Comprehensive chemical profiling of Jia-Wei-Qi-Fu-Yin and its network pharmacology-based analysis on Alzheimer's disease

Comprehensive chemical profiling and quantitative analysis of ethnicYi medicine Miao-Fu-Zhi-Tong granules using UHPLC-MS/MS

Developing analytical methods for the chemical components of natural medicines remains a challenge due to its diversity and complexity. Miao-Fu-Zhi-Tong (MFZT) granules, an ethnic Yi herbal prescription, comprises 10 herbs and has been clinically applied for gouty arthritis (GA) therapy. Herein, a series of chemical profiling strategies including in-house library matching, molecular networking and MS/MS fragmentation behavior validation based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) were developed for qualitative analysis of MFZT granules. A total of 207 compounds were identified or characterized in which several rare guanidines were discovered and profiled into alkyl substituted or cyclic subtypes. Moreover, network pharmacology analysis indicated that MFZT's anti-gout mechanism was mostly associated with the nuclear factor kappa-B (NF-κB) signaling, nucleotide oligomerization domain (NOD)-like signaling and rheumatoid arthritis pathways, along with the synergistic effect of 84 potential active compounds. In addition, a quantitative analytical method was developed to simultaneously determine the 29 potential effective components. Among them, berberine, pellodendrine, 3-feruloylquinic acid, neoastilbin, isoacteoside and chlorogenic acid derivatives at higher concentrations were considered as the chemical markers for quality control. These findings provide a holistic chemical basis for MFZT granules and will support the development of effective analytical methods for the herbal formulas of natural medicines.

Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis

Xuanbai Chengqi Decoction (XBCQD), a classic traditional Chinese medicine, has been widely used to treat COVID-19 in China with remarkable curative effect. However, the chemical composition and potential therapeutic mechanism is still unknown. Here, we used multiple open-source databases and literature mining to select compounds and potential targets for XBCQD. The COVID-19 related targets were collected from GeneCards and NCBI gene databases. After identifying putative targets of XBCQD for the treatment of COVID-19, PPI network was constructed by STRING database. The hub targets were extracted by Cytoscape 3.7.2 and MCODE analysis was carried out to extract modules in the PPI network. R 3.6.3 was used for GO enrichment and KEGG pathway analysis. The effective compounds were obtained via network pharmacology and bioinformatics analysis. Drug-likeness analysis and ADMET assessments were performed to select core compounds. Moreover, interactions between core compounds and hub targets were investigated through molecular docking, molecular dynamic (MD) simulations and MM-PBSA calculations. As a result, we collected 638 targets from 61 compounds of XBCQD and 845 COVID-19 related targets, of which 79 were putative targets. Based on the bioinformatics analysis, 10 core compounds and 34 hub targets of XBCQD for the treatment of COVID-19 were successfully screened. The enrichment analysis of GO and KEGG indicated that XBCQD mainly exerted therapeutic effects on COVID-19 by regulating signal pathways related to viral infection and inflammatory response. Meanwhile, the results of molecular docking showed that there was a stable binding between the core compounds and hub targets. Moreover, MD simulations and MM-PBSA analyses revealed that these compounds exhibited stable conformations and interacted well with hub targets during the simulations. In conclusion, our research comprehensively explained the multi-component, multi-target, and multi-pathway intervention mechanism of XBCQD in the treatment of COVID-19, which provided evidence and new insights for further research.

Decoding the Mechanism of CheReCunJin Formula in Treating Sjögren’s Syndrome Based on Network Pharmacology and Molecular Docking

Background

Sjögren's syndrome (SS) is a chronic autoimmune disease characterized by progressive oral and ocular dryness that correlates poorly with autoimmune damage to the glands. CheReCunJin (CRCJ) formula is a prescription formulated according to the Chinese medicine theory for SS treatment.

Objective

This study aimed to explore the underlying mechanisms of CRCJ against SS.

Methods

The databases, including Traditional Chinese Medicine System Pharmacology, Encyclopedia of Traditional Chinese Medicine, Bioinformatics Analysis Tool for the molecular mechanism of Traditional Chinese Medicine, and Traditional Chinese Medicine Integrated Databases, obtained the active ingredients and predicted targets of CRCJ. Then, DrugBank, Therapeutic Target Database, Genecards, Comparative Toxicogenomics Database, and DisGeNET disease databases were used to screen the predicted targets of SS. Intersected targets of CRCJ and SS were visualized by using Venn diagrams. The overlapping targets were uploaded to the protein–protein interaction network analysis search tool. Cytoscape 3.8.2 software constructed a “compound-targets-disease” network. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analyses characterized potential targets' biological functions and pathways. AutoDock Vina 1.1.2 software was used to research and verify chemical effective drug components and critical targets.

Results

From the database, we identified 878 active components and 2578 targets of CRCJ, and 827 SS-related targets. 246 SS-related genes in CRCJ were identified by intersection analysis, and then ten hub genes were identified as crucial potential targets from PPI, including ALB, IL-6, TNF, INS, AKT1, IL1B, VEGFA, TP53, JUN, and TLR4. The process of CRCJ action against SS was mainly involved in human cytomegalovirus infection and Th17 cell differentiation, as well as the toll-like receptor signaling and p53 signaling pathways. Molecular docking showed that the bioactive compounds of CRCJ had a good binding affinity with hub targets.

Conclusions

The results showed that CRCJ could activate multiple pathways and treat SS through multiple compounds and targets. This study lays a foundation for better elucidation of the molecular mechanism of CRCJ in the treatment of SS, and also provides basic guidance for future research on Chinese herbal compounds.

Alzheimer-Compound Identification Based on Data Fusion and forgeNet_SVM

Rapid screening and identification of potential candidate compounds are very important to understand the mechanism of drugs for the treatment of Alzheimer's disease (AD) and greatly promote the development of new drugs. In order to greatly improve the success rate of screening and reduce the cost and workload of research and development, this study proposes a novel Alzheimer-related compound identification algorithm namely forgeNet_SVM. First, Alzheimer related and unrelated compounds are collected using the data mining method from the literature databases. Three molecular descriptors (ECFP6, MACCS, and RDKit) are utilized to obtain the feature sets of compounds, which are fused into the all_feature set. The all_feature set is input to forgeNet_SVM, in which forgeNet is utilized to provide the importance of each feature and select the important features for feature extraction. The selected features are input to support vector machines (SVM) algorithm to identify the new compounds in Traditional Chinese Medicine (TCM) prescription. The experiment results show that the selected feature set performs better than the all_feature set and three single feature sets (ECFP6, MACCS, and RDKit). The performances of TPR, FPR, Precision, Specificity, F1, and AUC reveal that forgeNet_SVM could identify more accurately Alzheimer-related compounds than other classical classifiers.

A database-guided integrated strategy for comprehensive chemical profiling of traditional Chinese medicine

A comprehensive chemical profiling of traditional Chinese medicine is the basic issue for further pharmacological research and quality assessment. To facilitate chemical identification and potential components discovery, the present study proposed an integrated identification strategy guided by a self-built component database constructed from literatures to carry out the global profiling of complex matrixes. Lanqin Oral Liquid was applied as example to validate the feasibility of this strategy. Based on LQL Component Database containing 710 compounds, modified MDF windows was established to extract the interested analogues, isoquinoline alkaloids, flavonoids and iridoid glycosides, according to their regular integral masses and mass defect. For compounds with characteristic substructures, such as quinic acids, crocins and some glycoside derivatives, the associated neutral losses and diagnostic fragment ions were collected to assist in profiling. Directly matching the m/z or formulas in database was proposed to components with limited regularity of accurate masses and substructures, like indole alkaloids, sesquiterpenes and some nucleosides. Eventually, 170 ions of 1038 precursor ions were identified or temporarily deduced, including 59 alkaloids, 36 flavonoids, 48 terpenoids, 24 organic acids and their derivatives, 2 oligosaccharides, and 1 lignans. Among them, 52 putative compounds were confirmed by chemical standards. The results indicated that the database-oriented identification strategy could locate potential components quickly and eliminate interfering ions, which have the potential for in-depth analysis of compounds.

Network Pharmacology and Molecular Docking-Based Strategy to Investigate the Multitarget Mechanisms of Shenqi Yizhi Granule on Alzheimer's Disease

Background

Traditional Chinese herbal medicine draws more attention to explore an effective therapeutic strategy for Alzheimer's disease (AD). Shenqi Yizhi granule (SQYG), a Chinese herbal recipe, has been applied to ameliorate cognitive impairment in mild-to-moderate AD patients. However, the overall molecular mechanism of SQYG in treating AD has not been clarified.

Objective

This study aimed to investigate the molecular mechanism of SQYG on AD using an integration strategy of network pharmacology and molecular docking.

Methods

The active compounds of SQYG and common targets between SQYG and AD were screened from databases. The herb-compound network, compound-target network, and protein-protein interaction network were constructed. The enrichment analysis of common targets and molecular docking were performed.

Results

816 compounds and 307 common targets between SQYG and AD were screened. KEGG analysis revealed that common targets were mainly enriched in lipid metabolism, metal ion metabolism, IL-17 signaling pathway, GABA receptor signaling, and neuroactive ligand-receptor interaction. Molecular docking analysis showed high binding affinity between ginsenoside Rg1 and Aβ _1-42, tanshinone IIA and BACE1, baicalin, and AchE.

Conclusions

The therapeutic mechanisms of SQYG on AD were associated with regulating lipid metabolism, metal ion metabolism, IL-17 signaling pathway, and GABA receptor signaling. Ginsenoside Rg1, tanshinone IIA, baicalin, astragaloside IV, and folic acid may play an important role in AD treatment.

Mechanisms Underlying the Action of Ziziphi Spinosae Semen in the Treatment of Insomnia: A Study Involving Network Pharmacology and Experimental Validation

Purpose: This study aimed to investigate the potential mechanisms and related bioactive components of ZSS for the treatment of insomnia. Method: The insomnia model of rat induced by PCPA was established. After oral administration of ZSS extract, the general morphological observation, pentobarbital sodium-induced sleep test and histopathological evaluation were carried out. Network pharmacology, assisted by UHPLC-Q-Exactive-MS/MS analysis, was developed to identify the targets of ZSS in the treatment of insomnia, as well as the corresponding signaling pathways. In addition, we validated the identified targets and pathways by RT-qPCR and immunohistochemical analysis. Results: The pentobarbital sodium-induced sleep test, determination of 5-HT and GABA levles in hypothalamic tissues and HE staining showed that ZSS extract was an effective treatment for insomnia. Network pharmacology analysis identified a total of 19 candidate bioactive ingredients in ZSS extract, along with 433 potentially related targets. Next, we performed protein-protein interaction (PPI), MCODE clustering analysis, GO functional enrichment analysis, KEGG pathway enrichment analysis, and ingredient-target-pathway (I-T-P) sub-networks analysis. These methods allowed us to investigate the synergistic therapeutic effects of crucial pathways, including the serotonergic and GABAergic synapse pathways. Our analyses revealed that palmitic acid, coclaurine, jujuboside A, N-nornuciferine, caaverine, magnoflorine, jujuboside B, and betulinic acid, all played key roles in the regulation of these crucial pathways. Finally, we used the PCPA-induced insomnia in rats to validate the data generated by network pharmacology; these in vivo experiments clearly showed that pathways associated with the serotonergic and GABAergic system were activated in the rats model. Furthermore, ZSS treatment significantly suppressed high levels of HTR1A, GABRA1, and GABRG2 expression in the hypothalamus and reduced the expression levels of HTR2A. Conclusion: Based on the combination of comprehensive network pharmacology and in vivo experiments, we successfully identified the potential pharmacological mechanisms underlying the action of ZSS in the treatment of insomnia. The results provide a theoretical basis for further development and utilization of ZSS, and also provide support for the development of innovative drugs for the treatment of insomnia.

Network Pharmacology and Molecular Docking-Based Prediction of the Mechanism of Qianghuo Shengshi Decoction against Rheumatoid Arthritis

Qianghuo Shengshi decoction (QHSSD) is a classical Chinese medicine formula, which is used in clinical practice for the treatment of rheumatoid arthritis (RA) in China. However, the pharmacological mechanism of QHSSD on RA has remained unclear by now. We collected and screened active compounds and its potential targets by the pharmacology platform of Chinese herbal medicines. In addition, the therapeutic targets of RA were obtained and selected from databases. Network construction analyzed that 128 active compounds may act on 87 candidate targets and identified a total of 18 hub targets. GO annotation and KEGG enrichment investigated that the action mechanism underlying the treatment of RA by QHSSD might be involved in cell proliferation, angiogenesis, anti-inflammation, and antioxidation. Finally, molecular docking verification showed that TP53, VEGFA, TNF, EGFR, and NOS3 may be related to the RA treatment and molecular dynamics simulation showed the stability of protein-ligand interactions. In this work, QHSSD might exert therapeutic effect through a multicomponent, multitarget, and multipathway in RA from a holistic aspect, which provides basis for its mechanism of action and subsequent experiments.

A network pharmacology-based study on key pharmacological pathways and targets of Qi Fu Yin acting on Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a central nervous system (CNS) disease characterized by progressive cognitive dysfunction and memory loss. Qi Fu Yin is mainly used to treat dementia, particularly AD, in the clinic, but its comprehensive mechanisms are not known.

OBJECTIVE

In this research, we aimed to investigate the mechanisms of Qi Fu Yin in AD by network pharmacology and molecular docking.

METHODS

First, the chemical constituents in Qi Fu Yin were obtained from five databases and classified according to their structure. Targets of chemical constituents and AD-related targets were also collected from the databases. Then, overlapping genes between Qi Fu Yin and AD were identified by intersection analysis. MetaCore was used to gather enrichment information. Combination synergy analysis was performed by Cytoscape. After ligand-receptor docking, the binding affinity was verified by ADP-Glo™ kinase assay and fluorescence resonance energy transfer (FRET) assay.

RESULTS

We found 12 classes with 977 components in Qi Fu Yin. A total of 511 compounds and 577 potential target proteins in Qi Fu Yin were found to be related to AD. The pathways of Qi Fu Yin in AD included oxidative stress and immune response. There was the best binding affinity between 11 pairs of genes and compounds. Furthermore, CDK5 was inhibited by nepetin with an IC₅₀ of 3.172 μM and kaempferol with an IC₅₀ of 2.659 μM. Ceanothic acid and 18 beta-glycyrrhetinic acid inhibited GSK3β, and the IC₅₀ values were 8.732 μM and 8.06 μM, respectively.

CONCLUSION

Qi Fu Yin might alleviate Tau hyperphosphorylation by nepetin, kaempferol, ceanothic acid and 18 beta-glycyrrhetinic acid.

Network Pharmacology Analysis and Molecular Characterization of the Herbal Medicine Formulation Qi-Fu-Yin for the Inhibition of the Neuroinflammatory Biomarker iNOS in Microglial BV-2 Cells: Implication for the Treatment of Alzheimer's Disease

Aberrant microglial activation drives neuroinflammation and neurodegeneration in Alzheimer's disease (AD). The present study is aimed at investigating whether the herbal formula Qi-Fu-Yin (QFY) could inhibit the inflammatory activation of cultured BV-2 microglia. A network pharmacology approach was employed to predict the active compounds of QFY, protein targets, and affected pathways. The representative pathways and molecular functions of the targets were analyzed by Gene Ontology (GO) and pathway enrichment. A total of 145 active compounds were selected from seven herbal ingredients of QFY. Targets (e.g., MAPT, APP, ACHE, iNOS, and COX-2) were predicted for the selected active compounds based on the relevance to AD and inflammation. As a validation, fractions were sequentially prepared by aqueous extraction, ethanolic precipitation, and HPLC separation, and assayed for downregulating two key proinflammatory biomarkers iNOS and COX-2 in lipopolysaccharide- (LPS-) challenged BV-2 cells by the Western blotting technique. Moreover, the compounds of QFY in 90% ethanol downregulated iNOS in BV-2 cells but showed no activity against COX-2 induction. Among the herbal ingredients of QFY, Angelicae Sinensis Radix and Ginseng Radix et Rhizoma contributed to the selective inhibition of iNOS induction. Furthermore, chemical analysis identified ginsenosides, especially Rg3, as antineuroinflammatory compounds. The herbal formula QFY may ameliorate neuroinflammation via downregulating iNOS in microglia.