At present, the treatments of OP mainly include bisphosphonates, hormone therapy, and RANKL antibody therapy. However, these treatments have observable side effects and cannot fundamentally improve bone metabolism. Currently, the prescription of herbal medicine and their derived proprietary Chinese medicines are playing increasingly important roles in the treatment of OP due to their significant curative effects and few side effects. Among these prescriptions, Gushukang Granules (GSK), Xianling Gubao Capsules (XLGB), and Er-xian Decoction (EXD) are widely employed at the clinic on therapy of OP, which also is in line with the compatibility principle of “different treatments for the same disease” in herbal medicine. However, at present, the functional interpretation of “different treatments for the same disease” in herbal medicine still lacks systematic quantitative research, especially on the detection of key component groups and mechanisms. To solve this problem, we designed a new bioinformatics model based on random walk, optimized programming, and information gain to analyze the components and targets to figure out the Functional Response Motifs (FRMs) of different prescriptions for the therapy of OP. The distribution of high relevance score, the number of reported evidence, and coverage of enriched pathways were performed to verify the precision and reliability of FRMs. At the same time, the information gain and target influence of each component was calculated, and the key component groups in all FRMs of each prescription were screened to speculate the potential action mode of different prescriptions on the same disease. Results show that the relevance score and the number of reported evidence of high reliable genes in FRMs were higher than those of the pathogenic genes of OP. Furthermore, the gene enrichment pathways in FRMs could cover 79.6, 81, and 79.5% of the gene enrichment pathways in the component-target (C-T) network. Functional pathway enrichment analysis showed that GSK, XLGB, and EXD all treat OP through osteoclast differentiation (hsa04380), calcium signaling pathway (hsa04020), MAPK signaling pathway (hsa04010), and PI3K-Akt signaling pathway (hsa04151). Combined with experiments, the key component groups and the mechanism of “different treatments for the same disease” in the three prescriptions and proprietary Chinese medicines were verified. This study provides methodological references for the optimization and mechanism speculation of Chinese medicine prescriptions and proprietary Chinese medicines.