Combined Network Pharmacology and Molecular Docking to Verify the Treatment of Type 2 Diabetes with <i>Pueraria Lobata Radix</i> and <i>Salviae Miltiorrhizae Radix</i>

Mao, Jingxin; Wang, Guowei; Yang, Lin; Tan, Lihong; Tian, Cheng; Tang, Lijing; Fang, Ling; Mu, Zhenqiang; Zhu, Zhaojing; Li, Yan

doi:https://doi.org/10.1155/2023/9150324

Computational and Mathematical Methods in Medicine

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusion Abbreviations Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Special Issue

Machine Learning and Network Methods for Biology and Medicine 2022

View this Special Issue

Research Article | Open Access

Volume 2023 | Article ID 9150324 | https://doi.org/10.1155/2023/9150324

Combined Network Pharmacology and Molecular Docking to Verify the Treatment of Type 2 Diabetes with Pueraria Lobata Radix and Salviae Miltiorrhizae Radix

Jingxin Mao,^1,2Guowei Wang,²Lin Yang,^1,3Lihong Tan,^1,3Cheng Tian,^1,3Lijing Tang,^1,3Ling Fang,^1,3Zhenqiang Mu,^1,3Zhaojing Zhu ,^1,3and Yan Li^1,3

Academic Editor: Lei Chen

Received05 Oct 2022

Revised27 Oct 2022

Accepted24 Nov 2022

Published11 Feb 2023

Abstract

Objective. To explore the potential molecular mechanism of Pueraria Lobata Radix (RP) and Salviae Miltiorrhizae Radix (RS) in the treatment of type 2 diabetes mellitus (T2DM) based on network pharmacology and molecular docking. Methods. The chemical constituents and core targets of RP and RS were searched by Traditional Chinese Medicine System Pharmacology (TCMSP); target genes related to T2DM were obtained through GeneCards database, component target network diagram was constructed, intersection genes of active compounds and T2DM were synthesized, protein-protein interaction (PPI) relationship was obtained, and core targets were screened by using Cytoscape 3.7.2. Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were analyzed utilizing R studio 4.0.4 according to David database. Based on molecular docking, the screened active components of RP and RS were verified by molecular docking with the core target using Discovery Studio 2019. Results. There were totally 92 components and 29 corresponding targets in the component target network of RP and RS drug pair, of which 6 were the core targets of RP and RS in the treatment of T2DM. Molecular docking results showed that the active compounds of puerarin, formononetin, tanshinone iia, and luteolin had better binding activity with AKT1, VEGFA, NOS3, PPARG, MMP9, and VCAM1, respectively. Among them, puerarin showed significant effects in activating NOS3 pathway and luteolin exhibited significant effects in activating MMP9 pathway, respectively. The main biological processes mainly including xenobiotic stimulus, response to peptide, gland development, response to radiation, cellular response to chemical stress, response to oxygen levels, and the main signal pathways include response to xenobiotic stimulus, cellular response to chemical stress, response to peptide, gland development, and response to oxygen levels. Conclusion. Network pharmacology is an effective tool to explain the action mechanism of Traditional Chinese Medicine (TCM) from the overall perspective. RP and RS pair could alleviate T2DM via the molecular mechanism predicted by the network pharmacology, which provided new ideas and further research on the molecular mechanism of T2DM.

1. Introduction

Diabetes mellitus (DM) is a group of metabolic diseases characterized by increased blood glucose due to genetic and environmental effects, resulting in defective insulin secretion and reduced sensitivity of target cells to insulin. Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, mainly associated with the accumulation of lipids in the insulin β-cells can lead to elevated blood glucose levels and abnormal glucose tolerance due to the dysfunction of the pancreatic β-cells, and the clinical symptoms are persistent hyperglycemia. In recent decades, the prevalence of T2DM has gradually increased worldwide. The prevalence of DM in the world has increased by 102.9% from 1990 to 2010 and is the country with the largest number of diabetic patients in the world [1]. T2DM is a common clinical endocrine and metabolic disease, and the prevalence of DM in Chinese population is about 11.6%, and the prevalence of pre-DM is 50.1% [2], which is a chronic metabolic disease that seriously affects human health.

The important cause of T2DM is the disorder of lipid metabolism, therefore, it is especially important to control blood sugar and regulate blood lipid in the process of T2DM treatment in time [3]. At present, the main methods of T2DM drug treatment are subcutaneous insulin injection and oral hypoglycemic drugs (such as double pulse, sulfonyl artery, and a glyoxylase inhibitors); but with the development of the diseas

e, single-target development of drugs is difficult to treat T2DM and prevent the occurrence of complications such as glucose disorders and gastrointestinal tract, thus reducing the quality of life of patients [4].

Traditional Chinese Medicine (TCM) treatment of T2DM is based on single-target superposition and, multicomponent and multitarget synergistic toxicity dispersion effect to achieve better efficacy and lower toxicity group, which is a complex theoretical system to achieve multidimensional regulation from a whole [5]. DM belongs to the category of “thirst disorders” in TCM, and the main treatment of DM in TCM is to clear heat and moisten dryness, and to nourish yin and produce fluid [6]. After the TCM, doctors have formulated prescriptions according to the above treatment rules, the overall regulating advantages of TCM, which can play a role in treating both the symptoms and the root cause, and TCM is milder and more durable than western medicine, with fewer side effects [7].

Pueraria Lobata Radix (RP) and Salviae Miltiorrhizae Radix (RS) are a common pair of medicine contained in the famous Chinese medicine book “Shi Jinmo on Medicine.” RP is the dried root of Pueraria lobata (Willd.) Ohwi, which has the functions of quenching thirst, raising yang, relieving diarrhea, relieving muscle and fever, and activating meridians [8]. RS is also called “DanShen” that derived from the dried root and rhizome of Salvia miltiorrhiza Bunge, which has the effects of activating blood circulation, cooling the blood and clearing the heart, and removing irritation and calming the mind [9]. The combination of RP and RS exhibits the effect of promoting “qi,” resolving blood stasis, promoting blood circulation, and relieving pain, and the two are used as a pair to treat diabetes [10, 11]. Modern medicinal chemistry and pharmacology research shows that the main chemical components of RP are isoflavones, triterpenoids, flavonoids, coumarins, etc., which have pharmacological effects such as hypoglycemic and hypolipidemic, anti-inflammatory and antioxidant, and hepatoprotective [12]. The main chemical components of RS mainly including tanshinones, tanshin acids, and volatile oils, which have antioxidant, anti-inflammatory, and antithrombotic pharmacological effects [13].

Previous studies have been demonstrated that Pueraria Lobata Radix and Salviae Miltiorrhizae Radix (RP-RS) paired exhibits varies effects on T2DM or diabetes related diseases [10, 14–17]. However, the research on effective compounds of RP-RS is not in-depth, and the analytical methods are not comprehensive in these studies. Therefore, based on the idea of multicomponent and multitarget research, the present study was conducted to predict the mechanism of action and targets of RP-RS drug for the treatment of T2DM through network pharmacology and molecular docking methods, to find the active chemical components, disease therapeutic targets and signaling pathways, and to provide a scientific basis for the experimental research and clinical application of RP-RS drug for the treatment of T2DM.

2. Materials and Methods

2.1. Screening of RP and RS for Active Components and Potential Targets

The chemical components of RP and RS were obtained with the help of the Traditional Chinese Medicine System Pharmacology Analysis Platform (TCMSP, http://temspw.com/temsp.php), according to the set the bioavailability and drug-like properties , screening out eligible active ingredients and related targets.

2.2. T2DM-Related Target Prediction

Through the GeneCards (http://www.genecards.org/) database, with “Type 2 diabetes mellitus or T2DM” as the search term, the targets related to T2DM were obtained, and the correlation value (relevance ) was used as the screening condition, and the screening results were used as candidate target genes of T2DM.

2.3. Construction of Protein Interaction Network (PPI)

The effect of drugs on disease treatment is ultimately manifested in protein interactions. The Venn diagram (https://bioinfogp.cnb.csic.es/tools/venny/index.html) was used to obtain the intersection genes of the active ingredient target and the T2DM target, and imported into STRING11.0 (http://www.string-db.org/) to obtain the protein interaction relationship. Using Cytoscape 3.7.2 draws the interaction network, analyzes the key targets by degree value, and constructs the interaction network of RP-RS in the treatment of T2DM.

2.4. Construction of Chemical Components-Target Network of TCM

The screened candidate compounds of RP-RS that predicted component target genes were imported into Cytoscape 3.7.2 software to construct a compound-target network, and the main active ingredients/components of RP and RS were analyzed, respectively, according to the degree value in the network.

2.5. Analysis of Biological Function and Pathway Enrichment of RP-RS Pair in the Treatment of T2DM

GO enrichment is a commonly used method for analysis of omic data, which is usually used to discover the enrichment degree of GO term in differential genes. Through GO enrichment analysis, the genes in the difference table can be classified according to their functions to achieve the purpose of annotation and classification of genes [18]. KEGG is a practical program database for understanding advanced functions and biological systems (such as cells, organisms, and ecosystems) from molecular level information, especially genome sequencing and other high-throughput experimental technologies generated from large molecular data sets. It can predict the role of PPI networks in various cell activities [19]. Based on the David database (https://david.ncifcrf.gov/), the targets of RP-RS for the treatment of T2DM were collected and imported into R studio 4.0.4 (The species was limited to “Human”). GO functional annotation and KEGG pathway enrichment analysis were performed on the intersection target genes of RP-RS and T2DM, respectively (). Potential targets were analyzed for biological process (BP), cellular component (CC), and molecular function (MF), and KEGG was used for pathway enrichment analysis of potential targets. To validate the anti-T2DM mechanism of RP-RS across the key targets and multiple pathways, the KEGG mapper functional analysis was used to mark the target genes on the pathway associated with T2DM.

2.6. Molecular Docking Prediction of Key Targets of Active Ingredient Intervention in the Treatment of T2DM by RP-RS

According to the analysis of network pharmacology results, molecular docking software was used to predict the key targets of RP-RS intervention on the main active components. The 3D structure of the compound was constructed using Chem 3D of ChemOffice software and saved in.mol2 format. Download the protein structure of the target from the PDB (https://www.rcsb.org/) database, use PyMOL 2.5 to perform protein and ligand separation, dehydrogenation, water addition, and other operations on the original PDB protein molecule, and use AutoDock 1.5.7 software. The above compound and protein formats were converted to pdbqt format using Discovery Studio 2019 software for molecular docking and mapping of compounds and core targets.

3. Results

3.1. Screening of Active Compounds from RP-RS

Taking OB and DL properties as screening criteria, qualified compounds were screened from TCMSP database. After setting the screening conditions, 7 and 85 chemical components of RP and RS were obtained, respectively (Table 1).

3.2. Intersection Genes of RP-RS with T2DM

By database analysis, 356, 159, and 99 targets were identified for T2DM, RP, and RS, respectively. The online Venn diagram analysis showed that there were 28 intersecting genes between the active ingredient target of RS and T2DM (Figure 1(a)), 10 intersecting genes between the active ingredient target of RP and T2DM (Figure 1(b)), and 8 intersecting genes among RP, RS, and T2DM (Figure 1(c)), which were the main potential targets of RP-RS for the treatment of T2DM.

(a)

(b)

(c)

3.3. Protein Interaction PPI Network Construction

In this study, we analyzed the interaction between the targets of RP and RS for the treatment of T2DM based on the STRING database, and constructed the target interaction network (Figures 2(a) and 2(b)) by importing compound-disease shared genes into STRING with the interaction confidence setting, medium confidence (0.4), and performed the network topology analysis. The top 6 nodes in the interaction network were AKT1 (26), VEGFA (25), NOS3 (24), PPARG (22), MMP9 (22), and VCAM1 (20), (Table 2, Figure 2(b)), which may play an important role in the treatment of T2DM with RS. These 6 key targets may play an important role in the treatment of T2DM with RP.

(a)

(b)

3.4. Compound-Target Interaction Network

The network diagram visually reflects the interaction between compounds and targets, the nodes represent compounds, and the edges represent the relationship between compounds and targets, which can reflect the synergistic superposition of multicomponent and multitarget in Chinese medicine. The top 4 compounds in terms of degree value were MOL000006-luteolin (degree ), MOL012297-puerarin (degree ), MOL07154-tanshinone iia (degree ), and MOL000392-formononetin (degree ), respectively (Table 3, Figure 3).

3.5. Core Target Pathway Analysis

A total of 2015 BPs, 68 CCs, and 171 MFs of key targets were obtained by GO functional annotation, respectively () (Figure 4). BP mainly involved response to xenobiotic stimulus, response to peptide, gland development, response to radiation, cellular response to chemical stress, response to oxygen levels, response to metal ion, response to decreased oxygen levels, response to hypoxia, and response to UV. CC is mainly membrane raft, membrane microdomain, transcription requlator complex, postsynaptic membrane, protein kinase compley, caveola, serine/threonine protein kinase complex, plasma membrane raft, cyclin-dependent protein kinase holoenzyme complex, and integral component of presynaptic membrane. MF mainly involves DNA-binding transcription factor binding, RNA polymerase I-specific DNA-binding transcription factor binding, ubiquitin-like protein ligase binding, ubiquitin protein ligase binding, phosphatase binding, kinase regulator activity, protein phosphatase binding, cyclin-dependent protein serine/threonine kinase regulator activity, G protein-coupled amine receptor activity, and G protein-coupled neurotransmitter receptor activity. The KEGG analysis results showed that a total of 136 signaling pathways were enriched (Figure 5), mainly related to response to xenobiotic stimulus, cellular response to chemical stress, response to peptide, gland development, response to oxygen levels, response to radiation, response to decreased oxygen levels, response to UV, response to metalion, response to hypoxia, response to reactive oxygen species, response to estradiol, response to oxidative stress, response to light stimulus, regulation of apoptotic signaling pathway, reproductive structure development, neuron death, reproductive system development, cellular response to oxidative stress, and cellular response to peptide. Based on the GO functional annotation and KEGG pathway enrichment analysis of these two main aspects, the RP-RS drug pair mainly treats T2DM through the synergistic effect of multiple pathways and multiple targets. Annotated map of the key target genes locations of RP-RS in T2DM-related pathways was presented in Figure 6. It was found that most of the key target genes are closely with AGE-RAGE signaling pathway in T2DM.

3.6. Molecular Docking Prediction of Key Targets for Active Ingredient Intervention in the Treatment of T2DM by RP-RS

The key targets predicted by network pharmacology were AKT1 (1H10), VEGFA (1BJ1), NOS3 (1M9J), PPARG (2VV4), MMP9 (1GKC), and VCAM1 (1VSC), respectively. Molecular docking results of the top 4 main active ingredients and 6 core targets are shown in Figure 7 and Table 4, respectively. The key targets were individually docked to the active compounds puerarin (Figure 8), formononetin (Figure 9), tanshinone iia (Figure 10), and luteolin (Figure 11). Using Discovery Studio 2019 software, the selected compounds were finally docked into the binding site by utilizing the LibDock modules. In addition, the docked pose with the highest LibDock Score was retained for each compound for the LibDock results. The results of molecular docking showed that MMP9 had the best binding energy (LibDock Score) to puerarin, formononetin, tanshinone iia, and luteolin (133.3540, 130.3760, 123.063, and 138.5800), VEGFA to puerarin, formononetin, tanshinone iia, and luteolin (117.1350, 90.4544, 77.7759, and 59.7402), AKT1 to puerarin, formononetin, tanshinone iia, and luteolin (79.3393, 53.2793, 61.7867, and 61.3038), NOS3 to puerarin, formononetin, and luteolin (141.9620, 115.5420, and 87.0491), VCAM1 to puerarin, formononetin, tanshinone iia, and luteolin (121.3260, 93.8531, 96.6147, and 100.627), and PPARG to formononetin and tanshinone iia (60.7435 and 87.5627), respectively, and the key targets were molecularly docked to the active compounds.

(a)

(b)

(c)

(d)

(e)

(a)

(b)

(c)

(d)

(e)

(f)

(a)

(b)

(c)

(d)

(e)

(a)

(b)

(c)

(d)

(e)

4. Discussion

Current research on T2DM has focused on several pathological alterations such as obesity-related insulin resistance and defective insulin secretion as well as decreased B-cell mass through B-cell apoptosis, and has a close association with inflammatory alterations, immune gene defects, and impaired mitochondrial function [20, 21]. In this way, the results of the network pharmacological analysis, i.e., the results of the potential mechanism of RP-RS for the treatment of T2DM and the results of the molecular docking of potential pharmacodynamic substances and key targets will be discussed.

In this study, a holistic analysis was performed using network pharmacology from multigene, multipassage, and multitarget, and 92 active ingredients of RP-RS for the treatment of T2DM were identified; the most important of which were puerarin, formononetin, tanshinone iia, and luteolin. The phytochemicals are estrogenically active polyphenolic nonsteroidal phytochemicals, which are commonly found in various plants. It has been shown that formononetin has therapeutic effects on diabetes, such as formononetin exhibited hypoglycemic effects in mice with tetraoxacillin-induced type 1 diabetes by inhibiting pancreatic β-cell apoptosis [22]. It was shown that formononetin significantly increased insulin sensitivity index, decreased HOMA-IR, and improved insulin resistance [23]. Puerarin, as its main active ingredient in the treatment of T2DM may participate in the whole process of inflammatory factor expression in type 2 diabetes patients, reduce the inflammatory response, regulate the body’s internal environment, and improve the state of insulin resistance and disorders of glucose and lipid metabolism, while the symptoms of type 2 diabetes can be improved [24]. It was reported that puerarin may also ameliorated streptozotocin (STZ) pancreatic injury in mice, upregulated insulin receptor substrate 1 and insulin-like growth factor protein expression in the pancreas, inhibited STZ-induced apoptosis of islet β-cells in diabetic mice, and increased serum insulin levels; and its protective effects on β-cells may be mediated by modulating the phosphatidylinositol 3-kinase/protein kinase B pathway, thereby exerting hypoglycemic effects and improving glucose tolerance [25]. In previous study, puerarin may also upregulated the gene expression of retinal vascular endothelial growth factor and hypoxia-inducible factor-1, which had a significant protective effect against STZ-induced diabetic retinopathy in rats, while VEGF, an angiogenic and vascular permeability factor, was significantly increased in the vitreous and aqueous fluids of eyes with proliferative diabetic retinopathy [26]. In addition, tanshinone iia has been reported to antagonize endothelial damage and antioxidant effects to effectively reduce diabetic nephropathy [27] and diabetic neuropathy [28]. Previous studies have shown that luteolin inhibits high-glucose-induced activation of NF-κB in human monocytes and the release of the proinflammatory factor TNF-α, with potential preventive and therapeutic activity in diabetes mellitus [29]. It was revealed that have a regulatory effect on endothelial cell function, and luteolin enhance insulin action in adipocytes by activating the PPAR pathway [30]. Recent studies have revealed the potential protective effect of luteolin on diabetes-related hypertension, which may significantly reduce diabetes-induced vascular complications and hypertension [31]. Therefore, these components of RP-RS may play an important role in the prevention and treatment of T2DM.

Core targets including AKT1, VEGFA, NOS3, PPARG, MMP9, and VCAM1 have been identified as important by network pharmacological analysis. AKT1 is involved in several regulatory processes, including glucose metabolism, and AKT mediates insulin signaling and interacts with the transcription factors PGC-1α and FoxO1 to stimulate gluconeogenic gene expression [32]. AKT is part of the insulin-signaling pathway that directly inhibits the expression of PGC-1α protein in hepatocytes [33]. This pathway is able to regulate lipid secretion in type 2 diabetes. Because of AKT-induced inhibition of PGC-1α leads to inhibition of fatty acid oxidation in the liver, promoting PGC-1α activity in insulin-resistant hepatocytes may be able to eliminate lipid imbalance in T2DM patients [34]. It was reported that VEGFA promotes angiogenesis, and abnormal levels of VEGFA expression can exacerbate pathological angiogenesis and the development of diabetic retinopathy [35]. It was shown that reduced local production of VEGFA in the glomeruli of diabetic mouse models promotes endothelial injury and accelerates the progression of glomerular injury. It suggests that upregulation of VEGFA in diabetic kidneys protects microvasculature from injury, while decreased VEGFA in diabetes may be detrimental [36]. The NOS3 gene is an important 21-22 kb long gene located in vascular endothelial cells and contains 26 exons and 25 introns [37]. It has been reported that endothelial cells produce more oxygen radicals and release large amounts of Ca²⁺ in the early stages of diabetes, which leads to increased intracellular flow and activation of NOS, causing more endothelial cells to be produced. The end effector molecule of B-cell damage is NO, and NO can cause apoptosis by inducing endoplasmic reticulum stress-related apoptotic factors, indirectly damaging islet cells, and affecting insulin synthesis, and the activity of NOS will be reduced in diabetic patients in the later stages, while plasma NO levels will be reduced [38]. PPARG, a member of the nuclear hormone receptor superfamily, which has an important role in controlling lipid and glucose metabolism as well as in T2DM development [39]. Previous studies have shown that high expression of PPARG levels in adipose tissue reduces plasma lipid levels, has a beneficial role in long-term glucolipid homeostasis, reduces the incidence of visceral adipose IR, and is involved in regulating the pathological process of T2DM in obese populations [40]. DM is not only a metabolic disorder, activation of innate immunity and inflammatory response play an important role in the development of diabetes and its onset. MMP9 is a vital effector molecule of inflammatory cells; it will act as a switch in acute and chronic inflammation and is presumptively concerned within the initial part of inflammation and later tissue remodeling [41]. Hyperglycemia promotes the production of proinflammatory cytokines TNF-α and IL-6 production, and the expression of these proinflammatory cytokines induces an increase in MMP9 expression in an autocrine and paracrine manner [42]. Studies have demonstrated that the level of MMP9 directly affects the development of diabetic nephropathy, a complication of diabetes, and that high glucose downregulates the expression of MMP9 protein, thereby affecting its proportional imbalance and also exacerbating the development of diabetic nephropathy [43]. VCAM1 is a cell adhesion molecule that is a member of the immunoglobulin superfamily, and Guillén-Gómez et al. found that urinary VCAM1 levels were significantly higher in DN patients compared to diabetic patients, which could be a marker of renal pathology in diabetic patients [44]. In addition, VCAM1 protein level was significantly correlated with T2DM complications. The enhanced induction of VCAM1 expression in endothelial cells by circulating factors may play a role in the development of atherosclerosis in diabetes [45].

Through GO functional annotation analysis of the intersection target genes, it was found that RP-RS may regulate T2DM through various BP, cellular composition CC and MF. The GO enrichment analysis showed that RP-RS exhibits efficacy mainly via xenobiotic stimulus, response to peptide, response to oxygen levels, membrane raft, membrane microdomain, transcription requlator complex, DNA-binding transcription factor binding, RNA polymerase I-specific DNA-binding transcription factor binding, ubiquitin-like protein ligase binding, etc. The KEGG pathway enrichment results revealed that a total of 136 signaling pathways were enriched, mainly related to response to xenobiotic stimulus, cellular response to chemical stress, response to peptide, gland development, response to oxygen levels, and so on. The results of molecular docking validation showed that the key components screened by network pharmacology showed stable binding to the core targets NOS3 and MMP9, among which, the docking scores of puerarin and NOS3 were the highest, followed by those of luteolin and MMP9, and the stronger the interaction, the more stable the conformation of the compounds, indicating that puerarin showed good effects in activating NOS3 and luteolin exhibited good effects in activating MMP9 pathways, respectively.

5. Conclusion

In conclusion, a total of 92 active ingredients of RP-RS were obtained. The active components of RP-RS mainly including puerarin, formononetin, tanshinone iia, and luteolin which are closely associated with T2DM. A total of 29 intersecting target genes was acquired between drugs (RP-RS) and diseases (T2DM). Among them, the core target genes in treatment of T2DM mainly including VEGFA, MMP9, AKT1, NOS3, VCAM1, and PPARG, respectively. In addition, puerarin showed significant anti-T2DM effects in activating NOS3 and luteolin exhibited significant anti-T2DM effects in activating MMP9 pathways, respectively. The biological function exhibits efficacy mainly via positive regulation of xenobiotic stimulus, response to peptide, response to oxygen levels, membrane raft, and membrane microdomain. The signaling pathways that exerting their therapeutic effect on T2DM mainly including response to xenobiotic stimulus, cellular response to chemical stress, response to peptide, gland development, and response to oxygen levels. From the perspective of modern molecular biology, it was confirmed that RP-RS has good therapeutic effect on T2DM, the multitarget and multipath effects of TCM may rely on its therapeutic characteristics.

Abbreviations

RP:	Pueraria Lobata Radix
RS:	Salviae Miltiorrhizae Radix
RP-RS:	Pueraria Lobata Radix (RP) and Salviae Miltiorrhizae Radix
T2DM:	Type 2 diabetes mellitus
TCMSP:	Traditional Chinese medicine system pharmacology
GO:	Gene Ontology
KEGG:	Kyoto Encyclopedia of Genes and Genomes
PPI:	Protein-protein interaction
TCM:	Traditional Chinese medicine
DM:	Diabetes mellitus
OB:	Bioavailability
DL:	Drug-like properties
BP:	Biological process
CC:	Cellular component
MF:	Molecular function
STZ:	Streptozotocin.

Data Availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Conflicts of Interest

All authors declare that there have no any commercial or associative interest that represents competing interests in connection with the work submitted.

Authors’ Contributions

YanLi and Zhaojing Zhu conceived and designed the research. Jingxin Mao, Guowei Wang, Lin Yang, Lihong Tan, and Cheng Tian carried out the data analysis and wrote the paper in the study. Jingxin Mao, Yan Li, Lijing Tang, and Zhenqiang Mu finished the drawing and manuscript revision work. Yan Li and Zhaojing Zhu contributed equally to the manuscript. Jingxin Mao and Guowei Wang contributed equally to this work.

Acknowledgments

This work was supported by the General Program of Chongqing Natural Science Foundation (No. cstc2021jcyjmsxmX0452), the Scientific Research and Seedling Breeding Project of Chongqing Medical Biotechnology Association (cmba2022kyym-zkxmQ0003), the Project of Science and Technology Research Program of Chongqing Education Commission of China (No. KJQN202002801), the Talent introduction project of Chongqing Medical and Pharmaceutical College (No. ygz2022101), and the 2020 Ministerial Project of China (No. 2020YYCXCQSJ050), respectively.

References

J. Liu, Z. H. Ren, H. Qiang et al., “Trends in the incidence of diabetes mellitus: results from the global burden of disease study 2017 and implications for diabetes mellitus prevention,” BMC Public Health, vol. 20, no. 1, pp. 1–12, 2020.
View at: Publisher Site | Google Scholar
G. Ning, W. Zhao, and W. Wang, “Prevalence and control of diabetes in Chinese adults,” JAMA, vol. 310, no. 9, pp. 948–959, 2013.
View at: Publisher Site | Google Scholar
R. A. DeFronzo, E. Ferrannini, L. Groop et al., “Type 2 diabetes mellitus,” Nature Reviews Disease primers, vol. 1, no. 1, pp. 1–22, 2015.
View at: Publisher Site | Google Scholar
F. Petrak, S. Herpertz, E. Stridde, and A. Pfützner, “Psychological insulin resistance in type 2 diabetes patients regarding oral antidiabetes treatment, subcutaneous insulin injections, or inhaled insulin,” Diabetes Technology & Therapeutics, vol. 15, no. 8, pp. 702–710, 2013.
View at: Publisher Site | Google Scholar
E. Xiao and L. Luo, “Alternative therapies for diabetes: a comparison of western and traditional Chinese medicine (TCM) approaches,” Current Diabetes Reviews, vol. 14, no. 6, pp. 487–496, 2018.
View at: Publisher Site | Google Scholar
H. Zhang, C. Tan, H. Wang, S. Xue, and M. Wang, “Study on the history of traditional Chinese medicine to treat diabetes,” European Journal of Integrative Medicine, vol. 2, no. 1, pp. 41–46, 2010.
View at: Publisher Site | Google Scholar
W.. Feng, H. Ao, C. Peng, and D. Yan, “Gut microbiota, a new frontier to understand traditional Chinese medicines,” Pharmacological Research, vol. 142, pp. 176–191, 2019.
View at: Publisher Site | Google Scholar
L. Yang, J. Chen, H. Lu et al., “Pueraria lobata for diabetes mellitus: past, present and future,” The American Journal of Chinese Medicine, vol. 47, no. 7, pp. 1419–1444, 2019.
View at: Publisher Site | Google Scholar
S. U. Chun-Yan, M. I. N. G. Qian-Liang, K. Rahman, H. A. N. Ting, and Q. I. N. Lu-Ping, “Salvia miltiorrhiza : traditional medicinal uses, chemistry, and pharmacology,” Chinese Journal of Natural Medicines, vol. 13, no. 3, pp. 163–182, 2015.
View at: Publisher Site | Google Scholar
W. Niu, J. Miao, X. Li, Q. Guo, Z. Deng, and L. Wu, “Metabolomics combined with systematic pharmacology reveals the therapeutic effects of Salvia miltiorrhiza and Radix Pueraria lobata herb pair on type 2 diabetes rats,” Journal of Functional Foods, vol. 89, article 104950, 2022.
View at: Publisher Site | Google Scholar
W. Zhao, Y. Yuan, H. Zhao, Y. Han, and X. Chen, “Aqueous extract of Salvia miltiorrhiza Bunge-Radix Puerariae herb pair ameliorates diabetic vascular injury by inhibiting oxidative stress in streptozotocin-induced diabetic rats,” Food and Chemical Toxicology, vol. 129, pp. 97–107, 2019.
View at: Publisher Site | Google Scholar
Z. Zhang, T. N. Lam, and Z. Zuo, “Radix Puerariae: an overview of its chemistry, pharmacology, pharmacokinetics, and clinical use,” The Journal of Clinical Pharmacology, vol. 53, no. 8, pp. 787–811, 2013.
View at: Publisher Site | Google Scholar
H. Pang, L. Wu, Y. Tang, G. Zhou, C. Qu, and J. A. Duan, “Chemical analysis of the herbal medicine Salviae miltiorrhizae radix et Rhizoma (Danshen),” Molecules, vol. 21, no. 1, p. 51, 2016.
View at: Publisher Site | Google Scholar
L. Ni, X. Chen, X. Gong et al., “Patent information analysis of TCM prescription for the treatment of diabetes based on patent analysis and SWOT model,” Phytomedicine Plus, vol. 2, no. 3, article 100307, 2022.
View at: Publisher Site | Google Scholar
D. W. S. Cheung, C. M. Koon, C. F. Ng et al., “The roots of Salvia miltiorrhiza (Danshen) and Pueraria lobata (Gegen) inhibit atherogenic events: A study of the combination effects of the 2-herb formula,” Journal of Ethnopharmacology, vol. 143, no. 3, pp. 859–866, 2012.
View at: Publisher Site | Google Scholar
P. Hao, F. Jiang, J. Cheng, L. Ma, Y. Zhang, and Y. Zhao, “Traditional Chinese medicine for cardiovascular disease: evidence and potential mechanisms,” Journal of the American College of Cardiology, vol. 69, no. 24, pp. 2952–2966, 2017.
View at: Publisher Site | Google Scholar
J. O. Kim, K. S. Kim, G. D. Lee, and J. H. Kwon, “Antihyperglycemic and antioxidative effects of new herbal formula in streptozotocin-induced diabetic rats,” Journal of Medicinal Food, vol. 12, no. 4, pp. 728–735, 2009.
View at: Publisher Site | Google Scholar
J. Zhang, Z. Xing, M. Ma et al., “Gene ontology and KEGG enrichment analyses of genes related to age-related macular degeneration,” BioMed Research International, vol. 2014, Article ID 450386, 10 pages, 2014.
View at: Publisher Site | Google Scholar
L. Chen, C. Chu, J. Lu, X. Kong, T. Huang, and Y. D. Cai, “Gene ontology and KEGG pathway enrichment analysis of a drug target-based classification system,” PLoS One, vol. 10, no. 5, article e0126492, 2015.
View at: Publisher Site | Google Scholar
M. S. H. Akash, K. Rehman, and S. Chen, “Role of inflammatory mechanisms in pathogenesis of type 2 diabetes mellitus,” Journal of Cellular Biochemistry, vol. 114, no. 3, pp. 525–531, 2013.
View at: Publisher Site | Google Scholar
F. H. J. Van Tienen, S. F. Praet, H. M. De Feyter et al., “Physical activity is the key determinant of skeletal muscle mitochondrial function in type 2 diabetes,” The Journal of Clinical Endocrinology & Metabolism, vol. 97, no. 9, pp. 3261–3269, 2012.
View at: Publisher Site | Google Scholar
G. Qiu, W. Tian, M. Huan, J. Chen, and H. Fu, “Formononetin exhibits anti-hyperglycemic activity in alloxan-induced type 1 diabetic mice,” Experimental Biology and Medicine, vol. 242, no. 2, pp. 223–230, 2017.
View at: Publisher Site | Google Scholar
M. J. Oza and Y. A. Kulkarni, “Formononetin treatment in type 2 diabetic rats reduces insulin resistance and hyperglycemia,” Frontiers in Pharmacology, vol. 9, p. 739, 2018.
View at: Publisher Site | Google Scholar
X. Pan, J. Wang, Y. Pu, J. Yao, and H. Wang, “Effect of puerarin on expression of ICAM-1 and TNF-α in kidneys of diabetic rats,” Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, vol. 21, pp. 2134–2140, 2015.
View at: Publisher Site | Google Scholar
Z. Li, Z. Shangguan, Y. Liu et al., “Puerarin protects pancreatic β-cell survival via PI3K/Akt signaling pathway,” Journal of Molecular Endocrinology, vol. 53, no. 1, pp. 71–79, 2014.
View at: Publisher Site | Google Scholar
L. N. Hao, M. Wang, J. L. Ma, and T. Yang, “Puerarin decreases apoptosis of retinal pigment epithelial cells in diabetic rats by reducing peroxynitrite level and iNOS expression,” Acta Physiologica Sinica, vol. 64, no. 2, pp. 199–206, 2012.
View at: Google Scholar
G. Chen, X. Zhang, C. Li, Y. Lin, Y. Meng, and S. Tang, “Role of the TGFβ/p65 pathway in tanshinone IIA-treated HBZY-1 cells,” Molecular Medicine Reports, vol. 10, no. 5, pp. 2471–2476, 2014.
View at: Publisher Site | Google Scholar
Y. Liu, L. Wang, X. Li, C. Lv, D. Feng, and Z. Luo, “Tanshinone IIA improves impaired nerve functions in experimental diabetic rats,” Biochemical and Biophysical Research Communications, vol. 399, no. 1, pp. 49–54, 2010.
View at: Publisher Site | Google Scholar
H. J. Kim, W. Lee, and J. M. Yun, “Luteolin inhibits hyperglycemia-induced proinflammatory cytokine production and its epigenetic mechanism in human monocytes,” Phytotherapy Research, vol. 28, no. 9, pp. 1383–1391, 2014.
View at: Publisher Site | Google Scholar
A. C. Puhl, A. Bernardes, R. L. Silveira et al., “Mode of peroxisome proliferator-activated receptor γ activation by luteolin,” Molecular Pharmacology, vol. 81, no. 6, pp. 788–799, 2012.
View at: Publisher Site | Google Scholar
R. Sangeetha, “Luteolin in the management of type 2 diabetes mellitus,” Current Research in Nutrition and Food Science Journal, vol. 7, no. 2, pp. 393–398, 2019.
View at: Publisher Site | Google Scholar
F. S. Eshaghi, H. Ghazizadeh, S. Kazami-Nooreini et al., “Association of a genetic variant in AKT1 gene with features of the metabolic syndrome,” Genes & Diseases, vol. 6, no. 3, pp. 290–295, 2019.
View at: Publisher Site | Google Scholar
R. L. Tuttle, N. S. Gill, W. Pugh et al., “Regulation of pancreatic β-cell growth and survival by the serine/threonine protein kinase Akt1/PKBα,” Nature Medicine, vol. 7, no. 10, pp. 1133–1137, 2001.
View at: Publisher Site | Google Scholar
H. Wang, Y. Bei, Y. Lu et al., “Exercise prevents cardiac injury and improves mitochondrial biogenesis in advanced diabetic cardiomyopathy with PGC-1α and Akt activation,” Cellular Physiology and Biochemistry, vol. 35, no. 6, pp. 2159–2168, 2015.
View at: Publisher Site | Google Scholar
N. Sellami, L. B. Lamine, A. Turki, S. Sarray, M. Jailani, and A. K. Al-Ansari, “Association of VEGFA variants with altered VEGF secretion and type 2 diabetes: a case-control study,” Cytokine, vol. 106, pp. 29–34, 2018.
View at: Publisher Site | Google Scholar
G. A. Sivaskandarajah, M. Jeansson, Y. Maezawa, V. Eremina, H. J. Baelde, and S. E. Quaggin, “Vegfa protects the glomerular microvasculature in diabetes,” Diabetes, vol. 61, no. 11, pp. 2958–2966, 2012.
View at: Publisher Site | Google Scholar
F. Chen, Y. M. Li, L. Q. Yang, C. G. Zhong, and Z. X. Zhuang, “Association of NOS2 and NOS3 gene polymorphisms with susceptibility to type 2 diabetes mellitus and diabetic nephropathy in the Chinese Han population,” IUBMB Life, vol. 68, no. 7, pp. 516–525, 2016.
View at: Publisher Site | Google Scholar
M. J. Yahya, P. B. Ismail, N. B. Nordin et al., “CNDP1, NOS3, and MnSOD polymorphisms as risk factors for diabetic nephropathy among type 2 diabetic patients in Malaysia,” Journal of Nutrition and Metabolism, vol. 2019, Article ID 8736215, 13 pages, 2019.
View at: Publisher Site | Google Scholar
N. Sarhangi, F. Sharifi, L. Hashemian et al., “PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis,” Scientific Reports, vol. 10, no. 1, article 12764, 2020.
View at: Publisher Site | Google Scholar
G. Abreu-Vieira, A. W. Fischer, C. Mattsson et al., “Cidea improves the metabolic profile through expansion of adipose tissue,” Nature Communications, vol. 6, no. 1, p. 7433, 2015.
View at: Publisher Site | Google Scholar
M. Chadzinska, P. Baginski, E. Kolaczkowska, H. F. Savelkoul, and B. M. Lidy Verburg-van Kemenade, “Expression profiles of matrix metalloproteinase 9 in teleost fish provide evidence for its active role in initiation and resolution of inflammation,” Immunology, vol. 125, no. 4, pp. 601–610, 2008.
View at: Publisher Site | Google Scholar
D. Min, J. G. Lyons, J. Bonner, S. M. Twigg, D. K. Yue, and S. V. McLennan, “Mesangial cell-derived factors alter monocyte activation and function through inflammatory pathways: possible pathogenic role in diabetic nephropathy,” American Journal of Physiology-Renal Physiology, vol. 297, no. 5, pp. F1229–F1237, 2009.
View at: Publisher Site | Google Scholar
A. Kaminari, E. C. Tsilibary, and A. Tzinia, “A new perspective in utilizing MMP-9 as a therapeutic target for Alzheimer’s disease and type 2 diabetes mellitus,” Journal of Alzheimer's Disease, vol. 64, no. 1, pp. 1–16, 2018.
View at: Publisher Site | Google Scholar
E. Guillén-Gómez, B. Bardají-de-Quixano, S. Ferrer et al., “Urinary proteome analysis identified neprilysin and VCAM as proteins involved in diabetic nephropathy,” Journal of Diabetes Research, vol. 2018, Article ID 6165303, 12 pages, 2018.
View at: Publisher Site | Google Scholar
M. M. Fadel, F. R. A. Ghaffar, S. K. Zwain, and H. M. Ibrahim, “Serum netrin and VCAM-1 as biomarker for Egyptian patients with type IΙ diabetes mellitus,” Biochemistry and Biophysics Reports, vol. 27, article 101045, 2021.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2023 Jingxin Mao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

786

Downloads

639

Citations