Network pharmacology, a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

Abstract Network pharmacology can ascertain the therapeutic mechanism of drugs for treating diseases at the level of biological targets and pathways. The effective mechanism study of traditional Chinese medicine (TCM) characterized by multi-component, multi-targeted, and integrative efficacy, perfectly corresponds to the application of network pharmacology. Currently, network pharmacology has been widely utilized to clarify the mechanism of the physiological activity of TCM. In this review, we comprehensively summarize the application of network pharmacology in TCM to reveal its potential of verifying the phenotype and underlying causes of diseases, realizing the personalized and accurate application of TCM. We searched the literature using “TCM network pharmacology” and “network pharmacology” as keywords from Web of Science, PubMed, Google Scholar, as well as Chinese National Knowledge Infrastructure in the last decade. The origins, development, and application of network pharmacology are closely correlated with the study of TCM which has been applied in China for thousands of years. Network pharmacology and TCM have the same core idea and promote each other. A well-defined research strategy for network pharmacology has been utilized in several aspects of TCM research, including the elucidation of the biological basis of diseases and syndromes, the prediction of TCM targets, the screening of TCM active compounds, and the decipherment of mechanisms of TCM in treating diseases. However, several factors limit its application, such as the selection of databases and algorithms, the unstable quality of the research results, and the lack of standardization. This review aims to provide references and ideas for the research of TCM and to encourage the personalized and precise use of Chinese medicine. 

Network pharmacology: a bright guiding light on the way to explore the personalized precise medication of traditional Chinese medicine

Traditional Chinese Medicine (TCM), renowned for its holistic approach with a 2000-year history of utilizing natural remedies, offers unique advantages in disease prevention and treatment. Berberine, found in various Chinese herbs, has been employed for many years, primarily for addressing conditions such as diarrhea and dysentery. Berberine has recently become a research focus owing to its pharmacological activities and benefits to human bodies. However, little is known about the anti-inflammatory mechanism of berberine.To summarize recent findings regarding the pharmacological effects and mechanisms of berberine anti-inflammation and highlight and predict the potential therapeutic effects and systematic mechanism of berberine.Recent studies (2013-2023) on the pharmacological effects and mechanisms of berberine anti-inflammation were retrieved from Web of Science, PubMed, Google Scholar, and Scopus up to July 2023 using relevant keywords. Network pharmacology and bioinformatics analysis were employed to predict the therapeutic effects and mechanisms of berberine against potential diseases.The related pharmacological mechanisms of berberine anti-inflammation include the inhibition of inflammatory cytokine production (e.g., IL-1β, IL-6, TNF-α), thereby attenuating the inflammatory response; Inhibiting the activation of NF-κB signaling pathway and IκBα degradation; Inhibiting the activation of MAPK signaling pathway; Enhancing the activation of the STAT1 signaling pathway; Berberine interacts directly with cell membranes through a variety of pathways, thereby influencing cellular physiological activities. Berberine enhances human immunity and modulates immune system function, which is integral to addressing certain autoimmune and tumour-related health concerns.This study expounds on the correlation between berberine and inflammatory diseases, encapsulating the mechanisms through which berberine treats select typical inflammatory ailments. Furthermore, it delves into a deeper understanding of berberine's effectiveness by integrating network pharmacology and molecular docking techniques in the context of treating inflammatory diseases. It provides guidance and reference for berberine's subsequent revelation of the modern scientific connotation of Chinese medicine. 

Inhibition of inflammation by berberine: molecular mechanism and network pharmacology analysis

Herein, network pharmacology was used to identify the active components in Ilex kudingcha and common hypertension-related targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted, and molecular docking was performed to verify molecular dynamic simulations. Six active components in Ilex kudingcha were identified; furthermore, 123 target genes common to hypertension were identified. Topological analysis revealed the strongly associated proteins, with RELA, AKT1, JUN, TP53, TNF, and MAPK1 being the predicted targets of the studied traditional Chinese medicine. In addition, GO enrichment analysis revealed significant enrichment of biological processes such as oxidative stress, epithelial cell proliferation, cellular response to chemical stress, response to xenobiotic stimulus, and wound healing. Furthermore, KEGG enrichment analysis revealed that the genes were particularly enriched in lipid and atherosclerosis, fluid shear stress and atherosclerosis, and other pathways. Molecular docking revealed that the key components in Ilex kudingcha exhibited good binding potential to the target genes RELA, AKT1, JUN, TP53, TNF, and IL-6. Our study results suggest that Ilex kudingcha plays a role in hypertension treatment by exerting hypolipidemic, anti-inflammatory, and antioxidant effects and inhibiting the transcription of atherosclerosis-related genes.

Network pharmacology- and molecular docking-based analyses of the antihypertensive mechanism of Ilex kudingcha

Wuwei Shexiang Pill (WSP) is a Tibetan traditional medicine, which has been demonstrated to exhibit potent anti-inflammatory and anti-gout effects. However, the specific pharmacological mechanism is not elucidated clearly. In the present study, liquid chromatography-mass spectrometry (LC-MS)-based metabolomics was applied to investigate the alteration of serum metabolites induced by WSP treatment in MSU-induced gouty rats. Subsequently, bioinformatics was utilized to analyze the potential metabolic pathway of the anti-gout effect of WSP. The pharmacodynamic data discovered that WSP could ameliorate ankle swelling and inflammatory cell infiltration, as well as downregulate the protein expression of IL-1β, p-NF-κB p65, and NLRP3 in the synovial membrane and surrounding tissues of gouty ankles. LC-MS-based metabolomics revealed that there were 30 differential metabolites in the serum between sham-operated rats and gouty ones, which were mainly involved in the metabolism of fructose and mannose, primary bile acid biosynthesis, and cholesterol metabolism. However, compared to the model group, WSP treatment upregulated 11 metabolic biomarkers and downregulated 31 biomarkers in the serum. KEGG enrichment analysis found that 27 metabolic pathways contributed to the therapeutic action of WSP, including linoleic acid metabolism, phenylalanine metabolism, and pantothenate and CoA biosynthesis. The comprehensive analysis-combined network pharmacology and metabolomics further revealed that the regulatory network of WSP against gout might be attributed to 11 metabolites, 7 metabolic pathways, 39 targets, and 49 active ingredients of WSP. In conclusion, WSP could ameliorate the inflammation of the ankle in MSU-induced gouty rats, and its anti-gout mechanism might be relevant to the modulation of multiple metabolic pathways, such as linoleic acid metabolism, phenylalanine metabolism, and pantothenate and CoA biosynthesis. This study provided data support for the secondary development of Chinese traditional patent medicine.

LC-MS-based metabolomics reveals the mechanism of anti-gouty arthritis effect of Wuwei Shexiang pill

Traditional Chinese Medicine (TCM) has been extensively used as a mainstay for treating various pathologies. Combing the pharmacology and systems biology approaches, the network pharmacology (NP) approach was developed to predict the probable mechanism underlying the therapeutic effect of TCM. However, approaches solely based on NP cannot effectively elucidate the curative mechanism in a holistic and reliable manner due to limitations in NP-based methods and complexity of TCM components. Thus, integration strategies combining NP with other approaches are increasingly being used. Since the interdisciplinary research in TCM has received much attention in the advent of the big data era of which the NP-based integration strategy is broadly used, the strategy is clearly elaborated in the present review. We summarized several NP-based integration strategies and their applications in TCM studies, including multi-omics approach, gut microbiota study, chemical information analysis, data-mining, and network toxicology study.

Integration strategy of network pharmacology in Traditional Chinese Medicine: a narrative review.

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Integration strategy of network pharmacology in Traditional Chinese Medicine: a narrative review.