Network-based modeling of herb combinations in traditional Chinese medicine

Dietary Chinese herbal formula supplementation improves yolk fatty acid profile in aged laying hens

Chinese herbal formula (CHF) has the potential to improve the performance of aged laying hens through integrated regulation of various physiological functions. The present study aimed to investigate the effects of dietary CHF supplementation on the yolk fatty acid profile in aged laying hens. A total of 144 healthy 307-day-old Xinyang black-feather laying hens were randomly allocated into two groups: a control group (CON, fed a basal diet) and a CHF group (fed a basal diet supplemented with 1% CHF; contained 0.30% Leonurus japonicus Houtt., 0.20% Salvia miltiorrhiza Bge., 0.25% Ligustrum lucidum Ait., and 0.25% Taraxacum mongolicum Hand.-Mazz. for 120 days). The fatty acid concentrations in egg yolks were analyzed using a targeted metabolomics technology at days 60 and 120 of the trial. The results showed that dietary CHF supplementation increased (p < .05) the concentrations of several saturated fatty acids (SFA, including myristic acid and stearic acid), monounsaturated fatty acids (MUFA, including petroselinic acid, elaidic acid, trans-11-eicosenoic acid, and cis-11-eicosenoic acid), polyunsaturated fatty acids (PUFA, including linolelaidic acid, linoleic acid, γ-linolenic acid, α-linolenic acid, 11c,14c-eicosadienoic acid, eicosatrienoic acid, homo-γ-linolenic acid, arachidonic acid, and docosapentaenoic acid), and fatty acid indexes (total MUFA, n-3 and n-6 PUFA, PUFA/SFA, hypocholesterolemic/hypercholesterolaemic ratio, health promotion index, and desirable fatty acids) in egg yolks. Collectively, these findings suggest that dietary CHF supplementation could improve the nutritional value of fatty acids in egg yolks of aged laying hens, which would be beneficial for the production of healthier eggs to meet consumer demands.

Endotype-driven Co-module mechanisms of danhong injection in the Co-treatment of cardiovascular and cerebrovascular diseases: A modular-based drug and disease integrated analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Cardiovascular and cerebrovascular diseases are the leading causes of death worldwide and interact closely with each other. Danhong Injection (DHI) is a widely used preparation for the co-treatment of brain and heart diseases (CTBH). However, the underlying molecular endotype mechanisms of DHI in the CTBH remain unclear.

AIM OF THIS STUDY

To elucidate the underlying endotype mechanisms of DHI in the CTBH.

MATERIALS AND METHODS

In this study, we proposed a modular-based disease and drug-integrated analysis (MDDIA) strategy for elucidating the systematic CTBH mechanisms of DHI using high-throughput transcriptome-wide sequencing datasets of DHI in the treatment of patients with stable angina pectoris (SAP) and cerebral infarction (CI). First, we identified drug-targeted modules of DHI and disease modules of SAP and CI based on the gene co-expression networks of DHI therapy and the protein-protein interaction networks of diseases. Moreover, module proximity-based topological analyses were applied to screen CTBH co-module pairs and driver genes of DHI. At the same time, the representative driver genes were validated via in vitro experiments on hypoxia/reoxygenation-related cardiomyocytes and neuronal cell lines of H9C2 and HT22.

RESULTS

Seven drug-targeted modules of DHI and three disease modules of SAP and CI were identified by co-expression networks. Five modes of modular relationships between the drug and disease modules were distinguished by module proximity-based topological analyses. Moreover, 13 targeted module pairs and 17 driver genes associated with DHI in the CTBH were also screened. Finally, the representative driver genes AKT1, EDN1, and RHO were validated by in vitro experiments.

CONCLUSIONS

This study, based on clinical sequencing data and modular topological analyses, integrated diseases and drug targets. The CTBH mechanism of DHI may involve the altered expression of certain driver genes (SRC, STAT3, EDN1, CYP1A1, RHO, RELA) through various enriched pathways, including the Wnt signaling pathway.

Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study

Herbal medicines, particularly traditional Chinese medicines (TCMs), are a rich source of natural products with significant therapeutic potential. However, understanding their mechanisms of action is challenging due to the complexity of their multi-ingredient compositions. We introduced Herb-CMap, a multimodal fusion framework leveraging protein-protein interactions and herb-perturbed gene expression signatures. Utilizing a network-based heat diffusion algorithm, Herb-CMap creates a connectivity map linking herb perturbations to their therapeutic targets, thereby facilitating the prioritization of active ingredients. As a case study, we applied Herb-CMap to Suhuang antitussive capsule (Suhuang), a TCM formula used for treating cough variant asthma (CVA). Using in vivo rat models, our analysis established the transcriptomic signatures of Suhuang and identified its key compounds, such as quercetin and luteolin, and their target genes, including IL17A, PIK3CB, PIK3CD, AKT1, and TNF. These drug-target interactions inhibit the IL-17 signaling pathway and deactivate PI3K, AKT, and NF-κB, effectively reducing lung inflammation and alleviating CVA. The study demonstrates the efficacy of Herb-CMap in elucidating the molecular mechanisms of herbal medicines, offering valuable insights for advancing drug discovery in TCM.

Study on the material basis of Zhujing pill in treating fundus lesions through component analysis and network pharmacology

Zhujing pill (ZP) is a famous Chinese herbal formula that has been widely used to treat diabetic retinopathy, macular degeneration, retinitis pigmentosa and other fundus lesions. In this study, the material basis and mechanism of ZP in the treatment of fundus lesions were evaluated via the high-performance liquid chromatography fingerprint, ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry, network pharmacology and molecular docking. A total of 32 common components were found and 31 components were identified in 15 batches of ZP samples. Moreover, 134 common key targets and 17 putative active components that are connected to fundus lesions were identified. Molecular docking revealed that quercetin, kaempferol, isorhamnetin, 5-O-feruloylquinic acid, plantagoside and 2'-acetylacteoside have the ability to interact with the core targets such as AKT1, TP53, TNF, IL-6 and Jun. Our findings revealed that the therapeutic effects of ZP on fundus lesions are mediated by multiple components, targets and pathways, including at least six active ingredients and 11 targets. The study provides new ideas for further research on the material basis and mechanisms of traditional Chinese medicine prescriptions.

CDCS-TCM: A framework based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese medicine, with the feature of synergistic effects of multi-component, multi-pathway and multi-target, plays an important role in the treatment of cancer, cardiovascular and cerebrovascular diseases, etc. However, chemical components in traditional Chinese medicine are complex and most of the pharmacological mechanisms remain unclear, especially the relationships of chemical components change during the metabolic process.

AIM OF STUDY

Our aim is to provide a method based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine.

MATERIALS AND METHODS

We proposed a framework named CDCS-TCM to analyze the causality and dynamic correlation between substances in the metabolic process of traditional Chinese medicine. Our method mainly consists two parts. The first part is to discover the local and global causality by the causality network. The second part is to investigate the dynamic correlations and identify the essential substance by dynamic substance correlation network.

RESULTS

We developed a CDCS-TCM method to analyze the causality and dynamic correlation of substances. Using the XiangDan Injection for ischemic stroke as an example, we have identified the important substances in the metabolic process including substance pairs with strong causality and the dynamic changes of the core effector substance clusters.

CONCLUSION

The proposed framework will be useful for exploring the correlations of active ingredients in traditional Chinese medicine more effectively and will provide a new perspective for the elucidation of drug action mechanisms and the new drug discovery.

Predicting herb-disease associations using network-based measures in human protein interactome

BACKGROUND

Natural herbs are frequently used to treat diseases or to relieve symptoms in many countries. Moreover, as their safety has been proven for a long time, they are considered as main sources of new drug development. However, in many cases, the herbs are still prescribed relying on ancient records and/or traditional practices without scientific evidences. More importantly, the medicinal efficacy of the herbs has to be evaluated in the perspective of MCMT (multi-compound multi-target) effects, but most efforts focus on identifying and analyzing a single compound experimentally. To overcome these hurdles, computational approaches which are based on the scientific evidences and are able to handle the MCMT effects are needed to predict the herb-disease associations.

RESULTS

In this study, we proposed a network-based in silico method to predict the herb-disease associations. To this end, we devised a new network-based measure, WACP (weighted average closest path length), which not only quantifies proximity between herb-related genes and disease-related genes but also considers compound compositions of each herb. As a result, we confirmed that our method successfully predicts the herb-disease associations in the human protein interactome (AUROC = 0.777). In addition, we observed that our method is superior than the other simple network-based proximity measures (e.g. average shortest and closest path length). Additionally, we analyzed the associations between Brassica oleracea var. italica and its known associated diseases more specifically as case studies. Finally, based on the prediction results of the WACP, we suggested novel herb-disease pairs which are expected to have potential relations and their literature evidences.

CONCLUSIONS

This method could be a promising solution to modernize the use of the natural herbs by providing the scientific evidences about the molecular associations between the herb-related genes targeted by multiple compounds and the disease-related genes in the human protein interactome.

Network pharmacology to explore the mechanism of traditional Chinese medicine in the treatment of ground glass nodules

Background

Ground glass nodules (GGNs) in the lung are considered to be a high-risk factor of lung adenocarcinoma. Immediate surgery is not recommended for GGNs patients, and low-dose computed tomography (CT) is often used for observation and follow-up, which brings high psychological and economic burden to the patient.

Methods

Three traditional Chinese medicine (TCM) prescriptions for the treatment of GGNs were found through database including PubMed, Google Scholar, and China National Knowledge Infrastructure (CNKI), Scopus and so on. The possible targets of the active ingredients of the TCM preparations and the gene targets of GGNs were screened out from Traditional Chinese Medicine Systems Pharmacology (TCMSP), UniProt and GeneCards. Network visualization was realized via STRING, Cytoscape 3.7.2, Evenn, DAVID and Hiplot. Finally, molecular docking Vina and PyMOL software were performed to further explore the possibility of drug-target interactions using PubChem compounds, protein data bank (PDB) database, Autodocktools and Autodock.

Results

Three TCM preparations could target the same 13 potential therapeutic targets in GGNs. From network pharmacology, 14 signaling pathways, the functions of the significant targets, an effective ingredient in TCM prescriptions and its functions were obtained.

Conclusions

Chinese herbal formulas containing quercetin could be a potential treatment for GGNs, targeting C-reactive protein (CRP), tumor necrosis factor (TNF), interferon gamma (IFN-γ), intercellular adhesion molecule 1 (ICAM-1), and vascular endothelial growth factor A (VEGFA) through the hypoxia-inducible factor 1 (HIF-1) pathway, mitogen-activated protein kinase (MAPK) signaling pathway, and leukocyte transendothelial migration.

Revealing the anti-inflammatory ingredients in wine-processed Radix et Rhizoma Rhei using immobilized cysteinyl leukotriene receptor type 1 as the stationary phase

Despite the tremendous progress of wine-processed Radix et Rhizoma Rhei (Jiudahuang, JDH) in removing toxic heat from the blood in the upper portion of the body for hundreds of years, the deep understanding of its functional material basis of the anti-inflammatory ingredients remains unclear due to the lack of high specific and efficient methods. Herein, taking Cysteinyl leukotriene receptor type 1(CysLT1R) as the target protein, we established a chromatographic method based on the immobilized CysLT1R using haloalkane dehalogenases (Halo) at the C-terminus of the receptor in one step. After careful characterization by X-ray photoelectronic spectroscopy, immune-fluorometric analysis, and chromatographic investigations, the immobilized receptor was used to screen the anti-inflammatory ingredients in JDH. Aloe-emodin, rhein, emodin, chrysophanol, and physcion were identified as the main anthraquinone exerting anti-inflammatory effects in the drug. The association constants for the five compounds to bind with the receptor were calculated as (0.30 ± 0.06)× 105, (0.35 ± 0.03)× 105, (0.46 ± 0.05)× 105, (1.05 ± 0.14)× 105, and (1.66 ± 0.17)× 105 M-1 by injection amount-dependent method. Meanwhile, hydrogen bonds were identified as the main driving force for the five compounds to bind with CysLT1R by molecular docking. Based on these results, we believe that the immobilized receptor chromatography preserves historic significance in revealing the functional material basis of the complex matrices.

A critical assessment of Traditional Chinese Medicine databases as a source for drug discovery

Traditional Chinese Medicine (TCM) has been used for thousands of years to treat human diseases. Recently, many databases have been devoted to studying TCM pharmacology. Most of these databases include information about the active ingredients of TCM herbs and their disease indications. These databases enable researchers to interrogate the mechanisms of action of TCM systematically. However, there is a need for comparative studies of these databases, as they are derived from various resources with different data processing methods. In this review, we provide a comprehensive analysis of the existing TCM databases. We found that the information complements each other by comparing herbs, ingredients, and herb-ingredient pairs in these databases. Therefore, data harmonization is vital to use all the available information fully. Moreover, different TCM databases may contain various annotation types for herbs or ingredients, notably for the chemical structure of ingredients, making it challenging to integrate data from them. We also highlight the latest TCM databases on symptoms or gene expressions, suggesting that using multi-omics data and advanced bioinformatics approaches may provide new insights for drug discovery in TCM. In summary, such a comparative study would help improve the understanding of data complexity that may ultimately motivate more efficient and more standardized strategies towards the digitalization of TCM.

AI-assisted literature exploration of innovative Chinese medicine formulas

Objective: Our study provides an innovative approach to exploring herbal formulas that contribute to the promotion of sustainability and biodiversity conservation. We employ data mining, integrating keyword extraction, association rules, and LSTM-based generative models to analyze classical Traditional Chinese Medicine (TCM) texts. We systematically decode classical Chinese medical literature, conduct statistical analyses, and link these historical texts with modern pharmacogenomic references to explore potential alternatives. Methods: We present a novel iterative keyword extraction approach for discerning diverse herbs in historical TCM texts from the Pu-Ji Fang copies. Utilizing association rules, we uncover previously unexplored herb pairs. To bridge classical TCM herbal pairs with modern genetic relationships, we conduct gene-herb searches in PubMed and statistically validate this genetic literature as supporting evidence. We have expanded on the present work by developing a generative language model for suggesting innovative TCM formulations based on textual herb combinations. Results: We collected associations with 7,664 PubMed cross-search entries for gene-herb and 934 for Shenqifuzheng Injection as a positive control. We analyzed 16,384 keyword combinations from Pu-Ji Fang's 426 volumes, employing statistical methods to probe gene-herb associations, focusing on examining differences among the target genes and Pu-Ji Fang herbs. Conclusion: Analyzing Pu-Ji Fang reveals a historical focus on flavor over medicinal aspects in TCM. We extend our work on developing a generative model from classical textual keywords to rapidly produces novel herbal compositions or TCM formulations. This integrated approach enhances our comprehension of TCM by merging ancient text analysis, modern genetic research, and generative modeling.

Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review

Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

Buyang Huanwu Decoction alleviates blood stasis, platelet activation, and inflammation and regulates the HMGB1/NF-κB pathway in rats with pulmonary fibrosis

ETHNOPHARMACOLOGICAL RELEVANCE

Qi deficiency and blood stasis are identified to be pathological factors of pulmonary fibrosis (PF) in traditional Chinese medicine (TCM) theory. Buyang Huanwu Decoction (BYHWD) is a traditional Chinese prescription ameliorating Qi deficiency and blood stasis.

AIM OF THE STUDY

The objective of this study was to investigate the anti-fibrosis effect of BYHWD and the potential molecular mechanism in rats.

MATERIALS AND METHODS

Bleomycin was used to construct PF rat models. 27 PF rats were randomly divided into three groups based on treatments: model group (saline solution, n = 9), low-dose BYHWD group (3.5 g/kg, n = 9), and high-dose BYHWD group (14.0 g/kg, n = 9). Moreover, 9 normal rats were used as the blank group. The blood viscosity, coagulation indexes (APTT, TT, PT, and FIB), platelet-related parameters (PLT, PDW, MPV, PCT, and PLCR), platelet microparticles (PMPs), and inflammatory factors (IL-2, IL-10, IL-1β, IL-6, IL-8, IL-17, IFN-γ, TNF-α, PAC-1, HMGB1, NF-κB, and TF) were determined. The lung tissue samples of rats were observed after hematoxylin-eosin (HE) staining. The full component analysis of the BYHWD extract was performed using the ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. The signaling pathway included into the study was selected on the basis of bioinformatics analysis and the results of the phytochemical analysis. The expression levels of genes and proteins involved in the selected signaling pathway were detected.

RESULTS

Compared to the blank group, the whole blood viscosity, PLR, PDW, MPV, PCT, PLCR, PMPs, and the levels of IL-1β, IL-6, IL-8, IL-17, TNF-α, PAC-1, HMGB1, NF-κB, and TF were increased, while the levels of IL-2 and IL-10 were decreased in the model group. Both low-dose BYHWD and high-dose BYHWD reversed these PF-induced effects in spite of the fact that low-dose BYHWD had no significant effect on the level of NF-κB. In addition, BYHWD ameliorated PF-induced inflammation in the rat lung tissue. The phytochemical analysis of the BYHWD extract combined with the bioinformatics analysis suggested that the therapeutical effect of BYHWD on PF was related to the HMGB1/NF-κB pathway, which consisted of NF-κB, IKBKB, ICAM1, VCAM1, HMGB1, and TLR4. Both RT-qPCR and western blot analyses showed that PF induced increases in the expression levels of NF-κB, ICAM1, VCAM1, HMGB1, and TLR4, but a decrease in the expression level of IKBKB. Moreover, both low-dose BYHWD and high-dose BYHWD exerted the opposite effects, and recovered the expression levels of NF-κB, ICAM1, VCAM1, HMGB1, TLR4, and IKBKB, despite the fact that low-dose BYHWD had no effects on the mRNA expression levels of NF-κB or TLR4.

CONCLUSIONS

In summary, BYHWD alleviated PF-induced blood stasis, platelet activation, and inflammation in the rats. Our study suggested BYHWD had a therapeutic effect on PF and was a good alternative for the complementary therapy of PF, and the potential molecular mechanism was modulation of HMGB1/NF-κB signaling pathway, and it needs further study.

Quality Consistency Evaluation of Traditional Chinese Medicines: Current Status and Future Perspectives

Quality consistency evaluation of traditional Chinese medicines (TCMs) is a crucial factor that determines the safe and effective application in clinical settings. However, TCMs exhibit diverse, heterogeneous, complex, and flexible chemical compositions, as well as variability in preparation processes. These characteristics pose greater challenges in researching the consistency of TCMs compared to chemically synthesized and biological drugs. Therefore, it is paramount to develop effective strategies for evaluating the quality consistency of TCMs. From the starting point of quality properties, this review explores the strategy used to evaluate quality consistency in terms of chemistry-based strategy (chemical consistency) and the biology-based strategy (bioequivalence). Among them, the chemistry-based strategy is the mainstream, and biology-based strategy complements the chemistry-based strategy each other. Furthermore, the emerging chemistry-biology strategies (overall evaluation) is discussed, including individually combining strategy and integration strategy. Finally, this review provides insights into the challenges and future perspectives in this field. By highlighting current status and trends in TCMs quality consistency, this review aims to contribute to establishment of generally applicable chemistry-biology integrated evaluation strategy for TCMs. This will facilitate the advancement toward a higher stage of overall quality evaluation.

Main active components of Ilex rotunda Thunb. protect against ulcerative colitis by restoring the intestinal mucosal barrier and modulating the cytokine-cytokine interaction pathways

ETHNOPHARMACOLOGICAL RELEVANCE

Ilex rotunda Thunb. (IR) is widely used for gastrointestinal diseases by Yao physician, and it has a better clinical curative effect on ulcerative colitis (UC). However, the main active components and mechanism of IR in the treatment of UC remain to be clarified.

AIM OF THE STUDY

To investigate the main active components and mechanism of IR in the treatment of UC.

MATERIALS AND METHODS

Ten biological active components of IR were quantified by UPLC-MS/MS. In vitro, Caco2 cell monolayers were stimulated by lipopolysaccharide, and were treated with 10 biologically active components individually to investigate the protective role of the components of IR in mucosal barrier damage. In vivo, a mouse model of UC was induced by dextran sulfate sodium and administered with the candidate active components of IR. On day 8, the serum and colon tissue were collected for histological and molecular analysis to investigate the main active components and mechanism of IR.

RESULTS

Ziyuglycoside I, ziyuglycoside II, syringin, and pedunculoside in IR reduced phenol red transmission of the monolayer, and inhibited the protein expression of oncostatin M and oncostatin M receptor in Caco2 cells. Notably, ziyuglycoside II and syringin decreased the transepithelial electrical resistance of the monolayer, and promoted the protein expression of Occludin, Claudin-1 and zonula occludens-1 (ZO-1) in Caco2 cells. In vivo, ziyuglycoside II and syringin improved the symptoms of UC mice, including body weight, disease activity score, shortening of colon length, damaging of acidic mucus layer, histopathological changes, and protein expression of Occludin, Claudin-1, and ZO-1. Pedunculoside reduced the neutrophils and inflammatory response in the UC mice. Moreover, when the combination of ziyuglycoside II, syringin and pedunculoside was used for the treatment of UC, syringin and pedunculoside enhanced the therapeutic effect of ziyuglycoside II. Finally, RNA sequencing and RT-qPCR analysis revealed that ziyuglycoside II + syringin + pedunculoside and IR coregulated up to 42.7% of genes, and mainly reduced the overexpression of C-X-C motif ligand 1(CXCL1), oncostatin M receptor (OSMR), interleukin 1 receptor type I (IL1R1), tumor necrosis factor receptor superfamily member 9 (TNFRSF9), C-X-C motif chemokine 13 (CXCL13), oncostatin M (OSM), and interleukin 6 (IL-6) in the cytokine-cytokine interaction pathways.

CONCLUSIONS

The combination of ziyuglycoside II, syringin, and pedunculoside protects against UC by modulating the intestinal mucosal barrier and inhibiting the cytokine-cytokine interaction pathways, and the effect is relatively equivalent to that of the water extract of Ilex rotunda Thunb.

Network pharmacology, molecular docking and experimental verification of the mechanism of huangqi-jixuecao herb pair in treatment of peritoneal fibrosis

ETHNOPHARMACOLOGICAL RELEVANCE

The Huangqi-Jixuecao herb pair (HQJXCHP) is a traditional herbal formula composed of two widely applied TCM prescriptions, Huangqi (Astragalus membranaceus (Fisch.) Bunge) and Jixuecao (Centella asiatica (L.) Urb.), used for hundreds of years to replenish qi and clear away heat. However, the therapeutic effects of HQJXCHP against peritoneal fibrosis (PF) and potential targets are currently unclear.

AIMS OF THE STUDY

The main objective of this study was preliminary prediction and validation of the effects and molecular mechanisms of action of HQJXCHP against PF based on network pharmacology analysis and experimental verification.

MATERIALS AND METHODS

The ingredients of HQJXCHP were analyzed via HPLC-Q-TOF/MS. Bioactive compounds of HQJXCHP used for network pharmacology analysis were obtained from the TCMSP database. HQJXCHP-related therapeutic targets in PF were obtained from the GeneCards, OMIM, Therapeutic Targets and PharmGkb databases. Therapeutic target-related signaling pathways were predicted via GO and KEGG pathway enrichment analyses. The targets of HQJXCHO were further validated in a PDS-induced PF mouse model in vivo and PMCs MMT model in vitro.

RESULTS

A total of 23 bioactive compounds of HQJXCHP related 188 target genes were retrieved. The HQJXCHP compound-target and PF-related target networks identified 131 common target genes. Subsequent protein-protein interaction (PPI) network analysis results disclosed Akt1, TP53, TNF, VEGFA and CASP3 as the top five key targets of HQJXCHP. Further molecular docking data revealed strong affinity of the two key compounds of HQJXCHP, quercetin and kaempferol, for these key targets. GO and KEGG pathway enrichment analyses further showed that PI3K/Akt, IL-17, TNF and TLR pathways contribute to the therapeutic effects of HQJXCHP on PF. An in vivo PDS-induced PF mouse model and in vitro PMCs mesothelial-to-mesenchymal transition (MMT) model with or without HQJXCHP intervention were used to confirm the effects and mechanisms of action of HQJXCHP. Western blot and qRT-PCR results showed that HQ, JXC and HQJXCHP reduced PDS-induced inflammatory cell aggregation and peritoneal thickening through suppressing the MMT process, among which HQJXCHP exerted the greatest therapeutic effect. Moreover, HQJXCHP inhibited activation of the PI3K/Akt, IL-17, TNF and TLR signaling pathways induced by PDS.

CONCLUSIONS

This is the first study to employ network pharmacology and molecular docking analyses to predict the targets of HQJXCHP with therapeutic effects on PDS-related PF. Data from in vivo and in vitro validation experiments collectively showed that HQJXCHP delays the PF process through inhibiting PI3K/Akt, IL-17, TNF and TLR signaling pathways. Overall, our findings highlight the successful application of network pharmacology theory to provide a scientific basis for clinical utility of HQJXCHP against PF.

Puerarin-Tanshinone IIA Suppresses atherosclerosis inflammatory plaque via targeting succinate/HIF-1α/IL-1β axis

ETHNOPHARMACOLOGICAL RELEVANCE

Inflammatory injury is an important pathological factor for the formation of atherosclerotic plaque. It is well known that Puerarin and Tanshinone IIA (Pue-Tan) can significantly reduce interleukin-1β (IL-1β) levels and delay the atherosclerosis (AS) process clinically in China. Previous evidence has shown that the Succinate/HIF-1α/IL-1β inflammatory signaling axis (Succinate axis) promotes the progression of atherosclerotic inflammatory plaques. It is not clear whether Pue-Tan inhibits inflammatory plaques by reducing the level of IL-1β through the succinate signaling axis.

AIM OF STUDY

Find out the interaction between Pue-Tan targets and the succinate axis by means of network pharmacology and bioinformatics analysis and to further confirm whether Pue-Tan can inhibit vascular inflammation and delay the formation of atherosclerotic inflammatory plaques by targeting the succinate signaling axis.

MATERIALS AND METHODS

Firstly, animal experiments were conducted to verify the changing relationship between Succinate and IL-1β under Pue-Tan intervention. Secondly, network pharmacology approach was employed to uncover the specific targets of Pue-Tan in the intervention of AS from multiple levels of components, proteins, and pathways, and at the same time, the target must be a key factor of the succinate signaling axis. Autodock vina1.5.6 was applied to molecular docking for Pue-Tan and target protein. Subsequently, cells experiment and animal experiment were performed to verify Pue-Tan inhibiting the inflammatory progression of atherosclerosis by targeting succinate signaling axis.

RESULTS

Firstly, we first found that the reduction of IL-1β was positively correlated with succinate in the serum of Pue-Tan-treated mice. Secondly, network pharmacology compared with molecular docking showed that hypoxia-induced factor-1α (HIF-1α) was the key target of Pue-Tan and the key node of succinate singling axis. Finally, in vitro study, Pue-Tan significantly reduced the factors of succinate axis just as HIF-1α siRNA; in vivo study, we confirmed a decreased expression of succinate axis and ICAM-1 in the aorta of ApoE-/- mice under Pue-Tan intervention, which was consistent with the in vitro results.

CONCLUSION

This study confirmed that Pue-Tan blocked the succinate axis by targeting HIF-1α to prevent the formation of atherosclerotic inflammatory plaques and delay the pathological process of AS. Network Pharmacology, Bioinformatics of Molecular Docking, and Molecular Biology Validation can be used as a effective way to discover and verify the pharmacological mechanism of TCM.

Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine

Network pharmacology (NP) provides a new methodological perspective for understanding traditional medicine from a holistic perspective, giving rise to frontiers such as traditional Chinese medicine network pharmacology (TCM-NP). With the development of artificial intelligence (AI) technology, it is key for NP to develop network-based AI methods to reveal the treatment mechanism of complex diseases from massive omics data. In this review, focusing on the TCM-NP, we summarize involved AI methods into three categories: network relationship mining, network target positioning and network target navigating, and present the typical application of TCM-NP in uncovering biological basis and clinical value of Cold/Hot syndromes. Collectively, our review provides researchers with an innovative overview of the methodological progress of NP and its application in TCM from the AI perspective.

The combination of Ephedrae herba and coixol from Coicis semen attenuate adiposity via glucocorticoid receptor regulation

The enhanced therapeutic effects and mechanisms of certain herbal combination in various herbal prescriptions are mostly unclear. A combination of two herbs, namely Ephedrae herba (EH) and Coicis semen (CS), has been commonly prescribed for obesity. In our previous work, the combination of EH and CS was studied using network pharmacological approach to predict its pharmacological targets and in vitro experiments to evaluate its efficacy on obesity. Although we demonstrated enhanced anti-adiposity effects of the combination on matured adipocytes, the molecular mechanisms and contributing compounds underlying the effects of EH-CS combination on adiposity or adipogenesis were not fully elucidated. The current study adopted integrated bioinformatics analysis to precisely validate potential targets of EH-CS by screening differentially expressed genes (DEGs) of morbid obesity patients from NCBI gene expression omnibus (GEO). Based on the functional cluster analysis of down-regulated DEGs, the anti-adipogenesis mechanism of EH-CS combination was speculated with KEGG enrichment analysis. Furthermore, we investigated the combinational effects of EH and coixol, or stigmasterol, the two compounds in CS which were expected to have main beneficial effects in metabolic diseases. Moreover, distinct effect of the combination on transcriptional activity of glucocorticoid receptor (GR) was investigated using electrophoretic mobility shift assay (EMSA). The EH-CS combination was predicted to modulate down-regulated genes which are involved in KEGG pathways crucial to metabolic disease in morbidly obese individuals. The combination of EH with CS compounds significantly increased the phosphorylation of acetyl-coA carboxylase (ACC), AMP-activated protein kinase (AMPK), and protein kinase B (AKT) in 3T3-L1 cells and decreased intracellular lipid accumulation. The two CS compounds significantly increased the anti-adipogenesis/lipogenesis effects of EH by inhibiting the gene expression levels. Finally, the combination of EH and coixol inhibited dexamethasone-induced GR translocation to the nucleus and transcriptional binding activity in adipocytes. The combination of EH and CS could be considered a therapeutic strategy for treating metabolic diseases, including obesity.

Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb's targets to a symptom module is predictive of the herb's effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

Identification of the susceptible genes and mechanism underlying the comorbid presence of coronary artery disease and rheumatoid arthritis: a network modularization analysis

OBJECTIVE

The comorbidities of coronary artery disease (CAD) and rheumatoid arthritis (RA) are mutual risk factors, which lead to higher mortality, but the biological mechanisms connecting the two remain unclear. Here, we aimed to identify the risk genes for the comorbid presence of these two complex diseases using a network modularization approach, to offer insights into clinical therapy and drug development for these diseases.

METHOD

The expression profile data of patients CAD with and without RA were obtained from the GEO database (GSE110008). Based on the differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA) was used to construct a gene network, detect co-expression modules, and explore their relation to clinical traits. The Zsummary index, gene significance (GS), and module membership (MM) were utilized to screen the important differentiated modules and hub genes. The GO and KEGG pathway enrichment analysis were applied to analyze potential mechanisms.

RESULT

Based on the 278 DEGs obtained, 41 modules were identified, of which 17 and 24 modules were positively and negatively correlated with the comorbid occurrence of CAD and RA (CAD&RA), respectively. Thirteen modules with Zsummary < 2 were found to be the underlying modules, which may be related to CAD&RA. With GS ≥ 0.5 and MM ≥ 0.8, 49 hub genes were identified, such as ADO, ABCA11P, POT1, ZNF141, GPATCH8, ATF6 and MIA3, etc. The area under the curve values of the representative seven hub genes under the three models (LR, KNN, SVM) were greater than 0.88. Enrichment analysis revealed that the biological functions of the targeted modules were mainly involved in cAMP-dependent protein kinase activity, demethylase activity, regulation of calcium ion import, positive regulation of tyrosine, phosphorylation of STAT protein, and tissue migration, etc. CONCLUSION: Thirteen characteristic modules and 49 susceptibility hub genes were identified, and their corresponding molecular functions may reflect the underlying mechanism of CAD&RA, hence providing insights into the development of clinical therapies against these diseases.

Integrative medicine using East Asian herbal medicine for inflammatory pain in patients with rheumatoid arthritis: A protocol for systematic review and meta-analysis integrated with multiple data mining for core candidate discovery

BACKGROUND

Rheumatoid arthritis is a chronic inflammatory autoimmune disease characterized by a wide range of clinical symptoms affecting various bodily functions, including skeletal, vascular, metabolic, and cognitive functions. This review aimed to evaluate the efficacy and safety of integrative medicine (East Asian herbal medicine combined with conventional medicine) used for the treatment of inflammatory pain in rheumatoid arthritis and to identify key candidate drugs based on the data.

METHODS

A comprehensive literature search will be conducted in 4 core databases (PubMed, Excerpta Medica database, Cochrane Library, and Cumulative Index to Nursing & Allied Health Literature) 4 Korean databases (Oriental Medicine Advanced Searching Integrated System, Korean Studies Information Service System, Research Information Service System, and Korea Citation Index), 2 Chinese databases (Chinese National Knowledge Infrastructure Database and Wanfang data), and 1 Japanese database (Citation Information by National Institute of Informatics) for randomized controlled trials from December 13, 2022. Statistical analysis will be performed using R version 4.1.2 and R Studio program. The American College of Rheumatology 20/50/70 score and rate of adverse events will be the primary outcomes. All outcomes will be analyzed using a random-effects model to produce more statistically conservative results. Sensitivity, meta-regression, and subgroup analyses will be used to identify the sources of any heterogeneity in the study. The revised tool for assessing the risk of bias in randomized trials, version 2.0, will be used to evaluate methodological quality. The overall quality of evidence will be assessed according to the Grading of Recommendations Assessment, Development, and Evaluation Pro Framework.

ETHICS AND DISSEMINATION

There are no ethical issues, as no primary data will be collected directly from the participants. The results of this review will be reported in a peer-reviewed scientific journal.

TRIAL REGISTRATION

PROSPERO registration number: CRD42023412385.

Complex components of Shengmai formula interact with organic cation transporter 2 (OCT2) in MDCK cells

ETHNOPHARMACOLOGICAL RELEVANCE

Shengmai formula (SMF) is a well-known Chinese herbal compound preparation, which is utilized extensively for the treatment of myocardial ischemia, arrhythmia and other life-threatening conditions. Our previous researches have shown that some of the active ingredients in SMF can interact with organic anion transport polypeptide 1B1 (OATP1B1), breast cancer resistance protein (BCRP) and organic anion transporter 1 (OAT1), etc. Organic cation transporter 2 (OCT2) is a highly expressed uptake transporter in the kidney, and its interaction with the major active components in SMF remains unclear.

AIM OF THE STUDY

We purposed to explore OCT2-mediated interactions and compatibility mechanisms of the main active compounds in SMF.

MATERIALS AND METHODS

Fifteen active ingredients of SMF, including ginsenoside Rb1, Rd, Re, Rg1, Rf, Ro and Rc, methylophiopogonanone A and B, ophiopogonin D and D', schizandrin A and B, schizandrol A and B, were selected to investigate OCT2-mediated interactions in Madin-Darby cacine kidney (MDCK) cells stably expressing OCT2.

RESULTS

Among the above 15 main active components, only ginsenosides Rd, Re and schizandrin B could significantly inhibit the uptake of 4-(4-(dimethylamino)styryl)-N-methyl pyridiniumiodide (ASP⁺), a classical substrate of OCT2. Ginsenoside Rb1 and methylophiopogonanone A can be transported by MDCK-OCT2 cells, and their uptake was significantly reduced when OCT2 inhibitor decynium-22 was added. Ginsenoside Rd could remarkably reduce the uptake of methylophiopogonanone A and ginsenoside Rb1 by OCT2, ginsenoside Re only decreased the uptake of ginsenoside Rb1, while schizandrin B had no effect on the uptake of both.

CONCLUSIONS

OCT2 mediates the interaction of the major active components in SMF. Ginsenosides Rd, Re and schizandrin B are the potential inhibitors of OCT2, while ginsenosides Rb1 and methylophiopogonanone A are the potential substrates of OCT2. There is an OCT2-mediated compatibility mechanism among these active ingredients of SMF.

Network pharmacology approaches for research of Traditional Chinese Medicines

Pharmacodynamics material basis and effective mechanisms are the two main issues to decipher the mechnisms of action of Traditional Chinese medicines (TCMs) for the treatment of diseases. TCMs, in "multi-component, multi-target, multi-pathway" paradigm, show satisfactory clinical results in complex diseases. New ideas and methods are urgently needed to explain the complex interactions between TCMs and diseases. Network pharmacology (NP) provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of NP has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. The current organ-centricity of medicine and the "one disease-one target-one drug" dogma obstruct the understanding of complex diseases and the development of effective drugs. Therefore, more attentions should be paid to shift from "phenotype and symptom" to "endotype and cause" in understanding and redefining current diseases. In the past two decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), NP has been improved and deeply implemented, and presented its great value and potential as the next drug-discovery paradigm. NP is developed to cure causal mechanisms instead of treating symptoms. This review briefly summarizes the recent research progress on NP application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.

Optimizing Genomic Control in Hit Network-Target Set Model Associations with Lung Adenocarcinoma

Background: Hit network-target sets (HNSs), compiled sets of different network nodes of the same type, are available and play a significant role in cancer development but are notoriously more difficult to select than a single target. This is due to a combination of challenges attributed to the differential of node interactions, node heterogeneity, and the limitations of node-hit information. Methods: In this study, we constructed a lung adenocarcinoma regulatory network using TCGA data and obtained different HNSs of driver nodes (DNs), core modules (CMs) and core nodes (CNs) through three kinds of methods. Then, the optimized HNS (OHNS) was obtained by integrating CMs, CNs and DNs, and the performance of different HNSs was evaluated according to network structure importance, control capability, and clinical value. Results: We found that the OHNS has two main advantages, the central location of the network and the ability to control the network, and it plays an important role in the disease network through its multifaceted capabilities. Three unique pathways were discovered in the OHNS, which is consistent with previous experiments. Additionally, 13 genes were predicted to play roles in risk prognosis, disease drivers, and cell perturbation effects of lung adenocarcinoma, of which 12 may be candidates for new drugs and biomarkers of lung adenocarcinoma. Conclusion: This study can help us understand and control a network more effectively to determine the development trend of a disease, design effective multitarget drugs, and guide the therapeutic community to optimize appropriate strategies according to different research aims in cancer treatment.

Network pharmacology predicts combinational effect of novel herbal pair consist of Ephedrae herba and Coicis semen on adipogenesis in 3T3-L1 cells

BACKGROUND

Herbal combinations are regarded as basic strategy in oriental medicine with various purposes. Ephedrae herba (EH) and Coicis semen (CS) are two herbal medicines used to treat obesity in many herbal prescriptions, yet the effect and significance of this herbal pair have not been evaluated.

PURPOSE

This study is to elucidate the effect of a novel herbal pair, EH-CS, on obesity and identify the key synergistic mechanism underlying it.

METHODS

We investigated the network of herbs comprising the anti-obesity herbal prescriptions. Using the tools of network pharmacology, we investigated the compound-target interactions of EH and CS in combination to predict their effects in combination. Five EH-CS samples with different EH to CS ratios were prepared to investigate their efficacies in adipocytes.

RESULTS

1-mode network analysis of herbs in prescriptions based on literature review revealed the importance of EH-CS in anti-obesity prescriptions. The herbal combination comprised of equivalent weights (1:1) of EH and CS most potently reduced mature adipocyte adiposity, although several markers of adipogenesis and lipid synthesis were more suppressed by pure EH. PTGS2 (COX-2 gene) expression, a common target of EH and CS as deduced by compound-target network analysis, was affected by EH-CS extract treatments. However, EH at high concentration (25 μg/ml) notably increased PTGS2 expression without adversely affecting cell viability. However, EH-CS combination of the same concentration markedly decreased PTGS2 gene expression.

CONCLUSION

These results show that the compounds in CS and EH act in concert to enhance the pharmacological effect of EH, but control unexpected effects of EH treatment.

Identify Biomarkers and Design Effective Multi-Target Drugs in Ovarian Cancer: Hit Network-Target Sets Model Optimizing

Epithelial ovarian cancer (EOC) is highly aggressive with poor patient outcomes, and a deeper understanding of ovarian cancer tumorigenesis could help guide future treatment development. We proposed an optimized hit network-target sets model to systematically characterize the underlying pathological mechanisms and intra-tumoral heterogeneity in human ovarian cancer. Using TCGA data, we constructed an epithelial ovarian cancer regulatory network in this study. We use three distinct methods to produce different HNSs for identification of the driver genes/nodes, core modules, and core genes/nodes. Following the creation of the optimized HNS (OHNS) by the integration of DN (driver nodes), CM (core module), and CN (core nodes), the effectiveness of various HNSs was assessed based on the significance of the network topology, control potential, and clinical value. Immunohistochemical (IHC), qRT-PCR, and Western blotting were adopted to measure the expression of hub genes and proteins involved in epithelial ovarian cancer (EOC). We discovered that the OHNS has two key advantages: the network's central location and controllability. It also plays a significant role in the illness network due to its wide range of capabilities. The OHNS and clinical samples revealed the endometrial cancer signaling, and the PI3K/AKT, NER, and BMP pathways. MUC16, FOXA1, FBXL2, ARID1A, COX15, COX17, SCO1, SCO2, NDUFA4L2, NDUFA, and PTEN hub genes were predicted and may serve as potential candidates for new treatments and biomarkers for EOC. This research can aid in better capturing the disease progression, the creation of potent multi-target medications, and the direction of the therapeutic community in the optimization of effective treatment regimens by various research objectives in cancer treatment.

Analyzing network pharmacology and molecular docking to clarify Duhuo Jisheng decoction potential mechanism of osteoarthritis mitigation

As a classic remedy for treating Osteoarthritis (OA), Duhuo Jisheng decoction has successfully treated countless patients. Nevertheless, its specific mechanism is unknown. This study explored the active constituents of Duhuo Jisheng decoction and the potential molecular mechanisms for treating OA using a Network Pharmacology approaches. Screening active components and corresponding targets of Duhuo parasite decoction by traditional Chinese medicine systems pharmacology database and analysis platform database. Combining the following databases yielded OA disease targets: GeneCards, DrugBank, PharmGkb, Online Mendelian Inheritance in Man, and therapeutic target database. The interaction analysis of the herb-active ingredient-core target network and protein-protein interaction protein network was constructed by STRING platform and Cytoscape software. Gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were carried out. PyMOL and other software were used to verify the molecular docking between the essential active components and the core target. 262 active ingredients were screened, and their main components were quercetin, kaempferol, wogonin, baicalein, and beta-carotene. 108 intersection targets of disease and drug were identified, and their main components were RELA, FOS, STAT3, MAPK14, MAPK1, JUN, and ESR1. Gene ontology analysis showed that the key targets were mainly involved in biological processes such as response to lipopolysaccharide, response to xenobiotic stimulus, and response to nutrient levels. The results of Kyoto Encyclopedia of Genes and Genomes analysis show that the signal pathways include the AGE - RAGE signaling pathway, IL - 17 signaling pathway, TNF signaling pathway, and Toll - like receptor signaling pathway. Molecular docking showed that the main active components of Duhuo parasitic decoction had a good bonding activity with the key targets in treating OA. Duhuo Jisheng decoction can reduce the immune-inflammatory reaction, inhibit apoptosis of chondrocytes, strengthen proliferation and repair of chondrocytes and reduce the inflammatory response in a multi-component-multi-target-multi-pathway way to play a role in the treatment of OA.

Yishen Xiezhuo formula ameliorates the development of cisplatin-induced acute kidney injury by attenuating renal tubular epithelial cell senescence

Background

Although cisplatin (DDP) is an important clinical anti-tumor drug, its use is limited by its nephrotoxicity. How to avoid the renal injury incurred by platinum drugs and improve the clinical efficiency of platinum drugs use has become an urgent clinical problem. Previous studies have verified that Chinese medicine has definite effects on acute kidney injury (AKI). Yishen Xiezhuo formula (YSXZ) is a traditional Chinese medicine (TCM) compound which is an effective clinical drug for AKI, but its mechanism remains unclear.

Methods

In our research, an AKI model was induced by DDP in human renal tubular epithelial cell (HKC) lines in the in vitro study. The mechanism of the YSXZ on cell senescence was analyzed by Cell Counting Kit-8 (CCK-8), senescence-associated β-galactosidase (SA-β-Gal) staining, western blot, flow cytometry, and enzyme-linked immunosorbent assay (ELISA). Network pharmacology was used to analyze the role of YSXZ against AKI.

Results

Compared with the control group, the cells in the DDP intervention group were significantly senescent. Compared with DDP group, YSXZ decreased the number of SA-β-Gal-positive senescence cells, down regulated the expression of senescence-related proteins, reduced the release of senescence-related secreted phenotypic factors, and reversed the phenomenon of cell cycle S-phase arrest. Network pharmacology and experimental studies showed that the mitogen-activated protein kinase (MAPK) signaling pathway played a central role.

Conclusions

Our present results suggested that YSXZ ameliorated the development of DDP-induced AKI by attenuating renal tubular epithelial cell (RTEC) senescence via alleviating the activation of MAPK pathway.

Astragalus and its formulas as a therapeutic option for fibrotic diseases: Pharmacology and mechanisms

Fibrosis is the abnormal deposition of extracellular matrix, characterized by accumulation of collagen and other extracellular matrix components, which causes organ dysfunction and even death. Despite advances in understanding fibrosis pathology and clinical management, there is no treatment for fibrosis that can prevent or reverse it, existing treatment options may lead to diarrhea, nausea, bleeding, anorexia, and liver toxicity. Thus, effective drugs are needed for fibrotic diseases. Traditional Chinese medicine has played a vital role in fibrotic diseases, accumulating evidence has demonstrated that Astragalus (Astragalus mongholicus Bunge) can attenuate multiple fibrotic diseases, which include liver fibrosis, pulmonary fibrosis, peritoneal fibrosis, renal fibrosis, cardiac fibrosis, and so on, mechanisms may be related to inhibition of epithelial-mesenchymal transition (EMT), reactive oxygen species (ROS), transforming growth factor beta 1 (TGF-β1)/Smads, apoptosis, inflammation pathways. The purpose of this review was to summarize the pharmacology and mechanisms of Astragalus in treating fibrotic diseases, the data reviewed demonstrates that Astragalus is a promising anti-fibrotic drug, its main anti-fibrotic components are Calycosin, Astragaloside IV, Astragalus polysaccharides and formononetin. We also review formulas that contain Astragalus with anti-fibrotic effects, in which Astragalus and Salvia miltiorrhiza Bunge, Astragalus and Angelica sinensis (Oliv.) Diels are the most commonly used combinations. We propose that combining active components into new formulations may be a promising way to develop new drugs for fibrosis. Besides, we expect Astragalus to be accepted as a clinically effective method of treating fibrosis.

PINet 1.0: A pathway network-based evaluation of drug combinations for the management of specific diseases

Drug combinations can increase the therapeutic effect by reducing the level of toxicity and the occurrence of drug resistance. Therefore, several drug combinations are often used in the management of complex diseases. However, due to the exponential growth in drug development, it would be impractical to evaluate all combinations through experiments. In view of this, we developed Pathway Interaction Network (PINet) biological model to estimate the optimal drug combinations for various diseases. The random walk with restart (RWR) algorithm was used to capture the “disease state” and “drug state,” while PINet was used to evaluate the optimal drug combinations and the high-order drug combination¹. The model achieved a mean area under the curve of a receiver operating characteristic curve of 0.885. In addition, for some diseases, PINet predicted the optimal drug combination. For example, in the case of acute myeloid leukemia, PINet correctly predicted midostaurin and gemtuzumab as effective drug combinations, as demonstrated by the results of a Phase-I clinical trial. Moreover, PINet also correctly predicted the potential drug combinations for diseases that lacked a training dataset that could not be predicted using standard machine learning models.

The application of proteomics and metabolomics to reveal the molecular mechanism of Nutmeg-5 in ameliorating cardiac fibrosis following myocardial infarction

BACKGROUND

Nutmeg-5, an ancient and classic formula in traditional Mongolian medicine comprising five kinds of traditional Chinese medicine, is widely used in the treatment of myocardial infarction (MI, called heart "Heyi" disease in Mongolian medicine). Cardiac fibrosis plays a critical role in the development and progression of heart failure after MI. However, the material basis and pharmacological mechanisms of the effect of Nutmeg-5 on cardiac fibrosis after MI remain unclear.

OBJECTIVE

The aim of this study was to first explore the potential material basis and molecular mechanism of action of Nutmeg-5 in improving cardiac fibrosis after MI via a multiomics approach.

METHODS

The constituents in Nutmeg-5 were identified by ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). High-performance liquid chromatography (HPLC) and gas chromatography (GC)-based fingerprints of Nutmeg-5 were analysed, and characteristic peaks were identified by comparison to standard samples. A rat MI model was created by permanent ligation of the left anterior descending artery. The protective effect of Nutmeg-5 on cardiac fibrosis after MI was evaluated by tissue histology and measurement of the serum biomarkers of myocardial injury. Cardiac fibrosis levels were evaluated by Sirius red staining. Differentially expressed proteins in the myocardium and metabolites in the serum were explored by proteomic and untargeted metabolome analyses, respectively. Pearson correlation analysis was performed to explore the association between serum metabolites and myocardial proteins.

RESULTS

A total of 67 constituents were identified in Nutmeg-5 by UPLC-MS/MS. Sixteen components were identified in the fingerprint of Nutmeg-5 by comparison with a standard sample. Six lactones were isolated from Nutmeg-5 and quantified by HPLC and GC. MI was significantly alleviated in Nutmeg-5-treated rats compared to MI rats, as demonstrated by their decreased mortality, improved cardiac function, and attenuated cardiac fibrosis and myocardial injury. A total of 252 significant differential metabolites were identified in plasma between model and Nutmeg-5-treated rats by untargeted metabolome analysis. Among these, 36 critical metabolites were associated with Nutmeg-5 activity. Proteomic analysis identified 338 differentially expressed proteins in the rat myocardium between MI and Nutmeg-5-treated rats, including 204 upregulated and 134 downregulated proteins. Protein set enrichment analysis revealed that Nutmeg-5 treatment significantly inhibited the extracellular matrix (ECM)-receptor interaction pathway, which was activated in the myocardium of MI rats. A significant decrease in collagen and alpha smooth muscle actin expression levels was found in the myocardium of Nutmeg-5-treated rats compared to MI rats. These results illustrated that Nutmeg-5 had a significant protective effect on cardiac fibrosis after MI. A significant correlation was found between the ECM-receptor interaction pathway in the myocardium and critical metabolites in the serum. In addition, there were positive correlations between the levels of critical metabolites and the expression levels of transforming growth factor (TGF)-β1 and Smad2 in the rat myocardium.

CONCLUSIONS

Nutmeg-5 alleviated cardiac fibrosis after MI in rats by inhibiting the myocardial ECM-receptor interaction pathway and TGF-β1/Smad2 signalling, which was achieved by regulating plasma metabolites.

Exploring the Protective Effects and Mechanism of Huaji Jianpi Decoction against Nonalcoholic Fatty Liver Disease by Network Pharmacology and Experimental Validation

This paper was designed to predict the mechanisms of the active components of Huaji Jianpi Decoction (HJJPD) against nonalcoholic fatty liver disease (NAFLD) based on network pharmacology-combined animal experiments. The candidate compounds of HJJPD and its relative targets were obtained from TCMSP and PharmMapper web server, and the intersection genes for NAFLD were discerned using OMIM, GeneCards, and DisGeNET. Then, the target protein-protein interaction (PPI) and component-target-pathway networks were constructed. Moreover, gene function annotation (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to study the potential signaling pathways associated with HJJPD’s effect on NAFLD. Molecular docking simulation was preformed to validate the binding affinity between potential core components and key targets. Eventually, the candidate targets, the possible pathway, and the mechanism of HJJPD were predicted by the network pharmacology-based strategy, followed by experimental validation in the NAFLD mice model treated with HJJPD. A total of 55 candidate compounds and 36 corresponding genes were identified from HJJPD that are associated with activity against NAFLD, and then the network of them was constructed. Inflammatory response and lipid metabolism-related signaling pathways were identified as the critical signaling pathways mediating the therapeutic effect of the active bioactive ingredients on NAFLD. Compared with the model group, the liver wet weight, liver/body ratio, the levels of total cholesterol (TC), triglyceride (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and high-density lipoprotein (HDL) in serum in the HJJPD low-dose (17.52 g/kg·d), medium-dose (35.04 g/kg·d), and high-dose (70.07 g/kg·d) groups significantly decreased ( $P<0.05$ ). Light microscope observation shows that HJJPD could control the degree of lipid denaturation of the mouse liver tissue to a great extent. RT-qPCR results show that the mRNA expression levels of peroxisome proliferative activated receptor gamma (PPARG), tumor necrosis factor-α (TNF-α), antiserine/threonine protein kinase 1 (AKT1), and prostaglandin-endoperoxide synthase (PTGS2) in the liver tissues of the three HJJPD groups (17.52 g/kg·d, 35.04 g/kg·d, and 70.07 g/kg·d) were significantly lower than those in the model group ( $P<0.05$ ). HJJPD can exert its effect by inhibiting hepatic steatosis and related mRNA expression and decreasing the levels of other liver-related indexes. This study suggested that HJJPD exerted its effect on NAFLD by modulating multitargets with multicompounds through multipathways. It also demonstrated that the network pharmacology-based approach might provide insights for understanding the interrelationship between complex diseases and interventions of HJJPD.

Polypharmacology-based approach for screening TCM against coinfection of Mycoplasma gallisepticum and Escherichia coli

Natural products and their unique polypharmacology offer significant advantages for finding novel therapeutics particularly for the treatment of complex diseases. Meanwhile, Traditional Chinese Medicine exerts overall clinical benefits through a multi-component and multi-target approach. In this study, we used the previously established co-infection model of Mycoplasma gallisepticum and Escherichia coli as a representative of complex diseases. A new combination consisting of 6 herbs were obtained by using network pharmacology combined with transcriptomic analysis to reverse screen TCMs from the Chinese medicine database, containing Isatdis Radix, Forsythia Fructus, Ginkgo Folium, Mori Cortex, Licorice, and Radix Salviae. The results of therapeutic trials showed that the Chinese herbal compounds screened by the target network played a good therapeutic effect in the case of co-infection. In summary, these data suggested a new method to validate target combinations of natural products that can be used to optimize their multiple structure-activity relationships to obtain drug-like natural product derivatives.

Clinical evidence construction of East Asian herbal medicine for inflammatory pain in rheumatoid arthritis based on integrative data mining approach

BACKGROUND

Rheumatoid arthritis (RA) is a chronic inflammatory disease that leads to a significant social burden. East Asian herbal medicine (EAHM) has long been used to treat RA. Therefore, a systematic study of how EAHM treatments can be developed into new drugs using specific materials is needed.

METHODS

Eleven databases containing literature in English, Korean, Chinese, and Japanese were searched for randomized controlled trials comparing EAHM with conventional medicine (CM). A meta-analysis was performed on the variable data to assess their effects on inflammatory pain. Subsequently, we searched for core materials and combinations of core material-based data mining methods.

RESULTS

A total of 186 trials involving 19,716 patients with RA met the inclusion criteria. According to the meta-analysis, EAHM had a significantly superior effect on continuous pain intensity, tender joint count, and response rate. Patients treated with EAHM had a significantly reduced incidence of adverse events compared with those treated with CM. Based on additional analysis of the EAHM formula data included in this meta-analysis, 21 core materials and five core herbal combinations were identified.

CONCLUSION

EAHM remedies for RA have the adequate potential for use as candidate materials for treating inflammatory pain in RA. The candidate core herbs evaluated in this study act on multiple pathways and are expected to provide pain relief, sustained inflammation suppression, immune regulation, and prevention of joint destruction. It seems worthwhile to conduct follow-up research on drug development using the core materials derived from this review.

Deep learning and machine intelligence: New computational modeling techniques for discovery of the combination rules and pharmacodynamic characteristics of Traditional Chinese Medicine

It has been increasingly accepted that Multi-Ingredient-Based interventions provide advantages over single-target therapy for complex diseases. With the growing development of Traditional Chinese Medicine (TCM) and continually being refined of a holistic view, "multi-target" and "multi-pathway" integration characteristics of which are being accepted. However, its effector substances, efficacy targets, especially the combination rules and mechanisms remain unclear, and more powerful strategies to interpret the synergy are urgently needed. Artificial intelligence (AI) and computer vision lead to a rapidly expanding in many fields, including diagnosis and treatment of TCM. AI technology significantly improves the reliability and accuracy of diagnostics, target screening, and new drug research. While all AI techniques are capable of matching models to biological big data, the specific methods are complex and varied. Retrieves literature by the keywords such as "artificial intelligence", "machine learning", "deep learning", "traditional Chinese medicine" and "Chinese medicine". Search the application of computer algorithms of TCM between 2000 and 2021 in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Elsevier and Springer. This review concentrates on the application of computational in herb quality evaluation, drug target discovery, optimized compatibility and medical diagnoses of TCM. We describe the characteristics of biological data for which different AI techniques are applicable, and discuss some of the best data mining methods and the problems faced by deep learning and machine learning methods applied to Chinese medicine.

Integrative network pharmacology and experimental verification to reveal the anti-inflammatory mechanism of ginsenoside Rh4

Inflammation is an innate immune response to infection, and it is the main factor causing bodily injury and other complications in the pathological process. Ginsenoside Rh4 (G-Rh4), a minor ginsenoside of Panax ginseng C. A. Meyer and Panax notoginseng, has excellent pharmacological properties. However, many of its major pharmacological mechanisms, including anti-inflammatory actions, remain unrevealed. In this study, network pharmacology and an experimental approach were employed to elucidate the drug target and pathways of G-Rh4 in treating inflammation. The potential targets of G-Rh4 were selected from the multi-source databases, and 58 overlapping gene symbols related to G-Rh4 and inflammation were obtained for generating a protein–protein interaction (PPI) network. Molecular docking revealed the high affinities between key proteins and G-Rh4. Gene ontology (GO) and pathway enrichment analyses were used to analyze the screened core targets and explore the target–pathway networks. It was found that the JAK-STAT signaling pathway, TNF signaling pathway, NF-κB signaling pathway, and PI3K-Akt signaling pathway may be the key and main pathways of G-Rh4 to treat inflammation. Additionally, the potential molecular mechanisms of G-Rh4 predicted from network pharmacology analysis were validated in RAW264.7 cells. RT-PCR, Western blot, and ELISA analysis indicated that G-Rh4 significantly inhibited the production of pro-inflammatory cytokines such as TNF-α, IL-6, and IL-1β, as well as inflammation-related enzymes in lipopolysaccharide (LPS)-stimulated RAW264.7 cells. Moreover, in vitro experiments evaluated that Ginsenoside Rh4 exerts anti-inflammatory effects via the NF-κB and STAT3 signaling pathways. It is believed that our study will provide the basic scientific evidence that G-Rh4 has potential anti-inflammatory effects for further clinical studies.

A review of disease burden and clinical management for generalized pustular psoriasis in China

INTRODUCTION

Generalized pustular psoriasis (GPP) is a rare, severe, immune-mediated and potentially life-threatening skin disease. The rarity, differential diagnoses, relapsing nature, skin and systemic symptoms, complications and limited therapeutic approaches for this disease pose a clinical and psychological burden on patients and their families.

AREAS COVERED

Epidemiologic data of GPP in Chinese patients, including the disease prevalence and age of disease onset, as well as epidemiologic data in global populations were reviewed. Multiple proinflammatory cytokines are involved in the disease development and clinical presentation of GPP and the interleukin (IL)-36-mediated signalling pathway play a central role. Furthermore, loss-of-function mutations in IL-36RN (encoding the IL-36 receptor antagonist) are associated with GPP, suggesting a potential drug target for developing a disease-specific therapeutic approach. Biologic agents, including IL-36R targeted agents, are promising treatment options, especially as existing conventional therapies are inadequate. Chinese guidelines for the diagnosis and treatment of psoriasis recommend systemic and topical treatment options for GPP and disease complications, as well as for GPP during pregnancy and juvenile GPP.

EXPERT OPINION

This review summarizes the epidemiology, pathogenesis, clinical characteristics, disease burden and management of patients with GPP in China, and also describes future treatment targets and related clinical trials.

Qingfei Jiedu decoction inhibits PD-L1 expression in lung adenocarcinoma based on network pharmacology analysis, molecular docking and experimental verification

Objective: We aim at investigating the molecular mechanisms through which the Qingfei Jiedu decoction (QFJDD) regulates PD-L1 expression in lung adenocarcinoma (LUAD).

Methods: Bioactive compounds and targets of QFJDD were screened from TCMSP, BATMAN-TCM, and literature. Then, GeneCard, OMIM, PharmGKB, Therapeutic Target, and DrugBank databases were used to identify LUAD-related genes. The protein-protein interaction (PPI) network was constructed using overlapping targets of bioactive compounds in LUAD with the Cytoscape software and STRING database. The potential functions and pathways in which the hub genes were enriched by GO, KEGG, and DAVID pathway analyses. Molecular docking of bioactive compounds and key genes was executed via AutoDock Vina. Qualitative and quantitative analyses of QFJDD were performed using UPLC-Q-TOF-MS and UPLC. Expressions of key genes were determined by qRT-PCR, immunoreactivity score (IRS) of PD-L1 was assessed by immunohistochemistry (IHC), while the CD8⁺PD-1⁺T% derived from spleen tissues of Lewis lung cancer (LLC) bearing-mice was calculated using flow cytometry (FCM).

Results: A total of 53 bioactive compounds and 288 targets of QFJDD as well as 8151 LUAD associated genes were obtained. Further, six bioactive compounds, including quercetin, luteolin, kaempferol, wogonin, baicalein, and acacetin, and 22 hub genes were identified. The GO analysis showed that the hub genes were mainly enriched in DNA or RNA transcription. KEGG and DAVID pathway analyses revealed that 20 hub genes were primarily enriched in virus, cancer, immune, endocrine, and cardiovascular pathways. The EGFR, JUN, RELA, HIF1A, NFKBIA, AKT1, MAPK1, and MAPK14 hub genes were identified as key genes in PD-L1 expression and PD-1 checkpoint pathway. Moreover, ideal affinity and regions were identified between core compounds and key genes. Notably, QFJDD downregulated EGFR, JUN, RELA, HIF1A, NFKBIA, and CD274 expressions (p < 0.05), while it upregulated AKT1 and MAPK1 (p < 0.05) levels in A549 cells. The PD-L1 IRS of LLC tissue in the QFJDD high dose (H_d) group was lower than model group (p < 0.01). CD8⁺PD-1⁺T% was higher in the QFJDD H_d group than in normal and model groups (p < 0.05).

Conclusion: QFJDD downregulates PD-L1 expression and increases CD8⁺PD-1⁺T% via regulating HIF-1, EGFR, JUN and NFκB signaling pathways. Therefore, QFJDD is a potential treatment option for LUAD.

Mechanism of Zhinao Capsule in Treating Alzheimer’s Disease Based on Network Pharmacology Analysis and Molecular Docking Validation

Objective

This study aimed to determine the active components of Zhinao capsule (ZNC) and the targets in treating Alzheimer's disease (AD) so as to investigate and explore the mechanism of ZNC for AD.

Methods

The active components and targets of ZNC were determined from the traditional Chinese medicine systems pharmacology database (TCMSP). The target genes of AD were searched for in GeneCards. Cytoscape was used to construct an herb-component-target-disease network. A protein-protein interaction (PPI) network was constructed by STRING. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the OmicShare. UCSF Chimera and SwissDock were used for molecular docking verification. Finally, four key target genes were validated by Western blotting.

Results

In total, 55 active components, 287 targets of active components, 1197 disease genes, and 134 common genes were screened, which were significantly enriched in 3975 terms of biological processes (BP), 284 terms of cellular components (CC), 433 terms of molecular functions (MF), and 245 signaling pathways. Caspase-3 (CASP3) and beta-sitosterol, tumor necrosis factor-alpha (TNF-α) and quercetin, vascular endothelial growth factor A (VEGFA) and baicalein, and mitogen-activated protein kinase 1 (MAPK1) and quercetin showed good-to-better docking. Moreover, ZNC not only downregulated CASP3 and TNF-α protein expression but also upregulated the protein expression of VEGFA and MAPK1.

Conclusions

The active components of ZNC, such as beta-sitosterol, quercetin, and baicalein may act on multiple targets like CASP3, VEGFA, MAPK1, and TNF-α to affect T cell receptor (TCR), TNF, and MAPK signaling pathway, thereby achieving the treatment of AD. This study provides a scientific basis for further exploring the potential mechanism of ZNC in the treatment of AD and a reference for its clinical application.

ANTIBACTERIAL EFFECTS OF SINGLE AND COMBINED CRUDE EXTRACTS OF SYNADENIUM GLAUCESCENS AND COMMIPHORA SWYNNERTONII

Background

Synadenium glaucescens and Commiphora swynnertonii are among the reported plants used traditionally for treatment of bacterial infections. This study reports antibacterial effects of single and combined extracts from leaves, stem and root barks of Commiphora swynnertonii and Synadenium glaucescens.

Materials and Methods

Plants were collected from Manyara and Njombe regions in Tanzania. Extraction was done using dichloromethane and methanol. The extracts were assessed for antibacterial activity against Gram-positive bacteria (Staphylococcus aureus and Enterococcus faecalis) and Gram-negative bacteria (Escherichia coli, Klebsiella pneumonia and Pseudomonas aeruginosa). Minimum Inhibitory Concentrations (MIC) was determined by broth microdilution, while Fractional Inhibitory Concentration (FIC) indices were calculated from MIC values of combined extracts to determine combination effects.

Results

Strong antibacterial activities were demonstrated by all extracts of S. glaucescens (MIC 0.011-0.375mg/mL) against Gram-positive bacteria and methanol extracts of C. swynnertonii (MIC 0.047-0.375mg/mL). Synergistic effect was observed when combining methanol extracts of C. swynnertonii stem bark with S. glaucescens leaves against S. aureus (∑FIC 0.5), Other synergistic effects were observed against E. faecalis with dichloromethane extracts of C. swynnertonii stem bark and S. glaucescens stem bark (∑FIC 0.5), and C. swynnertonii root bark and S. glaucescens root bark (FIC index 0.3). For the remaining combinations, mainly additive effects were observed.

Conclusion

Synergistic effects on bacteria were observed by combining different plant parts of S. glaucescens and C. swynnertonii suggesting that it could be beneficial to combine such extracts when used for antibacterial purposes.

Network Pharmacological Study on the Mechanism of Cynanchum paniculatum (Xuchangqing) in the Treatment of Bungarus multicinctus Bites

Background

Bungarus multicinctus is one of the top ten venomous snakes in China. Its venom is mainly neurotoxin-based. Novel antivenom drugs need to be further researched and developed.

Objective

This study aimed to explore the molecular mechanism of Cynanchum paniculatum in treating Bungarus multicinctus bites based on network pharmacology. Material and methods. The potential active ingredients of Cynanchum paniculatum were screened and their SDF structures were obtained using the PubChem database and imported into the SwissTargetPrediction database, and targets were obtained for the antitoxin effects of Cynanchum paniculatum in the treatment of Bungarus multicinctus bites. The Cynanchum paniculatum-active compound-potential target network and protein-protein interaction network were constructed by using Cytoscape software, and then biological function analysis and KEGG pathway enrichment analysis were performed using the DAVID.

Results

Seven potential active components (cynapanoside C, cynatratoside B, tomentolide A, sitosterol, sarcostin, tomentogenin, and paeonol) and 286 drug targets were obtained, including 30 key targets for the treatment of bungarotoxin toxicity. The active components mainly acted on PIK3CA, MAPK1, MAP2K1, JAK2, FYN, ACHE, CHRNA7, CHRNA4, and CHRNB2, and they antagonized the inhibitory effect of bungarotoxin on the nervous system through cholinergic synapses and the neurotrophin signaling pathway.

Conclusions

Cynanchum paniculatum exerts a therapeutic effect on Bungarus multicinctus bites through multiple active components, multiple targets, and multiple pathways. The findings provide a theoretical basis for the extraction of active components of Cynanchum paniculatum and for related antivenom experiments.

Quantitative Analysis of Multicomponents in Qufeng Zhitong Capsule and Application of Network Pharmacology to Explore the Anti-Inflammatory Activity of Focused Compounds

Qufeng Zhitong capsule (QZC) is a well-known Chinese patent medicine that has been widely applied for the clinical treatment of rheumatoid arthritis and other inflammatory diseases. To date, its material basis is still unclear, which has greatly limited its clinical application. In this study, by taking advantage of ultra-high-performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry, 16 chemical components such as gallic acid, protocatechuic acid, and neochlorogenic acid in QZC were characterized and unambiguously identified based on comparison with the corresponding reference standards. In addition, the correlation between the focused components and their corresponding raw herbs from QZC prescription was investigated. For the first time, the relationship between the components mentioned above and their anti-inflammatory activity was explored via network pharmacology analysis, and a visualized network of "medicinal materials-QZC-compounds-targets-pathways" was established. Based on the brief prediction results of network pharmacological analysis, ultra-performance liquid chromatography coupled with photodiode array detector method was validated in terms of linearity, limit of detection, limit of quantification, precision, repeatability, stability, and recovery test and was successfully employed to determine 16 compounds in 28 batches of QZCs, which confirmed the feasibility and reliability of the established method for the quantitative analysis of 16 compounds in QZC. Considering the content and bioactivity of the tested components, four compounds were recommended as candidate indicators for quality evaluation ultimately. The potential value of this study could not only support a quality evaluation of QZC but also provide a theoretical basis for further in-depth research of QZC in clinical research.

Theabrownin and Poria cocos Polysaccharide Improve Lipid Metabolism via Modulation of Bile Acid and Fatty Acid Metabolism

Nonalcoholic fatty liver disease (NAFLD) is prevalent worldwide, while no pharmaceutical treatment has been approved. Natural herbs are promising for their amelioration effect on lipid metabolism. Theabrownin (TB) and Poria cocos polysaccharide (PCP) have been reported to have effect on hyperlipidemia and diabetes. Here, we compared the effect of individual TB or PCP and the combination of TB and PCP (TB + PCP) on NAFLD phenotypes and the alteration of metabolism in the mice with high-fat diet. The results showed that TB, PCP, and TB + PCP reduced serum and hepatic lipid levels, among which TB + PCP was the most effective. Serum metabolomic profile and liver mRNA analyses revealed that the treatments altered metabolic pathways involved in fatty acid metabolism, bile acid metabolism, and tricarboxylic acid cycle, which was also most significant in the TB + PCP group. This study demonstrated that TB, PCP, especially the combination of TB and PCP could be potential therapeutic formula for NAFLD that promoted lipid utilization and inhibited lipid synthesis and absorption.

Oral Administration of East Asian Herbal Medicine for Inflammatory Skin Lesions in Plaque Psoriasis: A Systematic Review, Meta-Analysis, and Exploration of Core Herbal Materials

Psoriasis is an inflammatory autoimmune skin disease with various clinical manifestations. The aim of this review was to systematically evaluate the efficacy and safety of oral administration of East Asian herbal medicine (EAHM) for inflammatory skin lesions in psoriasis and to explore core herbal materials for drug discovery. A comprehensive search was conducted in 10 electronic databases for randomized controlled trials from their inception until 29 July 2021. Statistical analysis was performed in R version 4.1.2 and R studio. When heterogeneity in studies was detected, the cause was identified through sensitivity analysis, meta-regression, and subgroup analysis. Methodological quality was independently assessed using the revised tool for risk of bias in randomized trials. A total of 56 trials with 4966 psoriasis patients met the selection criteria. Meta-analysis favored EAHM monotherapy on Psoriasis Area Severity Index (PASI) 70 (RR: 1.2845; 95% CI: 1.906 to 1.3858, p < 0.0001), PASI 60 (RR: 1.1923; 95% CI: 1.1134 to 1.2769, p < 0.0001), continuous PASI score (MD: −2.3386, 95% CI: −3.3068 to −1.3704, p < 0.0001), IL-17, IL-23, TNF-α, and Dermatology Life Quality Index. Patients treated with EAHM monotherapy had significantly reduced adverse events incidence rate. In addition, based on additional examination of the herb data included in this meta-analysis, 16 core materials were identified. They are utilized in close proximity to one another, and all have anti-inflammatory properties. The findings in this study support that oral EAHM monotherapy may be beneficial for inflammatory skin lesions in psoriasis. Meanwhile, the identified core materials are expected to be utilized as useful drug candidate hypotheses through follow-up studies on individual pharmacological activities and synergistic effects.

Network pharmacology combined with GEO database identifying the mechanisms and molecular targets of Polygoni Cuspidati Rhizoma on Peri-implants

Peri-implants is a chronic disease leads to the bone resorption and loss of implants. Polygoni Cuspidati Rhizoma (PCRER), a traditional Chinese herbal has been used to treat diseases of bone metabolism. However, its mechanism of anti-bone absorption still remains unknown. We aimed to identify its molecular target and the mechanism involved in PCRER potential treatment theory to Peri-implants by network pharmacology. The active ingredients of PCRER and potential disease-related targets were retrieved from TCMSP, Swiss Target Prediction, SEA databases and then combined with the Peri-implants disease differential genes obtained in the GEO microarray database. The crossed genes were used to protein–protein interaction (PPI) construction and Gene Ontology (GO) and KEGG enrichment analysis. Using STRING database and Cytoscape plug-in to build protein interaction network and screen the hub genes and verified through molecular docking by AutoDock vina software. A total of 13 active compounds and 90 cross targets of PCRER were selected for analysis. The GO and KEGG enrichment analysis indicated that the anti-Peri-implants targets of PCRER mainly play a role in the response in IL-17 signaling, Calcium signaling pathway, Toll-like receptor signaling pathway, TNF signaling pathway among others. And CytoHubba screened ten hub genes (MMP9, IL6, MPO, IL1B, SELL, IFNG, CXCL8, CXCL2, PTPRC, PECAM1). Finally, the molecular docking results indicated the good binding ability with active compounds and hub genes. PCRER’s core components are expected to be effective drugs to treat Peri-implants by anti-inflammation, promotes bone metabolism. Our study provides new thoughts into the development of natural medicine for the prevention and treatment of Peri-implants.

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.

Network-driven targeted analysis reveals that Astragali Radix alleviates doxorubicin-induced cardiotoxicity by maintaining fatty acid homeostasis

ETHNOPHARMACOLOGICAL RELEVANCE

Astragali Radix (AR) is a popular traditional Chinese medicine that has been used for more than 2000 years. It is a well-known tonic for weak people with chronic diseases, such as heart failure and cerebral ischemia. Previous studies have reported that AR could support the "weak heart" of cancer patients who suffered from doxorubicin (DOX)-induced cardiotoxicity (DIC). However, the underlying mechanism remains unclear.

AIM OF THE STUDY

This study aimed to uncover the critical pathways and molecular determinants for AR against DIC by fully characterizing the network-based relationship.

MATERIALS AND METHODS

We integrated ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) profiling, database and literature searching, and the human protein-protein interactome to discover the specific network module associated with AR against DIC. To validate the network-based findings, a low-dose, long-term DIC mouse model and rat cardiomyoblast H9c2 cells were employed. The levels of potential key metabolites and proteins in hearts and cells were quantified by the LC-MS/MS targeted analysis and western blotting, respectively.

RESULTS

We constructed one of the most comprehensive AR component-target network described to date, which included 730 interactions connecting 64 unique components and 359 unique targets. Relying on the network-based evaluation, we identified fatty acid metabolism as a putative critical pathway and peroxisome proliferator-activated receptors (PPARα and PPARγ) as potential molecular determinants. We then confirmed that DOX caused the accumulation of fatty acids in the mouse failing heart, while AR promoted fatty acid metabolism and preserved heart function. By inhibiting PPARγ in H9c2 cells, we further found that AR could alleviate DIC by activating PPARγ to maintain fatty acid homeostasis.

CONCLUSIONS

Our findings imply that AR is a promising drug candidate that treats DIC by maintaining fatty acid homeostasis. More importantly, the network-based method developed here could facilitate the mechanism discovery of AR therapy and help catalyze innovation in its clinical application.

Mining Important Herb Combinations of Traditional Chinese Medicine against Hypertension Based on the Symptom-Herb Network Combined with Network Pharmacology

Although data mining methods are extensively used in the rule analysis of famous old traditional Chinese medicine (TCM) experts' prescriptions for the treatment of hypertension, most of them only mine the association between herbs and herbs, ignoring the importance of symptoms in the disease. This study collected 439 cases of hypertension treated by famous old TCM experts from the FangNet platform. Using the structure network algorithm, the symptom-herb network was constructed, which redefined the importance of herb in disease. Based on the network, 21 driver herbs, 76 herb pairs, and 41 symptom-herb associations were mined. Finally, the basic prescription composed of Gouteng (Uncariae Ramulus cum Uncis), Huanglian (Coptidis Rhizoma), Chuanxiong (Chuanxiong Rhizoma), Gegen (Puerariae Lobatae Radix), Danggui (Angelicae Sinensis Radix), and Huangqin (Scutellariae Radix) was found. These herbs are the most significant among all herbs, and they have a potential correlation with each other. To further verify the rationality of the data mining results, we adopted the network pharmacology method. Network pharmacological analysis shows that the five core targets in the basic prescription include IL6, VEGFA, TNF, TP53, and EGF, which link 10 significant active compounds and 7 important KEGG pathways. It was predicted that anti-inflammatory, antioxidant, vascular endothelial protection, emotion regulation, and ion channel intervention might be the main mechanisms of the basic prescription against hypertension. This study reveals the prescription rule of famous old TCM experts for treating hypertension from a new perspective, which provides a new approach to inherit the academic experience of famous old TCM experts and develop new drugs.