journal article·2024-07-01Open access

The construction and theoretical investigation of compound-protein target-pathway network for Radix Pueraria

Xueyan Zhang, Yunhua Li, Bin Xie, Fei Chen

AIP Advances· Volume 14· Issue 7

Abstract

The complex network approach is an effective method to analyze the global properties of complex biological systems, which can be used to explore the interactions between multiple compounds and protein targets of drug. Radix Pueraria has a long history of efficacy in different diseases, containing a variety of compounds that can produce multiple therapeutic effects via multiple targets. To explore the interrelationship between compounds of Radix Pueraria, protein targets, and pathways, the present investigation used the complex network approach to construct the compound-protein target-pathway network of Radix Pueraria. The analysis of the statistical and topological characteristics shows that the network has small-world and scale-free characteristics. The diameter of the network is 7, indicating that the information exchange between two nodes could quickly spread to the whole network. With the rank of degree value and integrated centrality as identification indicators, by taking the threshold of integrated centrality as 0.70, a total of nine key hub nodes containing three active compounds, two protein targets, and four biological pathways were identified: genistein, daidzein, puerarin, MAPK3, MAPK1, hsa01100, hsa05200, hsa05417, and hsa05207. The network analysis suggests these key hub nodes should play an important role in the pharmacological action of Radix Pueraria. The results of this study provide useful information and knowledge for further exploring the pharmacological mechanism of Radix Pueraria in the course of disease treatment.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Computational Drug Discovery Methods · Bioinformatics and Genomic Networks · Alzheimer's disease research and treatments

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Physics, School of Physics and Astronomy, Yunnan University 1 , Kunming 650500, China

Institute of Solar Energy Engineering, Kunming University of Science and Technology 2 , Kunming 650500, China

Faculty of Chemical Engineering, Kunming University of Science and Technology 3 , Kunming 650500, China

Funding

National Natural Science Foundation of China · Ten Thousand Talent Plans for Young Top-Notch Talents of Yunnan Province

References (49)

Show source-provided references
1. Design of new traditional Chinese medicine herbal formulae for treatment of type 2 diabetes mellitus based on network pharmacology10.1016/s1875-5364(17)30065-1 ↗
2. ETCM: An encyclopaedia of traditional Chinese medicine10.1093/nar/gky987 ↗
3. TCM: Made in China10.1038/480s82a ↗
4. Anticancer properties of traditional Chinese medicine10.2174/1386207320666170116141818 ↗
5. Traditional Chinese medicine and immune regulation10.1007/s12016-012-8332-0 ↗
6. Identification of multiple constituents in the traditional Chinese medicine formula Sheng-Mai San and rat plasma after oral administration by HPLC–DAD–MS/MS10.1016/j.jpba.2010.11.034 ↗
7. Progress in diabetes research in China10.1111/j.1753-0407.2009.00037.x ↗
8. Pueraria lobata for diabetes mellitus: Past, present and future10.1142/s0192415x19500733 ↗
9. Collective dynamics of ‘small-world’ networks10.1038/30918 ↗
10. Emergence of scaling in random networks10.1126/science.286.5439.509 ↗
11. Exploring complex networks10.1038/35065725 ↗
12. The structure and function of complex networks10.1137/s003614450342480 ↗
13. The large-scale organization of metabolic networks10.1038/35036627 ↗
14. Network biology: Understanding the cell’s functional organization10.1038/nrg1272 ↗
15. A complex network analysis of hypertension-related genes10.1016/j.physa.2013.09.054 ↗
16. H. Wang , C.-Y.Xu, J.-B.Hu, and K.-F.Cao, “A complex network analysis of hypertension-related genes (Revised version),” arXiv:1601.07192 (2016).
17. Systems biology: A brief overview10.1126/science.1069492 ↗
18. An overview of data models for the analysis of biochemical pathways10.1093/bib/4.3.246 ↗
19. The network of non-coding RNAs and their molecular targets in breast cancer10.1186/s12943-020-01181-x ↗
20. Uncovering the gene regulatory network of type 2 diabetes through multi-omic data integration10.1186/s12967-022-03826-5 ↗
21. Identification of potential prognostic markers associated with lung metastasis in breast cancer by weighted gene co-expression network analysis10.3233/cbm-210199 ↗
22. Network pharmacology: The next paradigm in drug discovery10.1038/nchembio.118 ↗
23. Navigating traditional Chinese medicine network pharmacology and computational tools10.1155/2013/731969 ↗
24. A system-level investigation into the mechanisms of Chinese traditional medicine: Compound Danshen formula for cardiovascular disease treatment10.1371/journal.pone.0043918 ↗
25. Network-based approaches to explore complex biological systems towards network medicine10.3390/genes9090437 ↗
26. A novel strategy of profiling the mechanism of herbal medicines by combining network pharmacology with plasma concentration determination and affinity constant measurement10.1039/c6mb00500d ↗
27. Exploring the pharmacological mechanism of Yanghe Decoction on HER2-positive breast cancer by a network pharmacology approach10.1016/j.jep.2017.01.045 ↗
28. TCMSP: A database of systems pharmacology for drug discovery from herbal medicines10.1186/1758-2946-6-13 ↗
29. Systems approaches and polypharmacology for drug discovery from herbal medicines: An example using licorice10.1016/j.jep.2013.02.004 ↗
30. Using the bipartite human phenotype network to reveal pleiotropy and epistasis beyond the gene
31. KEGG: Kyoto encyclopedia of genes and genomes10.1093/nar/28.1.27 ↗
32. An improved index of centrality10.1002/bs.3830100205 ↗
33. A set of measures of centrality based on betweenness10.2307/3033543 ↗
34. Centrality in social networks: Conceptual clarification10.1016/0378-8733(78)90021-7 ↗
35. Effects of three flavonoids from an ancient traditional Chinese medicine Radix puerariae on geriatric diseases10.4103/bc.bc_13_18 ↗
36. Radix puerariae in the treatment of diabetic nephropathy: A network pharmacology analysis and experimental validation10.1515/chem-2022-0311 ↗
37. Genistein: A promising therapeutic agent for obesity and diabetes treatment10.1016/j.ejphar.2012.11.013 ↗
38. Genistein, a specific inhibitor of tyrosine-specific protein kinases10.1016/s0021-9258(18)45614-1 ↗
39. Daidzein: A review of pharmacological effects10.4314/ajtcam.v13i3.15 ↗
40. Daidzein promotes glucose uptake through glucose transporter 4 translocation to plasma membrane in L6 myocytes and improves glucose homeostasis in type 2 diabetic model mice10.1016/j.jnutbio.2013.09.012 ↗
41. Synergistic hypoglycemic effects of pumpkin polysaccharides and puerarin on type II diabetes mellitus mice10.3390/molecules24050955 ↗
42. Antihyperglycemic effect of puerarin in streptozotocin-induced diabetic rats10.1021/np0203887 ↗
43. Quantitative phosphoproteomics reveal cellular responses from caffeine, coumarin and quercetin in treated HepG2 cells10.1016/j.taap.2022.116110 ↗
44. A ceRNA network of BBOX1-AS1-hsa-miR-125b-5p/hsa-miR-125a-5p-CDKN2A shows prognostic value in cervical cancer10.1016/j.tjog.2020.12.006 ↗
45. Integration of network pharmacology and molecular docking to explore the molecular mechanism of cordycepin in the treatment of Alzheimer’s disease10.3389/fnagi.2022.1058780 ↗
46. Analysis of the multi-physiological and functional mechanism of wheat alkylresorcinols based on reverse molecular docking and network pharmacology10.1039/d2fo01438f ↗
47. Puerarin-tanshinone IIA suppresses atherosclerosis inflammatory plaque via targeting succinate/HIF-1α/IL-1β axis10.1016/j.jep.2023.116675 ↗
48. Studies on chemical composition of Pueraria lobata and its anti-tumor mechanism10.3390/molecules27217253 ↗
49. Molecular mechanism of Puerariae lobatae Radix in treatment of hepatocellular carcinoma based on network pharmacology10.19540/j.cnki.cjcmm.20200427.402 ↗