Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning

Yang, Jian; Tian, Sai; Zhao, Jing; Zhang, Weidong

doi:10.1016/j.phrs.2020.105034

Cited by 72 publications

(44 citation statements)

References 86 publications

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“…In detail, before the algorithm was executed, a sub-network of SNS genes and NAFLD genes was obtained from the Snet and considered to be the core PPI network of SNS against NAFLD. The RWR algorithm was employed with seed genes as SNS genes and a restarting probability (r) of 0.75 by RandomWalkRestartMH R package, as in previous studies (Yang et al, 2020). The top 10 genes with the highest affinity scores were identified.…”

Section: Network-based Efficacy Evaluation Of Sinisan Against Non-alcoholic Fatty Liver Diseasementioning

confidence: 99%

Network Pharmacology-Based Analysis on the Potential Biological Mechanisms of Sinisan Against Non-Alcoholic Fatty Liver Disease

et al. 2021

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Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease in China. Sinisan (SNS) is a traditional Chinese medicine formula that has been widely used in treating chronic liver diseases, including NAFLD. However, its underlying biological mechanisms are still unclear. In this study, we employed a network pharmacology approach consisting of overlapped terms- (genes or pathway terms-) based analysis, protein-protein interaction (PPI) network-based analysis, and PPI clusters identification. Unlike the previous network pharmacology study, we used the shortest path length-based network proximity algorithm to evaluate the efficacy of SNS against NAFLD. And we also used random walk with restart (RWR) algorithm and Community Cluster (Glay) algorithm to identify important targets and clusters. The screening results showed that the mean shortest path length between genes of SNS and NAFLD was significantly smaller than degree-matched random ones. Six PPI clusters were identified and ten hub targets were obtained, including STAT3, CTNNB1, MAPK1, MAPK3, AGT, NQO1, TOP2A, FDFT1, ALDH4A1, and KCNH2. The experimental study indicated that SNS reduced hyperlipidemia, liver steatosis, and inflammation. Most importantly, JAK2/STAT3 signal was inhibited by SNS treatment and was recognized as the most important signal considering the network pharmacology part. This study provides a systems perspective to study the relationship between Chinese medicines and diseases and helps to discover potential mechanisms by which SNS ameliorates NAFLD.

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Section: Network-based Efficacy Evaluation Of Sinisan Against Non-alcoholic Fatty Liver Diseasementioning

confidence: 99%

Network Pharmacology-Based Analysis on the Potential Biological Mechanisms of Sinisan Against Non-Alcoholic Fatty Liver Disease

et al. 2021

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“…Usually, same disease diagnosed by orthodox medical methods could have different TCM Syndromes. For example, in TCM diagnosis, rheumatoid arthritis is classified as the types of cold Syndrome and heat Syndrome [ 3 , 4 ], coronary heart disease is categorized as several Syndromes, including heart-blood stasis, Qi stagnation and blood stasis, Qi deficiency and blood stasis, as well as Cold Congealing and Qi Stagnation [ 5 ]. Hence different TCM formulae were prescribed for different Syndromes of the same disease.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, several types of typical TCM Syndromes have been well-established in TCM theory, such as Cold Congealing and Qi Stagnation (CCQS), and Qi Stagnation and Blood Stasis (QSBS), etc. [ 5 , 7 ]. Although the patient stratification of CHD with different Syndromes is practical for “precise therapy” with diversified formula in TCM, the scientific basis for Syndrome differentiation of CHD is poorly understood so far.…”

Section: Introductionmentioning

confidence: 99%

Exploring biological basis of Syndrome differentiation in coronary heart disease patients with two distinct Syndromes by integrated multi-omics and network pharmacology strategy

Zhao

Song

et al. 2021

Chin Med

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Background Traditional Chinese Medicine (TCM) is distinguished by Syndrome differentiation, which prescribes various formulae for different Syndromes of same disease. This study aims to investigate the underlying mechanism. Methods Using a strategy which integrated proteomics, metabolomics study for clinic samples and network pharmacology for six classic TCM formulae, we systemically explored the biological basis of TCM Syndrome differentiation for two typical Syndromes of CHD: Cold Congealing and Qi Stagnation (CCQS), and Qi Stagnation and Blood Stasis (QSBS). Results Our study revealed that CHD patients with CCQS Syndrome were characterized with alteration in pantothenate and CoA biosynthesis, while more extensively altered pathways including D-glutamine and D-glutamate metabolism; alanine, aspartate and glutamate metabolism, and glyoxylate and dicarboxylate metabolism, were present in QSBS patients. Furthermore, our results suggested that the down-expressed PON1 and ADIPOQ might be potential biomarkers for CCQS Syndrome, while the down-expressed APOE and APOA1 for QSBS Syndrome in CHD patients. In addition, network pharmacology and integrated analysis indicated possible comorbidity differences between the two Syndromes, that is, CCQS or QSBS Syndrome was strongly linked to diabetes or ischemic stroke, respectively, which is consistent with the complication disparity between the enrolled patients with two different Syndromes. These results confirmed our assumption that the molecules and biological processes regulated by the Syndrome-specific formulae could be associated with dysfunctional objects caused by the Syndrome of the disease. Conclusion This study provided evidence-based strategy for exploring the biological basis of Syndrome differentiation in TCM, which sheds light on the translation of TCM theory in the practice of precision medicine.

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“…When combined with machine learning algorithms, the potential relationships between herbs and diseases as identified in the databases can be used to evaluate and predict the efficacy of traditional Chinese medicine and to infer its mechanisms of action. Previously, the effective herb combinations were condensed, and the disease phenotype and drug chemical properties were integrated at the levels of pharmacology and protein interaction to show the effect of TCM formulae on disease biomolecule networks and to explain biomolecule action mechanisms [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Summarizing the Effective Herbs for the Treatment of Hypertensive Nephropathy by Complex Network and Machine Learning

Huan

Wei

et al. 2021

Evidence-Based Complementary and Alternative Medicine

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Hypertensive nephropathy is a common complication of hypertension. Traditional Chinese medicine has been used in the clinical treatment of hypertensive nephropathy for a long time, but the commonly used prescriptions have not been summarized, and the basic therapeutic approaches have not been discussed. Based on data from 3 years of electronic medical records of traditional Chinese medicine used at the Affiliated Hospital of Shandong University of Traditional Chinese Medicine, a complex network and machine learning algorithm was used to explore the prescribed herbs of traditional Chinese medicine in the treatment of hypertensive nephropathy (HN). In this study, complex network algorithms were used to describe traditional Chinese medicine prescriptions for HN treatment. The Apriori algorithm was used to analyze the compatibility of these treatments with modern medicine. Data on the targets and regulatory genes related to hypertensive nephropathy and the herbs that affect their expression were obtained from public databases, and then, the signaling pathways enriched with these genes were identified on the basis of their participation in biological processes. A clustering algorithm was used to analyze the therapeutic pathways at multiple levels. A total of 1499 prescriptions of traditional Chinese medicines used for the treatment of hypertensive renal damage were identified. Fourteen herbs used to treat hypertensive nephropathy act through different biological pathways: huangqi, danshen, dangshen, fuling, baizhu, danggui, chenpi, banxia, gancao, qumai, cheqianzi, ezhu, qianshi, and niuxi. We found the formulae of these herbs and observed that they could downregulate the expression of inflammatory cytokines such as TNF, IL1B, and IL6 and the NF-κB and MAPK signaling pathways to reduce the renal inflammatory damage caused by excessive activation of RAAS. In addition, these herbs could facilitate the deceleration in the decline of renal function and relieve the symptoms of hypertensive nephropathy. In this study, the traditional Chinese medicine approach for treating hypertensive renal damage is summarized and effective treatment prescriptions were identified and analyzed. Data mining technology provided a feasible method for the collation and extraction of traditional Chinese medicine prescription data and provided an objective and reliable tool for use in determining the TCM treatments of hypertensive nephropathy.

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Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning

Cited by 72 publications

References 86 publications

Network Pharmacology-Based Analysis on the Potential Biological Mechanisms of Sinisan Against Non-Alcoholic Fatty Liver Disease

Network Pharmacology-Based Analysis on the Potential Biological Mechanisms of Sinisan Against Non-Alcoholic Fatty Liver Disease

Exploring biological basis of Syndrome differentiation in coronary heart disease patients with two distinct Syndromes by integrated multi-omics and network pharmacology strategy

Summarizing the Effective Herbs for the Treatment of Hypertensive Nephropathy by Complex Network and Machine Learning

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