Skip to main content

TCM Preparation Network Pharmacology Analysis

  • Chapter
  • First Online:
Traditional Chinese Medicine and Diseases

Part of the book series: Translational Bioinformatics ((TRBIO,volume 18))

  • 291 Accesses

Abstract

Computational biology and multi-omics have expanded the study of system biology, which have led to studies on network pharmacology as a result of this progress (Boezio et al. 2017). Thus, this approach has changed from a single-drug approach to an approach focused on several targets and multiple components of diseases. Small-molecule regulation principles are revealed in a high-throughput manner by network pharmacology, which establishes a “compound-protein/gene-disease” network. TCM preparations, in particular, benefit greatly from network pharmacology in drug analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abeyrathna P, Su Y. The critical role of Akt in cardiovascular function. Vasc Pharmacol. 2015;74:38–48.

    Article  CAS  Google Scholar 

  • Amberger JS, Hamosh A. Searching online Mendelian inheritance in man (OMIM): a knowledgebase of human genes and genetic phenotypes. Curr Protoc Bioinformatics. 2017;58:1.2.1–1.2.12.

    Article  Google Scholar 

  • An L, Feng F. Network pharmacology-based antioxidant effect study of zhi-zi-da-huang decoction for alcoholic liver disease. Evid Based Complement Alternat Med. 2015;2015:492470.

    Article  Google Scholar 

  • Auyeung KK, Han QB, Ko JK. Astragalus membranaceus: a review of its protection against inflammation and gastrointestinal cancers. Am J Chin Med. 2016;44(1):1–22.

    Article  Google Scholar 

  • Becker KG, et al. The genetic association database. Nat Genet. 2004;36(5):431–2.

    Article  CAS  Google Scholar 

  • Boezio B, et al. Network-based approaches in pharmacology. Mol Inform. 2017;36:10.

    Article  Google Scholar 

  • Buhlmann S, Reymond JL. ChEMBL-likeness score and database GDBChEMBL. Front Chem. 2020;8:46.

    Article  Google Scholar 

  • Byrne NM, et al. Intermittent energy restriction improves weight loss efficiency in obese men: the MATADOR study. Int J Obes. 2018;42(2):129–38.

    Article  CAS  Google Scholar 

  • Chai Z, et al. Generating adverse outcome pathway (AOP) of inorganic arsenic-induced adult male reproductive impairment via integration of phenotypic analysis in comparative toxicogenomics database (CTD) and AOP wiki. Toxicol Appl Pharmacol. 2021;411:115370.

    Article  CAS  Google Scholar 

  • Chen CY. TCM Database@Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico. PLoS One. 2011;6(1):e15939.

    Article  CAS  Google Scholar 

  • Chen JY, Mamidipalli S, Huan T. HAPPI: an online database of comprehensive human annotated and predicted protein interactions. BMC Genomics. 2009;10(Suppl 1):S16.

    Article  Google Scholar 

  • Chen X, Ji ZL, Chen YZ. TTD: therapeutic target database. Nucleic Acids Res. 2002;30(1):412–5.

    Article  CAS  Google Scholar 

  • Corson TW, Crews CM. Molecular understanding and modern application of traditional medicines: triumphs and trials. Cell. 2007;130(5):769–74.

    Article  CAS  Google Scholar 

  • Cotto KC, et al. DGIdb 3.0: a redesign and expansion of the drug-gene interaction database. Nucleic Acids Res. 2018;46(D1):D1068–73.

    Article  CAS  Google Scholar 

  • Ding ZH, et al. Systems pharmacology reveals the mechanism of activity of Ge-Gen-Qin-Lian decoction against LPS-induced acute lung injury: a novel strategy for exploring active components and effective mechanism of TCM formulae. Pharmacol Res. 2020;156

    Google Scholar 

  • El-Arabey AA, Abdalla M, Ali Eltayb W. Metformin: ongoing journey with Superdrug revolution. Adv Pharm Bull. 2019;9(1):1–4.

    Article  CAS  Google Scholar 

  • Fan X, et al. Network toxicology and its application to traditional Chinese medicine. Zhongguo Zhong Yao Za Zhi. 2011;36(21):2920–2.

    Google Scholar 

  • Fonger GC, et al. TOXNET: a computerized collection of toxicological and environmental health information. Toxicol Ind Health. 2000;16(1):4–6.

    Article  CAS  Google Scholar 

  • Gfeller D, et al. SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Nucleic Acids Res. 2014;42(Web Server issue):W32-8.

    Google Scholar 

  • Gilson MK, et al. BindingDB in 2015: a public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Res. 2016;44(D1):D1045-53.

    Article  Google Scholar 

  • Goel R, et al. Human protein reference database and human Proteinpedia as resources for phosphoproteome analysis. Mol BioSyst. 2012;8(2):453–63.

    Article  CAS  Google Scholar 

  • Gunther S, et al. SuperTarget and Matador: resources for exploring drug-target relationships. Nucleic Acids Res. 2008;36(Database issue):D919-22.

    Google Scholar 

  • Herrera Vazquez MM, et al. A network to promote health systems based on primary health care in the region of the Americas. Rev Panam Salud Publica. 2007;21(5):261–73.

    Google Scholar 

  • Hogan M, Berger JS. Heparin-induced thrombocytopenia (HIT): review of incidence, diagnosis, and management. Vasc Med. 2020;25(2):160–73.

    Article  Google Scholar 

  • Hong M, et al. A network-based pharmacology study of the herb-induced liver injury potential of traditional hepatoprotective Chinese herbal medicines. Molecules. 2017;22:4.

    Article  Google Scholar 

  • Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol. 2008;4(11):682–90.

    Article  CAS  Google Scholar 

  • Huang JH, et al. Network pharmacology-based approach to investigate the analgesic efficacy and molecular targets of Xuangui dropping pill for treating primary dysmenorrhea. Evid Based Complement Alternat Med. 2017;2017:7525179.

    Article  Google Scholar 

  • Huang L, et al. TCMID 2.0: a comprehensive resource for TCM. Nucleic Acids Res. 2018;46(D1):D1117–20.

    Article  CAS  Google Scholar 

  • Jarrell JT, et al. Network medicine for Alzheimer's disease and traditional Chinese medicine. Molecules. 2018;23:5.

    Article  Google Scholar 

  • Khalfaoui T, Lizard G, Ouertani-Meddeb A. Adhesion molecules (ICAM-1 and VCAM-1) and diabetic retinopathy in type 2 diabetes. J Mol Histol. 2008;39(2):243–9.

    Article  CAS  Google Scholar 

  • Kim J, et al. DigSee: disease gene search engine with evidence sentences (version cancer). Nucleic Acids Res. 2013;41(Web Server issue):W510-7.

    Google Scholar 

  • Kim S, et al. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 2021;49(D1):D1388–95.

    Article  CAS  Google Scholar 

  • Leung KW, et al. Ginsenoside-Rg1 induces vascular endothelial growth factor expression through the glucocorticoid receptor-related phosphatidylinositol 3-kinase/Akt and beta-catenin/T-cell factor-dependent pathway in human endothelial cells. J Biol Chem. 2006;281(47):36280–8.

    Article  CAS  Google Scholar 

  • Li JY, et al. Metabolic profiling of the effects of ginsenoside re in an Alzheimer's disease mouse model. Behav Brain Res. 2018;337:160–72.

    Article  CAS  Google Scholar 

  • Li S, Zhang B, Zhang NB. Network target for screening synergistic drug combinations with application to traditional Chinese medicine. BMC Syst Biol. 2011;5:S10.

    Article  Google Scholar 

  • Liang XJ, Li HY, Li S. A novel network pharmacology approach to analyse traditional herbal formulae: the Liu-Wei-Di-Huang pill as a case study. Mol BioSyst. 2014;10(5):1014–22.

    Article  CAS  Google Scholar 

  • Liu Q, et al. Application of network pharmacology and high through-put technology on active compounds screening from traditional Chinese medicine. Zhongguo Zhong Yao Za Zhi. 2012;37(2):134–7.

    CAS  Google Scholar 

  • Liu X, et al. PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach. Nucleic Acids Res. 2010;38(Web Server issue):W609-14.

    Google Scholar 

  • Liu Z, et al. BATMAN-TCM: a bioinformatics analysis tool for molecular mechANism of traditional Chinese medicine. Sci Rep. 2016;6:21146.

    Article  CAS  Google Scholar 

  • Luo CH, et al. Natural medicines for the treatment of fatigue: bioactive components, pharmacology, and mechanisms. Pharmacol Res. 2019;148:104409.

    Article  CAS  Google Scholar 

  • Luo TT, et al. Network pharmacology in research of Chinese medicine formula: methodology, application and prospective. Chin J Integr Med. 2020;26(1):72–80.

    Article  CAS  Google Scholar 

  • Lyu M, et al. Network pharmacology exploration reveals endothelial inflammation as a common mechanism for stroke and coronary artery disease treatment of Danhong injection. Sci Rep. 2017;7

    Google Scholar 

  • Ma'ayan A. Complex systems biology. J R Soc Interface. 2017;14:134.

    Article  Google Scholar 

  • Naithani S, et al. Plant Reactome: a knowledgebase and resource for comparative pathway analysis. Nucleic Acids Res. 2020;48(D1):D1093–103.

    CAS  Google Scholar 

  • National Toxicology Program. National Toxicology Program. Annual Plan. Fiscal year 2001. Natl Toxicol Program Tech Rep Ser. 2002:1–86.

    Google Scholar 

  • Nickel J, et al. SuperPred: update on drug classification and target prediction. Nucleic Acids Res. 2014;42(Web Server issue):W26-31.

    Google Scholar 

  • Pang B, et al. Application of berberine on treating type 2 diabetes mellitus. Int J Endocrinol. 2015;2015:905749.

    Article  Google Scholar 

  • Pankov R, et al. Characterization of stitch adhesions: fibronectin-containing cell-cell contacts formed by fibroblasts. Exp Cell Res. 2019;384(1):111616.

    Article  CAS  Google Scholar 

  • Park CH, et al. Beneficial effect of 7-O-galloyl-D-sedoheptulose, a polyphenol isolated from Corni Fructus, against diabetes-induced alterations in kidney and adipose tissue of type 2 diabetic db/db mice. Evid Based Complement Alternat Med. 2013;2013:736856.

    Article  Google Scholar 

  • Pinero J, et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. 2017;45(D1):D833–9.

    Article  CAS  Google Scholar 

  • Qiu J. Traditional medicine—a culture in the balance. Nature. 2007;448(7150):126–8.

    Article  CAS  Google Scholar 

  • Rappaport N, et al. MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search. Nucleic Acids Res. 2017;45(D1):D877–87.

    Article  CAS  Google Scholar 

  • Rhee MY, et al. Effect of Korean red ginseng on arterial stiffness in subjects with hypertension. J Altern Complement Med. 2011;17(1):45–9.

    Article  Google Scholar 

  • Rodrigues S, et al. Intact perineum: what are the predictive factors in spontaneous vaginal birth? Mater Sociomed. 2019;31(1):25–30.

    Article  Google Scholar 

  • Ru J, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform. 2014;6:13.

    Article  Google Scholar 

  • Shannon P, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.

    Article  CAS  Google Scholar 

  • Skinnider MA, et al. PrInCE: an R/bioconductor package for protein-protein interaction network inference from co-fractionation mass spectrometry data. Bioinformatics. 2021;

    Google Scholar 

  • Sumalan RM, et al. Assessment of mint, basil, and lavender essential oil vapor-phase in antifungal protection and lemon fruit quality. Molecules. 2020;25:8.

    Article  Google Scholar 

  • Szklarczyk D, et al. STITCH 5: augmenting protein-chemical interaction networks with tissue and affinity data. Nucleic Acids Res. 2016;44(D1):D380-4.

    Article  Google Scholar 

  • Tao QY, et al. Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Huashi Baidu formula in the treatment of COVID-19. Drug Dev Ind Pharm. 2020;46(8):1345–53.

    Article  CAS  Google Scholar 

  • van Beers RJ, Brenner E, Smeets JB. Random walk of motor planning in task-irrelevant dimensions. J Neurophysiol. 2013;109(4):969–77.

    Article  Google Scholar 

  • Venkatesh RD, Dellon ES. This String's attached: the Esophageal string test for detecting disease activity in eosinophilic esophagitis. Gastroenterology. 2020;159(6):2244–5.

    Article  Google Scholar 

  • Weng XG, et al. Research initiative of new thought on "main effect" of TCM formulae—new thinking on mechanism of compound action and compatibility mechanism of Chinese herbal compound formulae. Zhongguo Zhong Yao Za Zhi. 2018;43(18):3782–6.

    Google Scholar 

  • Wishart DS, et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2018;46(D1):D1074–82.

    Article  CAS  Google Scholar 

  • Wolfgang GH, Johnson DE. Web resources for drug toxicity. Toxicology. 2002;173(1–2):67–74.

    Article  CAS  Google Scholar 

  • Wu L, et al. Prediction of multi-target of Aconiti lateralis radix Praeparata and its network pharmacology. Zhongguo Zhong Yao Za Zhi. 2011;36(21):2907–10.

    Google Scholar 

  • Yao ZJ, et al. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models. J Comput Aided Mol Des. 2016;30(5):413–24.

    Article  CAS  Google Scholar 

  • Yi YD, Chang IM. An overview of traditional Chinese herbal formulae and a proposal of a new code system for expressing the formula titles. Evid Based Complement Alternat Med. 2004;1(2):125–32.

    Article  Google Scholar 

  • Yu GH, et al. Network pharmacology-based strategy to investigate pharmacological mechanisms of Zuojinwan for treatment of gastritis. BMC Complement Altern Med. 2018;18

    Google Scholar 

  • Zhang B, Wang X, Li S. An integrative platform of TCM network pharmacology and its application on a herbal formula, Qing-Luo-Yin. Evid Based Complement Alternat Med. 2013;2013

    Google Scholar 

  • Zhang RZ, et al. TCM-mesh: the database and analytical system for network pharmacology analysis for TCM preparations. Sci Rep. 2017;7

    Google Scholar 

  • Zhang RZ, et al. Network pharmacology databases for traditional Chinese medicine: review and assessment. Front Pharmacol. 2019;10:123.

    Article  Google Scholar 

  • Zhang YQ, et al. Deciphering the pharmacological mechanism of the Chinese formula Huanglian-Jie-Du decoction in the treatment of ischemic stroke using a systems biology-based strategy. Acta Pharmacol Sin. 2015;36(6):724–33.

    Article  Google Scholar 

  • Zhou C, et al. A systems biology-based approach to uncovering molecular mechanisms underlying effects of traditional Chinese medicine Qingdai in chronic myelogenous Leukemia, involving integration of network pharmacology and molecular docking technology. Med Sci Monit. 2018;24:4305–16.

    Article  CAS  Google Scholar 

  • Zhou ZC, et al. Applications of network pharmacology in traditional Chinese medicine research. Evid Based Complement Alternat Med. 2020;2020

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pengshuo Yang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Yang, P. (2022). TCM Preparation Network Pharmacology Analysis. In: Ning, K. (eds) Traditional Chinese Medicine and Diseases. Translational Bioinformatics, vol 18. Springer, Singapore. https://doi.org/10.1007/978-981-19-4771-1_7

Download citation

Publish with us

Policies and ethics