Bibliometric Analysis of Network Pharmacology in Traditional Chinese Medicine

Miao, Run-Pei; Meng, Qinggang; Wang, Chennan; Yuan, Wenjing

doi:10.1155/2022/1583773

Cited by 6 publications

(4 citation statements)

References 44 publications

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“…Notably, the rational structural modifications of AChE inhibitors were still the primary route to the discovery of novel One-molecule-multi-target anti-AD drugs at this stage (Rossi et al, 2021;Sang et al, 2022;Turgutalp et al, 2022). Since these two alkaloids' high potential in vitro acetylcholinesterase inhibitory activity had been verified by other researchers (Jia et al, 2021;Tang et al, 2021;Miao et al, 2022). Molecular docking analysis was used to predict the binding mode between these two compounds and AChE.…”

Section: Discussionmentioning

confidence: 99%

“…Even so, there are still some problems to overcome. Based on the newly bibliometric analysis results of network pharmacology in TCM, determining the key ingredients in TCM ( Miao et al, 2022 ) just based solely on data from limited databases is not sufficient, which may impact the quality of follow-up research. Researchers believe that this phenomenon occurred because the public databases do not reflect the difference in the composition and content of TCM compounds.…”

Section: Discussionmentioning

confidence: 99%

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Potential bioactive compounds and mechanisms of Fibraurea recisa Pierre for the treatment of Alzheimer’s disease analyzed by network pharmacology and molecular docking prediction

Wang

Ma²,

Huang³

et al. 2022

Front. Aging Neurosci.

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IntroductionHeat-clearing and detoxifying Chinese medicines have been documented to have anti-Alzheimer’s disease (AD) activities according to the accumulated clinical experience and pharmacological research results in recent decades. In this study, Fibraurea recisa Pierre (FRP), the classic type of Heat-clearing and detoxifying Chinese medicine, was selected as the object of research.Methods12 components with anti-AD activities were identified in FRP by a variety of methods, including silica gel column chromatography, multiple databases, and literature searches. Then, network pharmacology and molecular docking were adopted to systematically study the potential anti-AD mechanism of these compounds. Consequently, it was found that these 12 compounds could act on 235 anti-AD targets, of which AKT and other targets were the core targets. Meanwhile, among these 235 targets, 71 targets were identified to be significantly correlated with the pathology of amyloid beta (Aβ) and Tau.Results and discussionIn view of the analysis results of the network of active ingredients and targets, it was observed that palmatine, berberine, and other alkaloids in FRP were the key active ingredients for the treatment of AD. Further, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis revealed that the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway were the most significant signaling pathways for FRP to play an anti-AD role. Findings in our study suggest that multiple primary active ingredients in FRP can play a multitarget anti-AD effect by regulating key physiological processes such as neurotransmitter transmission and anti-inflammation. Besides, key ingredients such as palmatine and berberine in FRP are expected to be excellent leading compounds of multitarget anti-AD drugs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Potential bioactive compounds and mechanisms of Fibraurea recisa Pierre for the treatment of Alzheimer’s disease analyzed by network pharmacology and molecular docking prediction

Wang

Ma²,

Huang³

et al. 2022

Front. Aging Neurosci.

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“…Network construction primarily involves the seamless integration of three crucial types of databases: compound-target related databases, disease-gene related databases, and protein-protein interaction databases. By analyzing the topological properties of drug nodes within the constructed network, the active substances in TCM can be ultimately determined [7,8]. To further enhance the accuracy of predictions, a new network analysis method called Network-based Proximity has been developed to predict drug efficacy [9], and some studies have demonstrated that this method can better identify active molecules in TCM [10].…”

Section: Introductionmentioning

confidence: 99%

Meta-path-based drug efficacy prediction model for active natural compound discovery from Traditional Chinese medicine

Li,

Shen,

Cai

et al. 2024

Preprint

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Identifying the active nature compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. Here, we proposed Meta-DEP, a Meta-paths-based Drug Efficacy Prediction based on drug-protein-disease heterogeneity network, where Meta-paths contains all the shortest paths between drug targets and disease-related proteins in the network and drug efficacy is measured by a predictive score according to drug disease network proximity. Experiments show that Meta-DEP performs better than traditional network topology analysis on drug-disease interaction prediction task. Further investigations demonstrate that the key targets identified by Meta-DEP for drug efficacy are consistent with clinical pharmacological evidence. To prove that Meta-DEP can be used to discover active nature compounds, we apply it to predict the relationship between the monomeric components of traditional Chinese medicine included in the TCMSP database and diseases. Results indicate that Meta-DEP can accurately predict most of the drug-disease pairs included in the TCMSP database. In addition, biological experiments are directly used to demonstrate that the natural compound mined by Meta-DEP from traditional Chinese medicine has a protective effect against myocardial ischemia. Overall, the model developed in this study provides new impetus for driving the nature compound into innovative lead molecule. Code and data are available at https://github.com/t9lex/Meta-DEP.

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“…[4] Network pharmacology can analyze the biological behavior of various drug molecules operating on diverse targets, cells, and organs from the genetic and molecular levels, which can predict and disclose the effects and mechanisms of the different drug molecules. [5] According to the interaction network of "drug-chemical component-target-disease," through network topology analysis, systematically and comprehensively observe and study the intervention and influence of drugs on diseases, revealing the mystery of the multi-molecular properties of drugs that act synergistically on the human body. Network pharmacology has the characteristics of holistic and systemic nature, which coincides with the holistic view of Chinese medicine, and is currently one of the important methods for the discovery of the material basis of Chinese medicine efficacy.…”

Section: Introductionmentioning

confidence: 99%

Exploring the active components and mechanism of modified bazhen decoction in treatment of chronic cerebral circulation insufficiency based on network pharmacology and molecular docking

Xu,

Shen,

2023

Medicine

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Modified bazhen decoction (MBZD) is a classical Chinese medicine formula with potential efficacy in the treatment of chronic cerebral circulation insufficiency (CCCI), and its main components and potential mechanisms are still unclear. The study aimed to investigate the active ingredients and mechanism of action of MBZD in treating CCCI through network pharmacology combined with molecular docking. The chemical composition and targets of 11 Chinese herbs in MBZD were retrieved utilizing the traditional Chinese medicine systems pharmacology database and analysis platform platform, and the targets for CCCI were screened by Genecards, online mendelian inheritance in man, therapeutic target database, and comparative toxicogenomics database databases. The targets were genetically annotated with the Uniprot database. We created a compound-target network employing Cytoscape software and screened the core targets for the treatment of CCCI by CytoNCA clustering analysis; the AutoDock Vina program performed molecular docking study of crucial targets. One thousand one hundred ninety-one active compounds were obtained, 2210 corresponding targets were predicted, 4971 CCCI-related targets were obtained, and 136 intersecting genes were identified between them. The central core targets were IL6, MAPK14, signal transducer and activator of transcription 3, RELA, VEGFA, CCND1, CASP3, AR, FOS, JUN, EGFR, MAPK1, AKT1, MYC, and ESR1; gene ontology functional enrichment analysis yielded 911 gene ontology items (P < .01), while Kyoto Encyclopedia of Genes and Genomes pathway enrichment yielded 138 signal pathways (P < .01), primarily including oxidative reactions, vascular regulation, apoptosis, and PI3K-Akt signaling pathway. The molecular docking results showed that the core active component of MBZD had good binding with the main target. This research initially uncovered the mechanism of action of MBZD via multi-component-multi-target-multi-pathway for the treatment of CCCI, providing the theoretical basis for the clinical application of MBZD.

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Bibliometric Analysis of Network Pharmacology in Traditional Chinese Medicine

Cited by 6 publications

References 44 publications

Potential bioactive compounds and mechanisms of Fibraurea recisa Pierre for the treatment of Alzheimer’s disease analyzed by network pharmacology and molecular docking prediction

Potential bioactive compounds and mechanisms of Fibraurea recisa Pierre for the treatment of Alzheimer’s disease analyzed by network pharmacology and molecular docking prediction

Meta-path-based drug efficacy prediction model for active natural compound discovery from Traditional Chinese medicine

Exploring the active components and mechanism of modified bazhen decoction in treatment of chronic cerebral circulation insufficiency based on network pharmacology and molecular docking

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