Research ArticleNetwork Pharmacology-Based Approach to Investigate theMechanisms of Mahai Capsules in the Treatment ofCardiovascular Diseases
Minjuan Shi,1 Bo Li,1 Qiuzhen Yuan,1 Xuefeng Gan,1 Xiao Ren,1 Shanshan Jiang,1
and Zhuo Liu 2
1Department of Pharmacy, Shaanxi Provincial Hospital of Traditional Chinese Medicine, Xi’an 710000, Shaanxi, China2Department of Pharmacy, Xi’an Children’s Hospital, Xi’an 710000, Shaanxi, China
Correspondence should be addressed to Zhuo Liu; [email protected]
Received 5 September 2019; Accepted 16 April 2020; Published 13 May 2020
Academic Editor: Armando Zarrelli
Copyright © 2020 Minjuan Shi et al. *is 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.
Background. Mahai capsules (MHC) have been deemed to be an effective herb combination for treatment of cardiovasculardiseases (CVD) development and improvement of the life quality of CVD patients. To systematically explore the mechanisms ofMHC in CVD, a network pharmacology approach mainly comprising target prediction, network construction, biological processand pathway analysis, and related diseases was adopted in this study. Methods. We collected the bioactive compounds andpotential targets of MHC through the TCMSP servers. Candidate targets related to CVD were collected from*erapeutic TargetsDatabase and PharmGkb database and analyzed using ClueGO plugin in Cytoscape. KEGG pathway was enriched and analyzedthrough the EnrichR platform, and protein-protein interaction networks were calculated by STRING platform. *e compound-target, target-disease, and compound-target-disease networks were constructed using Cytoscape. Results. A total of 303 targets ofthe 57 active ingredients in MHC were obtained. *e network analysis showed that PTGS2, PTGS1, HSP90, Scn1a, estrogenreceptor, calmodulin, and thrombin were identified as key targets of MHC in the treatment of CVD. *e functional enrichmentanalysis indicated that MHC probably produced the therapeutic effects against CVD by synergistically regulating many biologicalpathways, such as PI3K-Akt, TNF, HIF-1, FoxO, apoptosis, calcium, T-cell receptor, VEGF, and NF-kappa B signaling pathway.Conclusions. In summary, the analysis of the complete profile of the pharmacological properties, as well as the elucidation oftargets, networks, and pathways, can further illuminate that the underlying mechanisms of MHC in CVD might be stronglyassociated with its synergic regulation of inflammation, apoptosis, and immune function, and provide new clues for its futuredevelopment of therapeutic strategies and basic research.
1. Background
Cardiovascular diseases (CVD) are a class of the degener-ative chronic diseases such as atherosclerosis, heart failure,hypertensive, aneurysms, and thromboembolism [1]. CVDmarkedly impairs the quality of life of patients and has beenthe leading cause for morbidity and mortality. It has beenreported that CVD deprives more than 10 million humanlives each year, and the mortality is projected to be 23.6million in 2030 [2]. *e prevention and treatment of car-diovascular medicine have been dramatically progressed inthe past years. Currently, the major pharmacologic options
for CVD include angiotensin-converting enzyme inhibitors,sodium channel blockers, nitrate esters, and variousthrombolytic agents [3, 4]. However, as a result of thecomplicated pathogenesis involved in CVD, single targetedtherapies may not be sufficient and several certain inevitableside effects still exist. *e medical failures of some patientswith CVD might be due to the incomplete understanding ofthe complex underlying pathophysiology. With the enor-mous development of medical science, researchers graduallyfound that most diseases are usually caused by multipletargets instead of single gene. Hence, multicomponent drugsrepresented by traditional Chinese medicine (TCM), which
HindawiEvidence-Based Complementary and Alternative MedicineVolume 2020, Article ID 9180982, 15 pageshttps://doi.org/10.1155/2020/9180982
had been widely used in health maintenance, have drawnincreasing attention in CVD treatment [5]. TCM is a wholemedical system with rich practice experience for thousandsof years and has attracted a lot of attention in recent yearsbecause of valid treatment effects and fewer adverse reac-tions. *e treatment of complex diseases using TCM hasbeen considered as a complexity whole that confronts an-other whole, and it focuses on the state of the whole or-ganisms by regulating all the elements within the body [6].Based on the characteristics of multi-ingredients and mul-titargets feature, TCM treatment has enormous potential intreating chronic complex diseases including CVD.
In China, various TCM have achieved great success inthe prevention and treatment of CVD. Danshen drippingpills and Danhong injection are notable examples that wereconfirmed by clinical trials in their protective effects againstCVD [7–9]. Similarly, Mahai capsules (MHC) have beendeemed to be a crucial strategy for treatment of CVD de-velopment and improvement of the life quality of CVDpatients. MHC is an effective herb combination that consistsof HedysarumMultijugumMaxim (Huangqi, HQ), StrychniSemen (Maqianzi, MQ), Angelicae Sinensis Radix (Danggui,DG), Caulis Piperis Kadsurae (Haifengteng, HFT), Homa-lomena Occulta (Lour.) Schott (Qiannianjian, QN), andRadix Rhei Et Rhizome (Dahuang, DH). *is formula isapplied to inhibit CVD developments such as atheroscle-rosis, stroke, deep vein thrombosis, and cerebral infarction.An increasing number of clinical researches emphasize thepositive effect of HQ in treating CVD, for example, HQ, hasbeen proven to protect cardiovascular disease throughmultiple mechanisms, including anti-inflammatory andlipid lowering effects [10–12]. Several recent clinical studiesshowed that HQ can enhance myocardial contractility andmyocardial cell excitation-contraction coupling and gen-erate significant cardiotonic effect with the treatment ofacute myocardial infarction [13, 14]. Besides, the efficacy andsafety of HQ preparation in control of heart failure fromcardiac dysfunction and metabolic alterations have also beenproven [10]. DG has been widely used to treat blood defi-ciency disease in China, and the ameliorative effect of DGagainst heart injury and myocardial infarction has beenstudied [15, 16]. However, the complex active ingredientsand underlying mechanisms of MHC on CVD have not beenidentified, and it complicates the modernization and clinicalusage of MHC. *us, it is necessary to identify the bioactivesubstances of MHC and understand their synergistic actionsin and the exact effects on multiple targets.
Even though there was considerable benefit with suchmulticomponent drugs, understanding the scientific mate-rial basis and underlying mechanism of TCM herbal for-mulas are still required in the treatment of CVD at themolecular level and from a systematic perspective. Mostherbal medicines containing enormous bioactive com-pounds and lots of related multiple targets also complicatethe pharmacological research, making it difficult to clarifytheir pharmacological mechanism only by traditional ex-perimental approaches. With the rapid development of lifescience and computer science, various virtual screening toolsand bioinformatic database have been developed to explore
the interactions between the complex ingredients and thehuge amount of target genes in TCM [17, 18]. *e networkpharmacology-based approach provides guidance to in-vestigate potential pharmacological actions and clarifycomplex molecular mechanisms of TCM [19]. TraditionalChinese Medicine Systems Pharmacology (TCMSP),PharmMapper, and many databases have been developed topredict the validated and potential targets [20, 21]. Mean-while, there are several bioinformatic software and servers toanalysis the biological and mechanical properties of com-pound targets, such as David, String, EnrichR, andCytoscape.
In this paper, we aim to employ virtual screening da-tabases and integrate bioinformatics analyses to explore therelationships between MHC and targets, which show thenetwork of drug and related targets on whole level. *ismight enable us to investigate the pharmacological mech-anism of how MHC exerts the protective effects on CVD.
2. Methods
2.1. Screening of Active Components and PharmacokineticAbsorption,Distribution,Metabolism, andExcretion (ADME)Evaluation. Candidate compounds for Hedysarum Multi-jugum Maxim (Huangqi, HQ), Strychni Semen (Maqianzi,MQ), Angelicae Sinensis Radix (Danggui, DG), CaulisPiperis Kadsurae (Haifengteng, HF), Homalomena Occulta(Lour.) Schott (Qiannianjian, QN), and Radix Rhei EtRhizome (Dahuang, DH) were retrieved from the TCMSPdatabase (ref.). Identification of ADME (absorption, dis-tribution, metabolism, and excretion) properties by theTCMSP database was employed to screen the compositecompounds. In the current study, OB (prediction of oralbioavailability) and DL (prediction of drug-likeness) identifythe potential bioactive compounds of MHC.*e ingredientssatisfying the criteria of OB ≥30% and DL ≥0.18 are retainedand treated as candidate molecules of MHC for subsequentanalysis.
2.2. Identification of Candidate Compounds and TargetGenes. To gather information on interactions between ac-tive functional compounds in MHC and associated genes,the bioactive compounds and potential targets were collectedthrough the TCMSP servers. Known CVD-related targetswere collected from existing resources, including *erapeuticTargets Database and PharmGkb database, which providecomprehensive information on bioactive compounds andtargets interactions, and relationships among compounds,targets, and diseases. All obtained proteins were subjected toPharmGkb or TTD to detect the relationships betweencandidate molecules, targets, and CVD.
2.3. Network Construction and Analysis. To investigate re-lationship between the compounds inMHC and their targetsin CVD, we construct the network through network visu-alization software in Cytoscape 3.6.1. *is software was usedto integrate data and analysis and visualize complex inter-action networks. In networks, nodes represent compounds
2 Evidence-Based Complementary and Alternative Medicine
or proteins and edges indicate compound-target gene in-teractions. *ree types of networks, for example, com-pounds-targets (C-T), targets-diseases (T-D), andcompounds-targets-diseases (C-T-D) networks, were con-structed and visualized using Cytoscape. For nodes in thecomplex network, three indicators were calculated to revealits features.
2.4.GeneOntology (GO)Analysis. ClueGO, which is a pluginintegrated in Cytoscape, can be employed to conduct GOanalysis to create functionally organized term networks andcomprehensively visualize functionally grouped terms forunderstanding the biological significances [22]. *e p valuewas used to examine the significance of the GO terms en-richment. *e GO terms that have a p value of ≤0.05 wereregarded as significant and interesting.
2.5. Kyoto Encyclopedia of Genes and Genomes (KEGG)Pathway Analysis. Enrichr is an integrative web-basedplatform that includes new gene-set libraries, an alternativeapproach to rank enriched terms, and various interactivevisualization approaches to display enrichment results [23].*e KEGG pathway was enriched and ranked based uponthe combined score which is calculated by the EnrichRplatform. An adjusted p value threshold of 0.05 was used forpathway discovery. In this study, we chose the top ten KEGGterms to explore the related pathways.
2.6. Protein-Protein Interaction (PPI) Networks. String(https://string-db.org/) was employed to construct PPInetworks with the species limited to “homo sapiens” [24].String is a known platform and forecasts the interactions ofproteins, and it defines PPI with confidence ranges for datascores.
3. Results
3.1. 8e Candidate Compounds and Putative Target Proteins.Using in silico prescreening models, the main componentsof MHC with favorable pharmacokinetic characteristicswere determined. From the 444 native MHC compoundscollected from the TCMSP database, 75 candidate com-pounds were screened from the 6 herbs by ADME andprepared for further study as the candidate compounds asshown in Table 1.
We compared the 303 putative target proteins forcommonality and properties, and the results are shown inFigure 1(a).*e distribution of the biochemical classificationindicates that the target space mainly consists of tran-scription factor, receptor, nucleic acid binding, hydrolase,oxidoreductase, transferase, enzyme modulator, transporter,and signaling molecule. Remarkably, the obtained drugtargets are enriched in transcription factor (15.3%), receptor(14.4%), and nucleic acid binding (14%), highlighting thecritical roles of targets in drug discovery. Among the targets,32 targets are receptors, 21 are transferases, and 14 aretransporters (Figure 1(b)).
3.2. C-TNetworkAnalysis. To uncover the synergistic effectsof multicomponents and multitargets in MHC, a global viewof the C-T network was generated. After removing 18compounds with no target proteins, a graph of C-T inter-actions (Figure 1(a)) was constructed using 57 candidatecompounds and their 303 potential targets. *e averagenumber of targets per compound is 5.3, showing the mul-titarget features and polypharmacology properties of con-stituents in MHC. *e C-Tnetwork contains 360 nodes and1056 ligand-target interactions. For most active compounds,quercetin, beta-sitosterol, and stigmasterol have high degreedistributions, and each of them hits more than 90 potentialtargets. For instance, quercetin has the highest degree (154),followed by beta-sitosterol with 114 drug-target interactionsand stigmasterol possessing 93 target proteins.
By further observation of the C-Tnetwork, we found thatmany targets are hit by different numbers of compounds,implying the multicomponent characteristics of herbs.Among these targets, PTGS2 possesses the largest degree(degree� 40), followed by PTGS1 (degree� 31), HSP90(degree� 31), Scn1a (degree� 28), estrogen receptor(degree� 16), calmodulin (degree� 16), and thrombin(degree� 15), demonstrating their potential therapeuticeffects for treating CVD. Among them, the target prosta-glandin G/H synthase 2 (PTGS2) with the highest degree(40) and prostaglandin G/H synthase 1 (PTGS1) with adegree of 31 can be modulated by the compounds in MHC,indicating their vital role in helping to treat CVDs. Similarly,heat shock protein 90 (HSP90), a key enzyme in the bloodcoagulation system, was predicted to be regulated by 31chemicals. *e details of the relationship between activatecompounds and targets are described in Table S1. All theseresults imply the probably different binding properties ofactive chemicals in MHC with the active substances andsuggest that individual compounds may act on the sametargets synergistically, thus exerting therapeutic effects onCVDs.
3.3. T-D Network and C-T-D Network Analysis. To gainbetter insight into the diseases that could be modified byMHC, a T-D network was constructed on the strength ofpredicted targets and the corresponding diseases (Figure 2,Table S2). *e gene entries related to CVD were collectedfrom the TTD and PharmGkb database and converted intoUniProtKB IDs to determine the correlation between theputative target proteins and CVD. Targets with the mostdegrees among the 49 targets were as follows: thrombin,prostaglandin G/H synthase 2, eNOS, estrogen receptor, andβ-adrenergic receptor; the top diseases that were most rel-evant to MHC were as follows: atherosclerosis, cardiovas-cular disease, hypertension, thrombosis, andneurodegenerative diseases, implying that MHCmay be alsoeffective in the treatment of these diseases.*rombin, a maintarget ofMHC, was associated with coronary atherosclerosis,thrombosis, and thrombotic disease in the T-D network.Based on these findings, MHC contained numerous effectivesubstances with different pharmacologic properties that mayact on multiple targets with potential synergistic effects.
Evidence-Based Complementary and Alternative Medicine 3
Table 1: *e candidate compounds and putative target proteins of MHC.
Code Molecule name MW OB (%) DLM1 Mairin 456.78 55.38 0.78M2 Jaranol 314.31 50.83 0.29M3 Hederagenin 414.79 36.91 0.75
M4 (3S,8S,9S,10R,13R,14S,17R)-10,13-Dimethyl-17-[(2R,5S)-5-propan-2-yloctan-2-yl]-2,3,4,7,8,9,11,12,14,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol 428.82 36.23 0.78
M5 Isorhamnetin 316.28 49.6 0.31M6 3,9-Di-O-methylnissolin 314.36 53.74 0.48M7 5′-Hydroxyiso-muronulatol-2′,5′-di-O-glucoside 642.67 41.72 0.69M8 7-O-Methylisomucronulatol 316.38 74.69 0.3M9 9,10-Dimethoxypterocarpan-3-O-β-D-glucoside 462.49 36.74 0.92M10 (6aR,11aR)-9,10-Dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol 300.33 64.26 0.42M11 Bifendate 418.38 31.1 0.67M12 Formononetin 268.28 69.67 0.21M13 Isoflavanone 316.33 109.99 0.3M14 Calycosin 284.28 47.75 0.24M15 Kaempferol 286.25 41.88 0.24M16 FA 441.45 68.96 0.71M17 (3R)-3-(2-Hydroxy-3,4-dimethoxyphenyl)chroman-7-ol 302.35 67.67 0.26M18 Isomucronulatol-7,2′-di-O-glucosiole 626.67 49.28 0.62M19 1,7-Dihydroxy-3,9-dimethoxy pterocarpene 314.31 39.05 0.48M20 Quercetin 302.25 46.43 0.28M21 (2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one 272.27 42.36 0.21M22 (S)-stylopine 323.37 51.15 0.85M23 Ziziphin_qt 472.78 66.95 0.62M24 Icaride A 404.5 48.74 0.43M25 Isostrychnine N-oxide (I) 352.47 35.45 0.8M26 Isostrychnine N-oxide (II) 350.45 37.33 0.8M27 Lokundjoside_qt 406.57 32.82 0.76M28 Vomicine 408.54 47.56 0.65M29 Brucine-N-oxide 410.51 49.17 0.38M30 Isobrucine 334.45 33.58 0.8M31 Brucine N-oxide 410.51 52.63 0.38M32 Stigmasterol 412.77 43.83 0.76M33 (+)-Catechin 290.29 54.83 0.24M34 Beta-sitosterol 414.79 36.91 0.75M35 Stigmasterol 412.77 43.83 0.76M36 (2R,3R,3aS)-3a-Allyl-2-(1,3-benzodioxol-5-yl)-5-methoxy-3-methyl-2,3-dihydrobenzofuran-6-one 340.4 59.99 0.43M37 Denudatin B 356.45 61.47 0.38M38 Futokadsurin C 356.45 61.09 0.45M39 Galgravin 372.5 57.12 0.39M40 (2S,3S,4S,5S)-2,5-Bis(3,4-dimethoxyphenyl)-3,4-dimethyltetrahydrofuran 372.5 57.12 0.39M41 Hancinone 340.4 39.31 0.44M42 Isofutoquinol A 354.43 59.2 0.48
M43 (1R,5S,6R,7R,8R)-3-Allyl-6-(3,4-dimethoxyphenyl)-8-hydroxy-1-methoxy-7-methyl-4-bicyclo[3.2.1]oct-2-enone 358.47 64.65 0.35
M44 Bicyclo(3.2.1)oct-3-ene-2,8-dione, 7-(4-hydroxy-3-methoxyphenyl)-5-methoxy-6-methyl-3-(2-propenyl)-, (1R-(6-endo,7-exo))- 342.42 94.67 0.32
M45 Acetic acid [(1R,5S,6R,7R,8R)-3-allyl-6-(3,4-dimethoxyphenyl)-1-methoxy-7-methyl-4-oxo-8-bicyclo[3.2.1]oct-2-enyl] ester 400.51 59.93 0.46
M46 (2S,3S)-2-(3,4-Dimethoxyphenyl)-7-methoxy-3-methyl-2,3-dihydrobenzofuran-5-carbaldehyde 328.39 42.15 0.32
M47 Kadsurenone 356.45 54.72 0.38M48 Kadsurin A 372.45 56.83 0.5M49 Kadsurin B 358.47 30.55 0.46
M50 (4R)-2-Allyl-4-[(E)-2-(4-hydroxy-3-methoxyphenyl)-1-methylvinyl]-4,5-dimethoxy-1-cyclohexa-2,5-dienone 356.45 55.14 0.3
M51 Piperkadsin B 430.54 55.44 0.41M52 Piperlactam S 295.31 40.44 0.4M53 Stigmasterol 412.77 43.83 0.76M54 N-Coumaroyltyramine 283.35 85.63 0.2
4 Evidence-Based Complementary and Alternative Medicine
*en, we mapped all candidate compounds with theircorresponding targets onto these diseases. After discardingthe targets without participating in any related CVDS andthe corresponding compounds, a compounds-targets-dis-eases network was constructed with 87 nodes (13 com-pounds, 49 targets, and 25 diseases) and 127 edges(Figure 3). For instance, 3 compounds such as quercetin,isorhamnetin, and kaempferol are referred to as regulatingimportant targets in atherosclerosis; isorhamnetin, 3,9-di-O-methylnissolin, and stigmasterol are referred to as regulatingmain targets in hypertension; quercetin, Jaranol iso-rhamnetin, and (+)-catechin are referred to as regulating keytargets in neurodegenerative diseases. Our results suggestthat different ingredients of MHC may be involved in dif-ferent diseases.
3.4. GO Enrichment Analysis. To clarify the multiplemechanisms of MHC on CVD from a systematic level, weperformed an enrichment analysis for the biological process(BP), molecular function (MF), and cellular component (CC)of the retrieved protein targets ofMHC. As shown in Figure 4,the significantly enriched BP terms were mainly involved inregulation of apoptotic process, positive regulation of nucleicacid-templated transcription, cellular response to cytokinestimulus, cytokine-mediated signaling pathway, positiveregulation of transcription, DNA-templated positive regula-tion of intracellular signal transduction, positive regulation ofgene expression, positive regulation of transcription fromRNA polymerase II promoter, and positive regulation ofprotein phosphorylation. *e most frequently occurringprotein targets were TP53, IL-6, TGFB1, TNF, IKBKB, EGFR,CHUK, AKT1, RELLA, VEGFA, FOS, SIRT1, MYC, HIF1A,NKX3-1, STAT1, and IL-4.
Figure 5 lists the significantly enrichedMF terms of thesetargets. *e results suggested that targets of MHC were
strongly correlated with the molecular functions such asprotein binding, enzyme binding, receptor binding, identicalprotein binding, protein dimerization activity, G-proteincoupled amine receptor activity, signal transducer activity,binding, molecular transducer activity, protein hetero-dimerization activity, steroid hormone receptor activity,drug binding, and signaling receptor activity. As shown inFigure 6, the top five cellular components were plasmamembrane region (20.93%), extracellular space (13.95%),cytoplasmic part (12.4%), and membrane raft (11.63%).*ese abovementioned observations are valued in improvedunderstanding of the mechanism of MHC.
3.5. Pathway Enrichment Analysis. To investigate the un-derlying mechanism of MHC, the targets were furthermapped to pathways, and the top 10 pathways are listed inFigure 7. Among the 177 enriched pathways, severalpathways have been verified as important and accurate targetpathways for curing CVDs, such as AGE-RAGE signalingpathway in diabetic complications (hsa04933), PI3K-Aktsignaling pathway (hsa04151), TNF signaling pathway(hsa04668), HIF-1 signaling pathway (hsa04066), FoxOsignaling pathway (hsa04068), apoptosis (hsa04210), cal-cium signaling pathway (hsa04020), T-cell receptor signal-ing pathway (hsa04660), MAPK signaling pathway(hsa04010), Toll-like receptor signaling pathway (hsa04620),focal adhesion (hsa04510), NOD-like receptor signalingpathway (hsa04621), VEGF signaling pathway (hsa04370),and NF-kappa B signaling pathway (hsa04064). Amongthem, the PI3K-Akt and TNF signaling pathways have thehighest combined scores, which imply the vital roles in thetreatment and prevention of CVDs. In addition, 6 signalingpathways including HIF-1, FoxO, VEGF, TLR, MAPK, andNF-κB signaling pathways are also important pathwayscapable of regulating anti-inflammatory, neuroprotective,
Table 1: Continued.
Code Molecule name MW OB (%) DLM55 Wallichinine 370.48 61.64 0.33M56 Futoquinol 354.43 59.83 0.36M57 Beta-sitosterol 414.79 36.91 0.75M58 Acetylbullatantriol 298.47 40.21 0.18M59 Maristeminol 322.54 30.64 0.38M60 Eupatin 360.34 50.8 0.41M61 Mutatochrome 552.96 48.64 0.61M62 Physciondiglucoside 608.6 41.65 0.63M63 Procyanidin B-5,3′-O-gallate 730.67 31.99 0.32M64 Rhein 284.23 47.07 0.28M65 Sennoside E_qt 524.5 50.69 0.61M66 Torachrysone-8-O-beta-D-(6′-oxayl)-glucoside 480.46 43.02 0.74M67 Toralactone 272.27 46.46 0.24M68 Emodin-1-O-beta-D-glucopyranoside 432.41 44.81 0.8M69 Sennoside D_qt 524.5 61.06 0.61M70 Daucosterol_qt 386.73 35.89 0.7M71 Palmidin A 510.52 32.45 0.65M72 Beta-sitosterol 414.79 36.91 0.75M73 Aloe-emodin 270.25 83.38 0.24M74 Gallic acid-3-O-(6′-O-galloyl)-glucoside 484.4 30.25 0.67M75 (-)-Catechin 290.29 49.68 0.24
Evidence-Based Complementary and Alternative Medicine 5
and antioxidative effects. *is suggests that the potentialtargets of MHC may be involved in various pathways,showing their specific mechanism of action to modulateCVDs.
3.6. Protein-Protein Interactions. *e protein-protein net-work was constructed via mapping the putative targets intothe String platform. After excluding isolated nodes, theprotein interaction network induced by MHC was
Eukaryotic translation initiation factor Beta-1 adrenergic receptor
Kadsurin B
(-)-Catechin Beta-1 adrenergic receptorHepatocyte growth factor receptor
Poly [ADP-ribose] polymerase 1
Procollagen C-endopeptidase enhancer 1
Pro-epidermal growth factor
Probable E3 ubiquitin-protein ligase HERC5
Plasminogen activator inhibitor 1
Cellular tumor antigen p53
Heme oxygenase 1
Prostatic acid phosphatase
Stromelysin-1
Myeloperoxidase
G2/mitotic-specific cyclin-B1
G1/S-specific cyclin-D1
Protein CBFA2T1
NAD(P)H dehydrogenase [quinone] 1
Protein kinase C beta type
Puromycin-sensitive aminopeptidase
Collagen alpha-1(III) chain
Glutathione S-transferase Mu 2
RAF proto-oncogene serine/threonine-protein kinase
Glutathione S-transferase Mu 1
Heat shock protein beta-1
Proto-oncogene c-Fos
RAC-alpha serine/threonine-protein kinase
Apoptosis regulator Bcl-2
Tissue factor
�rombomodulin
Mitogen-activated protein kinase 1
Interferon regulatory factor 1
Tissue-type plasminogen activator
Baculoviral IAP repeat-containing protein 5
Cathepsin D
Maltase-glucoamylase, intestinal
Ornithine decarboxylase
Collagen alpha-1(I) chain
DNA gyrase subunit B
ETS domain-containing protein Elk-1
ATP-binding cassette sub-family G member 2
Maristeminol
Lokundjoside_qt
Bcl-2-like protein 1 DNA topoisomerase 1
DNA topoisomerase 2-alpha
Estrogen sulfotransferase CD40 ligand
Dual oxidase 2
Mineralocorticoid receptor
Peroxisome proliferator-activated receptor delta
Interferon gamma
Peroxisome proliferator-activated receptor gamma
Phosphatidylinositol-3,4,5-trisphosphate3-phosphatase and dual-specificity
protein phosphatase PTEN
72 kDa type IV collagenase
Activator of 90 kDa heat shock protein ATPase homolog 1
Acetyl-CoA carboxylase 1
Gap junction alpha-1 protein
Nitric-oxide synthase, endothelial
Interleukin-4
Amine oxidase [flavin-containing] B
isofutoquinol A
Transcription factor AP-1
Acetylcholinesterase
Neuronal acetylcholine receptor protein, alpha-7 chain
Cytochrome P450 1A2 Tumor necrosis factor
Myc proto-oncogene protein
Apoptosis regulator BAX
Brucine N-oxide
Alcohol dehydrogenase 1C
Brucine-N-oxide
mRNA of PKA Catalytic Subunit C-alpha
DNA topoisomerase II
Cell division control protein 2 homolog
Hyaluronan synthase 2
Acetylcholinesterase
Xanthine dehydrogenase/oxidase
Coagulation factor VII
1,7-Dihydroxy-3,9-dimethoxypterocarpene
Peroxisome proliferator activated receptor gamma
Sodium channel protein type 5 subunit alpha
Piperkadsin B
Isostrychnine N-oxide (I)
Transcription factor AP-1
Isostrychnine N-oxide (II)
Dopamine D1 receptor
Gamma-aminobutyric acid receptor subunit alpha-1
5-hydroxytryptamine 7 receptor
5-hydroxytryptamine 2A receptor
Alpha-1B adrenergic receptor
Neuronal acetylcholine receptor subunit alpha-2
Delta-type opioid receptor
Mu-type opioid receptor
6
Gamma-aminobutyric-acid receptor alpha-3 subunit
Isobrucine
Glycogen synthase kinase-3 beta
Serum paraoxonase/arylesterase 1
Serine/threonine-protein kinase Chk1
Cell division protein kinase 2
Estrogen receptor beta
Aldose reductase
Coagulation factor Xa
Beta-2 adrenergic receptor
Dipeptidyl peptidase IV
Rhein
Retinoic acid receptor RXR-alpha
acetic acid [(1R,5S,6R,7R,8R)-3-allyl-6-(3,4-dimethoxyphenyl)-1-methoxy-7-methyl-4-oxo-8-bicyclo[3.2.1]oct-2-enyl]
ester
Vascular endothelial growth factor receptor 2
Alpha-1A adrenergic receptor
EUPATIN
Wallichinine
Potassium voltage-gated channel subfamily H member 2
(2R,3R,3aS)-3a-Allyl-2-(1,3-benzodioxol-5-yl)-5-methoxy-3-methyl-2,3-dihydrobenzofuran-6-one
(3S,8S,9S,10R,13R,14S,17R)-10,13-dimethyl-17-[(2R,5S)-5-propan-2-yloctan-2-yl]-2,3,4,7,8,9,11,12,14,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol
Peroxisome proliferator activated receptor delta
Sodium channel protein type 5 subunit alpha
FA
Proto-oncogeneserine/threonine-protein kinase
Pim-1
Nuclear receptor coactivator 2
Carbonic anhydrase II
Prostaglandin G/H synthase 1
Prostaglandin G/H synthase 2
piperlactam S
Amine oxidase [flavin-containing] B
Mairin
5'-Hydroxyiso-muronulatol-2',5'-di-O-glucoside
Trypsin-1
Progesterone receptor
Daucosterol_qt
n-Coumaroyltyramine
Kadsurin A
Intercellular adhesion molecule 1
Nuclear receptor subfamily 1 group I member 2
Nuclear receptor subfamily 1 group I member 3
Solute carrier family 2, facilitated glucose transporter member 4
Cytochrome P450 1B1
Transcription factor p65
Inhibitor of nuclear factor kappa-B kinase subunit beta
Signal transducer and activator of transcription 1-alpha/beta
RAC-alpha serine/threonine-protein kinase
Cytochrome P450 1A1
Type I iodothyronine deiodinase
kaempferol
Cyclin-dependent kinase inhibitor 1
Torachrysone-8-O-beta-D-(6'-oxayl)-glucoside
Aldo-keto reductase family 1 member C3
isomucronulatol-7,2'-di-O-glucosiole
DNA topoisomerase II
Glutathione S-transferase Mu 2
Glutathione S-transferase Mu 1
Physciondiglucoside
Neutrophil cytosol factor 1
Mitogen-activated protein kinase 14
Oxidized low-density lipoprotein receptor 1
Glycogen phosphorylase, muscle form
mRNA of Protein-tyrosine phosphatase, non-receptor type 1
Peroxisome proliferator-activated receptor gamma
isorhamnetin
Proliferating cell nuclear antigen
Fatty acid synthase
Cellular tumor antigen p53
Interleukin-1 beta
Krueppel-like factor 7
Protein kinase C delta type G2/mitotic-specific cyclin-B1
Dipeptidyl peptidase IV
Protein kinase C epsilon type
Aloe-emodin
Antileukoproteinase
Serine/threonine-proteinphosphatase 2B catalytic subunit
alpha isoform
Heme oxygenase 1
Mitogen-activated protein kinase 8
Activator of 90 kDa heat Shock protein ATPase homolog 1
Peroxidase C1A
Tumor necrosis factor
Emodin-1-O-beta-D-glucopyranoside
Protein kinase C alpha type
Transforming growth factor beta-1
Caspase-8
Glutamate receptor 2
Caspase-9
Caspase-3cAMP-dependent protein kinase
inhibitor alpha
Peroxisome proliferator activated receptor delta
Nitric-oxide synthase, endothelial
Glycogen synthase kinase-3 beta Androgen receptor
Serine/threonine-protein kinase Chk1
Calycosin Estrogen receptor beta
Cyclin-A2Jaranol
Nuclear receptor coactivator 1
3,9-di-O-methylnissolinHeat shock protein HSP 90
Prostaglandin G/H synthase 2
Calmodulin
Prostaglandin G/H synthase 1
Kadsurenone
Futoquinol
Retinoic acid receptor RXR-beta
(2S,3S)-2-(3,4-dimethoxyphenyl)-7-methoxy-3-methyl-2,3-dihydrobenzofuran-5-carbaldehydeSodium-dependent serotonin
transporter
Calmodulin
Bifendate
Gamma-aminobutyric acid receptor subunit alpha-1
Delta-type opioid receptor
(2S,3S,4S,5S)-2,5-bis(3,4-dimethoxyphenyl)-3,4-dimethyltetrahydrofuran
�rombin
Icaride A
7-O-methylisomucronulatol
Estrogen receptor
Trypsin-1
Beta-2 adrenergic receptor
Beta-lactamase
Nitric oxide synthase, inducible
Calcium-activated potassium channel subunit alpha 1 Mitogen-activated protein kinase 14
Toralactone
Epidermal growth factor receptor Interleukin-2Solute carrier family 2, facilitated glucose transporter member 4 C-X-C motif chemokine 2 Matrix metalloproteinase-9 Interleukin-1 betaCyclin-dependent kinase inhibitor 1 quercetin
Interleukin-8Claudin-4 NADPH--cytochrome P450
reductaseTranscription factor E2F1 Transcription factor E2F2
Signal transducer and activator of transcription 1-alpha/beta Interleukin-1 alpha Interleukin-10Caveolin-1
Type I iodothyronine deiodinase
Insulin-like growth factor II Cyclin-dependent kinase inhibitor
2A, isoforms 1/2/3 Nitric oxide synthase, endothelial
Neutrophil cytosol factor 1
NF-kappa-B inhibitor alpha Transcription factor p65
Vascular endothelial growth factor A
Cytochrome P450 1B1
Superoxide dismutase [Cu-Zn]
Heat shock factor protein 1
C-X-C motif chemokine 11Receptor tyrosine-protein kinase erbB-3
Intercellular adhesion molecule 1 Retinoblastoma-associated protein
Insulin-like growth factor-binding protein 3
Leukotriene A-4 hydrolase
Nuclear receptor subfamily 1 group I member 2
Nuclear receptor subfamily 1 group I member 3
Cytochrome P450 1A1
DDB1- and CUL4-associated factor 5
Serine/threonine-protein kinase Chk2
Prostaglandin E2 receptor EP3 subtype
Interleukin-6
Peroxidase C1A Peroxisome proliferator-activated
receptor alpha
3 beta-hydroxysteroid dehydrogenase/Delta
5-->4-isomerase type 1
3 beta-hydroxysteroid dehydrogenase/Delta
5-->4-isomerase type 2
NADH-ubiquinone oxidoreductase chain 6
ATP synthase subunit beta, mitochondrial
NAD-dependent deacetylase sirtuin-1
formononetin
Ras association domain-containing protein 1
78 kDa glucose-regulated protein
Hexokinase-2
Nuclear factor erythroid 2-related factor 2
Receptor tyrosine-protein kinase erbB-2
Homeobox protein Nkx-3.1
Ras GTPase-activating protein 1
C-C motif chemokine 2
C-reactive protein
Runt-related transcription factor 2
Osteopontin
Hypoxia-inducible factor 1-alpha
C-X-C motif chemokine 10
Inhibitor of nuclear factor kappa-B kinase subunit alpha
Glutathione S-transferase P
Urokinase-type plasminogen activator
26S proteasome non-ATPase regulatory subunit 3
Aryl hydrocarbon receptor E-selectin
Cytochrome P450 3A4
Arachidonate 5-lipoxygenase
Insulin receptor
Vascular cell adhesion protein 1
Interstitial collagenase
Chymotrypsinogen B
Amine oxidase [flavin-containing] A
Alpha-2A adrenergic receptor
Stigmasterol
Apoptosis regulator BAX
Caspase-8
Transforming growth factor beta-1
Muscarinic acetylcholine receptor M2
Microtubule-associated protein 2
Muscarinic acetylcholine receptor M3
Caspase-9
Gamma-aminobutyric-acid receptor alpha-2 subunit
Beta-sitosterol
Lysozyme
Apoptosis regulator Bcl-2
Gamma-aminobutyric-acid receptor subunit alpha-6
Gamma-aminobutyric-acid receptor alpha-5 subunit
Alcohol dehydrogenase 1B
Glutamate receptor 2Hederagenin
Muscarinic acetylcholine receptor M4
Muscarinic acetylcholine receptor M3
Nicotinate-nucleotide--dimethylbenzimidazolephosphoribosyltransferaseCytochrome P450-cam
Mineralocorticoid receptor Sodium-dependent noradrenaline transporter
Progesterone receptor
Vomicine
Mu-type opioid receptor
Muscarinic acetylcholine receptor M4
Alpha-1B adrenergic receptor
Ig gamma-1 chain C region
Bicyclo(3.2.1)oct-3-ene-2,8-dione,7-(4-hydroxy-3-methoxyphenyl)-5-methoxy-6-methyl-3-(2-propenyl)-,
(1R-(6-endo,7-exo))-
Muscarinic acetylcholine receptor M2
Beta-secretase
Futokadsurin C
Retinoic acid receptor RXR-beta
Glucocorticoid receptor
mRNA of PKA Catalytic Subunit C-alpha
Caspase-3
Nuclear receptor coactivator 1Cytochrome P450-cam
Neuronal acetylcholine receptor protein, alpha-7 chain
CatalaseRetinoic acid receptor RXR-alpha
(2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
5-hydroxytryptamine 2A receptor5-hydroxytryptamine receptor 3A
Carbonic anhydrase II
Protein kinase C alpha type CGMP-inhibited 3',5'-cyclic phosphodiesterase A (S)-Stylopine
Sodium-dependent dopamine Transporter
Phosphatidylinositol-4,5-bisphosphate3-kinase catalytic subunit, gamma
isoformHeat shock protein HSP 90
Muscarinic acetylcholine receptor M5
Nuclear receptor coactivator 2
(1R,5S,6R,7R,8R)-3-Allyl-6-(3,4-dimethoxyphenyl)-8-hydroxy-1-methoxy-7-methyl-4-bicyclo[3.2.1]oct-2-enone
Alpha-1D adrenergic receptor
Alpha-2C adrenergic receptor
Muscarinic acetylcholine receptor M1
CGMP-inhibited 3',5'-cyclic Phosphodiesterase A
Galgravin
(6aR,11aR)-9,10-Dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol
(+)-catechin
(a)
Transcription factor (PC00218)Enzyme modulator (PC00095)Oxidoreductase (PC00176)
Receptor (PC00197)Transfer/carrier protein (PC00219)Signaling molecule (PC00207)Transferase (PC00220)
Isomerase (PC00135)Hydrolase (PC00121)Nucleic acid binding (PC00171)Transporter (PC00227)
Cell junction protein (PC00070)Calcium-binding protein (PC00060)Lyase (PC00144)Cytoskeletal protein (PC00085)
0 5 10 15 20 25 30 35Genes
Cate
gory
(b)
Figure 1: *e C-T network of MHC and the targets class. (a) *e compound in MHC and the potential target network. Different colorsrepresent the nodes with different attributions. Yellow nodes represent the candidate compounds; blue represent the predicted targets. (b)*e distribution of the candidate targets.
6 Evidence-Based Complementary and Alternative Medicine
NAD-dependentdeacetylase sirtuin-1
Coronary heart disease
Neurologicaldiseases
Amine oxidase [flavin-containing] B
Tissue-type plasminogen activator
CGMP-inhibited 3',5'-cyclic phosphodiesterase A
Peroxisome proliferator activated receptor delta
C-C motif chemokine 2
Transcription factor AP-1
Atherosclerosis
Peroxisome proliferator activated receptor gamma
Caveolin-1Acute coronary syndromes
Coronary artery disease
Vascularimpairment
associated with diabetes
Beta-1 adrenergic receptor
Mineralocorticoid receptor
Cardiac arrhythmias
Hypertension
Brain injury
Nitric-oxide synthase, endothelial
Neutrophil cytosol factor 1
Beta-2 adrenergic receptor
Catalase
Alpha-2A adrenergic receptor
Arachidonate 5-lipoxygenase Arterial embolism; �rombosis
5-hydroxytryptamine 2A receptor
Caspase-9
Potassium voltage-gated channel subfamily H member 2
Brain injury associated with seizures
Sodium channel protein type 5 subunit alpha
Cardiac dysrhythmias
Alpha-1D adrenergic receptor
Vasospasm
Prostaglandin G/H synthase 1
Cell division protein kinase 2
Mitogen-activated protein kinase 1
Caspase-8
Vascular injury response
Myeloperoxidase
Prostaglandin G/H synthase 2
Mitogen-activated protein kinase 14
Alzheimer's disease
Glycogen synthase kinase-3 betaHeme oxygenase 1
Vascular diseases
Cathepsin D
Acetylcholinesterase
Neuronal acetylcholine receptor protein, alpha-7 chain
Beta-secretase
�rombomodulin
Gamma-aminobutyric-acid receptor alpha-5 subunit
Interstitial collagenase
Vascular lesion regression
Interleukin-8Arthritis
Muscarinicacetylcholinereceptor M1Stromelysin-1
Leukotriene A-4 hydrolase
Muscarinicacetylcholinereceptor M2
Myocardial infarction
Coronary syndromesEstrogen receptor beta
Estrogen receptorCardiovascular disease
Serum paraoxonase/arylesterase 1
Neurodegenerative diseases
Tissue factor
�rombosis
�rombin
Coronary atherosclerosis
Coagulation factor Xa
�rombotic disease
Figure 2: T-D network: a potential targets-CVD network and nodes represent targets and diseases.
Heme oxygenase 1Catalase
Arachidonate5-lipoxygenase
Mitogen-activatedprotein kinase 1
Caspase-8 Peroxisome proliferator activated receptor gamma
Beta-1 adrenergic receptor
Interleukin-8C-C Motif chemokine 2
Stromelysin-1
Tissue factor
Caspase-9
Estrogen receptor
Interstitial collagenase
Prostaglandin G/H synthase 1
Alpha-1D adrenergic receptor
Muscarinicacetylcholine receptor
M1
Isorhamnetin
Jaranol
Kaempferol
7-O-Methylisomucronulatol
3,9-di-O-Methylnissolin
Hederagenin
Quercetin
Cell division protein kinase 2
Coagulation factor Xa
Alpha-2A adrenergic receptor
Formononetin
Myeloperoxidase
Neutrophil cytosol factor 1
Nitric-oxidesynthase, endothelial
Beta-2 adrenergic receptor
5-Hydroxytryptamine 2A receptor
Thrombomodulin
Caveolin-1
Gamma-aminobutyric-acidreceptor alpha-5 subunit
CGMP-inhibited3',5'-cyclic
phosphodiesterase A
Leukotriene A-4 hydrolase
Sodium channel protein type 5 subunit alpha
Peroxisome proliferator activated receptor delta
Mitogen-activatedprotein kinase 14
Cardiac dysrhythmias
Brain injury associated with seizures
ThrombosisNeurological diseases
Thrombotic diseaseVascular diseases Coronaryatherosclerosis
Brain injury
Serumparaoxonase/arylesterase
1
Glycogen synthase kinase-3 beta
Tissue-typeplasminogen activator
Cathepsin D
Muscarinicacetylcholine receptor
M2
Thrombin
Transcriptionfactor AP-1
Beta-secretase
Estrogen receptor beta
(+)-Catechin
Potassiumvoltage-gated channel
subfamily H member 2 Neuronal acetylcholine
receptor protein, alpha-7 chain
Prostaglandin G/H synthase 2
Mineralocorticoidreceptor
Acetylcholinesterase
Arthritis
(2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
Cardiovascular disease
Vascular injury response Neurodegenerativediseases
Vascular impairment associated with
diabetes
Myocardial infarction
Cardiac arrhythmiasAtherosclerosis
HypertensionArterial embolism; Thrombosis
Amine oxidase [flavin-containing] B
(6aR,11aR)-9,10-Dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol
Futokadsurin C
Vasospasm
Alzheimer's disease
Stigmasterol
Vascular lesion regression
Coronary arterydisease
NAD-dependentdeacetylase sirtuin-1 Coronary syndromes Coronary heart disease
Acute coronary syndromes
Figure 3: C-T-D network: a compounds-targets-CVD network and nodes represent compounds and targets.
Evidence-Based Complementary and Alternative Medicine 7
TGFB1
VEGFAAKT1EGFR
IL1B
BCL2L1IL1A
BCL2
IL6
RELA
SIRT1
TP53
MYC
IKBKB
IL10
IL4
TNF
ERBB2
NKX3-1STAT1
MMP9
MET
CHUK
CXCL10EGF
IRF1
NFKBIA
FOS
HIF1A
JUNNFE2L2
E2F1NCF1
HMOX1RUNX2
ELK1AHR
NCOA1AKR1B1
PPARG
Regulat
ion of..
Positive
reg..
Cellular
resp..
Cytokine-m
e..
Positive
reg..
Positive
reg..
Positive
reg..
Positive
reg..
Positive
reg..
Cellular
resp..
(a)
Regulation of apoptotic process(GO:0042981)
Positive regulation of nucleic acid-templated transcription…
Cellular response to cytokinestimulus (GO:0071345)
Cytokine-mediated signalingpathway (GO:0019221)
Positive regulation oftranscription, DNA-templated…
Positive regulation of intracellularsignal transduction (GO:1902533)
Positive regulation of geneexpression (GO:0010628)
Positive regulation oftranscription from RNA…
Positive regulation of proteinphosphorylation (GO:0001934)
Cellular response to oxidativestress (GO:0034599)Positive regulation of cell
proliferation (GO:0008284)
Apoptotic process (GO:0006915)
Positive regulation ofphosphorylation (GO:0042327)
Cellular response to reactiveoxygen species (GO:0034614)
Positive regulation ofmacromolecule metabolic…
Negative regulation ofprogrammed cell death…
Cellular response to cadmium ion(GO:0071276)
Positive regulation of cellularprocess (GO:0048522)
Negative regulation of apoptoticprocess (GO:0043066)
Protein kinase B signaling(GO:0043491)
0
10
20
30
40
50
60
Gene counts–log P (p-value)
(b)
Figure 4: *e GO BP analysis of predicted targets of MHC. EnrichR analysis was performed to identify the most significantly enriched GOBP terms.
8 Evidence-Based Complementary and Alternative Medicine
composed of 221 nodes (proteins) and 3865 edges (Figure 8).*e topological properties of the network rewired by theMHC were analyzed with the network analyzer plugin.Among these properties, the node degree can be used todistinguish between random and scale-free network topol-ogies.*ree topological features of each node in the networkwere calculated to find the major nodes. Finally, 22 nodeswere selected as major nodes, namely, TP53, JUN, AKT1,IL6, TNF, VEGFA, EGF, MAPK1, FOS, PIK3CG, MYC,BCL2, ESR1, EGFR, MAPK8, IL8, PTGS2, CASP3,HSP90AA1, MMP9, NOS3, and CCND1. *us, these targetswere likely to be the key or central proteins that MHC maydirectly act on them to treat CVDs.
4. Discussion
*e efficacy of MHC has been verified through accumulatedconsiderable clinical experiences. However, it is difficult toilluminate the mechanism of MHC from the perspective ofmodern medicine because of the complex composition. *enetwork pharmacological analysis provides new approachesand perspectives for the study of complicated Chinesemedicine formula. In the present study, we used the networkpharmacology approach to illuminate the scientific materialbasis and multiple underlying mechanisms of MHC inCVDs treatment from a systematic perspective. *e phar-macodynamic compounds and potential targets, networkanalysis of elements such as active ingredients and potentialtargets, GO and KEGG pathway enrichment analysis, andprotein-protein interaction were used to investigate therelationships between active molecules and related proteinsof CVD.
HQ, MQ, DG, HFT, QN, and DH are the most com-monly used herbal medicines to treat CVDs. In our work,
with the help of the ADME evaluation system, 444 activeingredients were identified, 75 of which could interact with303 direct targets by drug targeting. Recent researches haveshown that some active ingredients in MHC have biologicalactivity against CVDs, which confirm the bioinformaticsdata analyzed in our study and highlights the credibility ofthe network pharmacology system. For instance, iso-rhamnetin has been proven to exert cardiovascular pro-tective effects through multiple mechanisms, includingantioxidative, anti-inflammatory, and antiproliferative ef-fects. Various pharmacological studies showed that iso-rhamnetin protects against cardiac hypertrophy and canexhibit positive effect on hypoxia/reoxygenation-inducedinjury by attenuating apoptosis and oxidative stress [25, 26].Kaempferol can inhibit inflammatory responses and exertprotective effect in LPS-induced microvascular endothelialcells [27]. Besides, the protective effect of kaempferol onheart in isoproterenol-induced heart failure has also beenproven [28, 29]. Quercetin is a flavonoid that possessespharmacological effects including antitumor, antioxidant,anti-inflammatory, immunosuppressive, and cardiovascularprotection activities [30–34]. In a recent study, it has beenreported that the beta-sitosterol exerts thrombus-preventingactivity by dose-dependent inhibition of thrombin in mousemodel [35].
As we know, MHC probably exerts its therapeutic effecton CVD by binding and regulating particular protein targets.*e analytical result of the C-Tnetwork displayed an averagedegree of 13 per compounds and 5.3 per target proteins,respectively. Among the 57 compounds with correspondingtargets, 99 were capable of acting on more than 2 targets and44 linked with more than 13 target proteins. *e key nodeproteins were suggested to be important targets in thetreatment of CVD. Among them, the targets prostaglandin
Cell adhesion molecule binding
Ubiquitin-likeprotein ligase
bindingTranscription
coactivator activity
Ammonium ion binding
Proteinactivity
Identical protein binding
Protease binding
Heat shock protein binding
Transcription factor binding
DNA-bindingtranscription
activator activity, RNA polymerase
II-specificProtein
homodimerizationactivityheterodimerizationHistone deacetylase
binding
Transcription factor activity, RNA polymerase II
proximal promoter sequence-specific
DNA binding
Transferase activity
Enzyme bindingMolecular function
regulator
Protein kinase regulator activity
Kinase regulator activity
Enzyme activator activity
DNA binding
Organic cyclic compound binding
Neurotransmitterreceptor activity
DNA-binding transcriptionfactor activity
Regulatory region nucleic acid binding
DNA-binding transcription factor activity, RNA polymerase II-specific
Phosphatasebinding
Cytokine activityBindingKinase activity
Transferase activity, transferring phosphorus-containing groups
Cytokine receptor bindingProtein tyrosine kinase activity
Antioxidant activity
Ion bindingSignaling receptor activity
Enzyme regulator activity
Anion binding
Cofactor binding
Moleculartransducer activity
Heterocyclic compound binding
Drug binding
Protein binding Small molecule binding
Serine-type peptidase activity
Protein domain specific binding
Growth factor receptor binding
Protein kinase activity
Purine ribonucleoside triphosphate binding
RNA polymerase II transcription factor
binding
Integrin bindingLipid binding
Kinase binding Phosphotransferase activity, alcohol group as acceptor
Ribonucleotide bindingAmide binding
Peptide binding
Transcriptioncoregulator activity
Nucleotide binding
Receptor ligand activity
Tetrapyrrole binding
Growth factor activity
Transmembrane signaling receptor activity
Receptor regulator activity
ATP binding
Chromatin binding
Inorganic anion transmembrane
transporter activity
Ion gated channel activity
Passive transmembrane transporter activity
Nuclear hormone receptor binding
Ion channel activityIon transmembrane transporter
activity
Heme binding
Oxidoreductaseactivity
Metal ion binding
Cation binding
Proteinserine/threoninekinase activity
Sulfur compound binding
Transcription factor activity, direct ligand regulated sequence-specific
DNA binding Nuclear receptor
activity
Heparinbinding
Inorganic molecular entity transmembrane transporter activity
Channel activity
Transmembranetransporter activity
Carbohydratederivative binding Steroid hormone
receptor activityOxidoreductaseactivity, acting on
paired donors, with incorporation or
reduction of molecular oxygen
Protein dimerization activitySerine hydrolase
activityHormone receptor binding
Growth factor binding
Steroid bindingSignaling receptor
bindingPeptidase activity
Protein-containingcomplex binding
Peptidase activity, acting on L-amino
acid peptides
Catalytic activity, acting on a protein Catalytic activity
Nucleosidephosphate binding
Figure 5: *e GO MF analysis of predicted targets of MHC. ClueGO was used to identify the most significantly enriched GO MF terms.
Evidence-Based Complementary and Alternative Medicine 9
G/H synthase 2 (PTGS2, COX-2) with the highest degree(40) and prostaglandin G/H synthase 1 (PTGS1, COX-1)with a degree of 31 can be modulated by the compounds inMHC, indicating their vital role in helping to treat CVDs.COX-2 and COX-1 are constitutively expressed in the en-dothelium, brain and various tissues in physiological con-ditions, and convert arachidonate to prostaglandin H2,
which is responsible for production of inflammatoryprostaglandins. Previous relevant studies have defined thatthe increased expression of COX-2 and COX-1 may con-tribute to the development of inflammatory diseases due tothe fact that they can facilitate the transcription of severalcytokines associated with disease progression. COX-2 andCOX-1 have been acknowledged as classic therapeutic
% Terms per group
Plasma membrane region 20.93%∗∗
Cytoplasmic part 12.4%∗∗
Extracellular space 13.95%∗∗
Perinuclear region of cytoplasm 0.78%∗∗
Multivesicular body 0.78%∗∗
Chromosome, telomeric region 0.78%∗∗
Cell surface 0.78%∗∗
Apical part of cell 1.55%∗∗
Extracellular matrix 1.55%∗∗
Microtubule organizing center 1.55%∗∗
Protein kinase complex 2.33%∗∗
Transcription factor complex 2.33%∗∗
Endomembrane system 3.1%∗∗
Cytoplasmic vesicle 3.88%∗∗
Membrane protein complex 3.88%∗∗
Integral component of postsynaptic membrane 4.65%∗∗
Nucleoplasm 6.2%∗∗
Mitochondrion 6.98%∗∗
Membrane ra� 11.63%∗∗
Extracellularvesicle
Membrane region
Plasma membrane ra�
Caveola
Membrane ra�
Secretory granule lumen
Cytoplasmic vesicle part
Secretory vesicleCytoplasmicvesicle lumen
Extracellular space
Vesicle
Endomembranesystem
Protein-containingcomplex
Cellular_component
Platelet alphagranuleSecretory granule
Platelet alphagranule lumen
Vesicle lumen
Extracellular region part
Extracellularorganelle
Plasma membrane
Intrinsic component of plasma Plasma membrane partmembrane
Organelle membrane
Integral component of plasma Intrinsic component of membranemembrane
Cyclin-dependentprotein kinase
holoenzyme complex
TransferasecomplexCatalytic
complex
Transferase complex,transferring phosphorus-
containing groups
Collagen-containingextracellular
matrixApical part of cell
Endoplasmic reticulum partEndoplasmic reticulum
Cell surface
Perinuclear region of cytoplasm
Transcription factor complex
Nucleartranscription
factor complex
Endoplasmic reticulum lumen
RNA polymerase II transcription factor complex Apical plasma membrane
Extracellular matrix
Endosome
Intracellular vesicle
Cytoplasmic vesicle
Ficolin-1-richgranule lumen
Ficolin-1-richgranule
Late endosome Multivesicularbody
Extracellular exosome
Dendritic tree
Cell projection part
Cell periphery
Cell body
Neuron part
Postsynaptic membrane
Chromosome,telomeric region
Integralcomponent
of presynaptic membrane
Integral component of postsynaptic
membraneIntrinsic
component ofsynaptic
membrane
PresynapseIntrinsic
componentof presynaptic
membrane
Plasma membrane regionIntegral
componentof membrane
Membranemicrodomain
Organelle
Non-membrane-bounded organelle
Spindle
Intracellularnon-membrane-bounded organelle
Membrane-bounded organelle
Membrane-enclosed lumenOrganelle part
Intrinsic component of postsynaptic membrane
Synapse part
Synaptic membrane
Somatodendritic compartment
Axon
Dendrite
Cell projection
Neuron projection
Neuronal cell body
Presynaptic membrane
Intracellular
Nuclear chromosome part
Intracellular organelle part
Chromosomal part
Cytoplasm
Cytoplasmic part
Intracellular organelle
Chromosomal region
Intrinsic component of postsynaptic specialization membrane
Ion channel complex
Transmembrane transporter complex
Membrane part
Intracellular membrane-bounded organelle
Organelle lumen
Nuclear partCytosol Nuclear lumen
Nucleus
Nucleoplasm
Chromosome
Plasma membrane bounded cell projection part
Integralcomponent ofpostsynaptic specializationmembrane
Plasma membrane bounded cell projection
Integralcomponentof synaptic membrane
Postsynapse
Outer membrane
Whole membrane
Organelle outer membrane
Mitochondrial envelope
Mitochondrion
Mitochondrial membrane
Mitochondrial outer membrane
Protein kinase complex
Chromatin
Microtubuleorganizing center
Nuclear chromosome
Nuclear chromatin
Intracellular part
Cytoskeletal part
Cell part
Envelope
Organelle envelope
Mitochondrial part
Transporter complex
Chloride channel complex
Plasma membrane protein complex
Membrane protein
Complex
Membrane
Figure 6: *e GO CC analysis of predicted targets of MHC. ClueGO was used to identify the most significantly enriched GO CC terms.
10 Evidence-Based Complementary and Alternative Medicine
targets of nonsteroidal anti-inflammatory drugs (NSAIDs),which bind the site corresponding to the COX active site.Inhibition of the COX with NSAIDs acutely reduces in-flammation, pain, and fever, and long-term use of thesedrugs reduces fatal thrombotic events, as well as the de-velopment of colon cancer and Alzheimer’s disease. A recentresearch suggested that the inhibition of COX-2may activatethe MAPK pathway and reduce inflammatory response andimprove myocardial remodeling in mice with myocardialinfarction. Various activity compounds in TCM exertprotective effects in the vascular or cardiac injury via thesignaling or downstream processing of COX-2 [36–39]. Inaddition, heat shock protein 90 (HSP 90), the key enzyme inthe blood coagulation system, has been identified to be thetarget of 31 chemicals. A recent study has shown that Hsp90modulates cardiac ventricular hypertrophy through acti-vating the MAPK pathway in cardiomyocytes [40]. SinceHSP 90 serves as a regulator in the TGF-β signaling pathway,the downregulation of HSP 90 can inhibit the activation ofmyocardial fibroblast, which is a pathological signature ofmyocardial fibrosis [41]. In light of recent evidence, theactivity compounds in various TCM formulas can producetherapeutic effects on atherosclerosis, cardiac injury, hy-pertension, thrombosis, and neurodegenerative diseasesthrough inhibiting the expression of HSP 90 in vitro or invivo. *us, the bioactive ingredients from MHC interactingwith COX-2, COX-1, and HSP 90 may be the key factors inthe treatment of the fibroblast activation in patients withCVD.
By analyzing the GO-enriched results, we found thatMHCmay have certain effects in regulating cytokine-relatedbiological processes, such as “cellular response to cytokinestimulus (GO:0071345)” and “cytokine-mediated signalingpathway (GO:0019221)”. Cytokines (such as IL-1β, IL-6, andTNF) derived from the vessel wall or blood have been provento be associated with vascular risk and predictive of futurecardiovascular events. Inflammatory processes and theirfailure to resolve is firmly established as central to theprogress of cardiovascular diseases. Several emerging lines ofevidence support the hypothesis that inhibition of the in-flammatory processes by targeting of the cytokines mightserve as an efficient system to attenuate myocardial andarterial injury, reduce disease progression, and promotehealing. Our results have shown that the protective effects ofMHC may be related to the inhibition of cytokines therebysuppressing chronic inflammatory process. Besides, one ofthe key reasons for the occurrence and development of CVDis the apoptotic process. In the present study the “regulationof apoptotic process (GO:0042981)” and “apoptotic process(GO:0006915)” are both enriched in the top ranked GO BPterms. Apoptosis is defined as a highly regulated form of celldeath and can be regulated by genetic or pharmacologicinterventions. Regulation of apoptosis is a hopeful choice oftreatment for CVDs and disorders such as myocardial in-farction, ischemia/reperfusion injury, chemotherapy car-diotoxicity, and heart failure. In the process of apoptotic,TP53, IL-6, TGF-β, TNF-α, IKBKB, and EGFR are con-sidered to be important related proteins. *e “cellular
HTLV-I infection_Homo sapiens_hsa05166PI3K-Akt signaling pathway_Homo sapiens_hsa04151
Small cell lung cancer_Homo sapiens_hsa05222
TNF signaling pathway_Homa sapiens_hsa04668
Prostate cancer_Homo sapiens_hsa05215AGE-RAGE signaling pathway in diabetic complications_Homo sapiens_hsa04933
Pancreatic cancer_Homo sapiens_hsa05212Pathways in cancer_Homo sapiens_hsa05200
Hepatitis B_Homo sapiens_hsa05161Proteoglycans in cancer_Homo sapiens_hsa05205
Small cell lung cancer_Homo sapiens_hsa05222
HTLV-I infection_Homo sapiens_hsa05166
TNF signaling pathway_Homo sapiens_hsa04668
Proteoglycans in cancer_Homo sapiens_hsa05205
Pancreatic cancer_Homo sapiens_hsa05212
Hepatitis B_Homo sapiens_hsa05161
Prostate cancer_Homo sapiens_hsa05215
PI3K-Akt signaling pathway_Homo sapiens_hsa04151
AGE-RAGE signaling pathway in diabetic complications_Homo sapiens_hsa04933
Pathways in cancer_Homo sapiens_hsa05200
Figure 7: *e KEGG enrichment analysis of predicted targets of MHC.
Evidence-Based Complementary and Alternative Medicine 11
response to oxidative stress (GO:0034599)” and “cellularresponse to reactive oxygen species (GO:0034614)” were alsoenriched in our results. It is established that elevated oxi-dative stress could be a key factor in the development ofcomplex biochemical, structural, and functional changesassociated with CVD. Recently, different research groupshave provided evidences that pharmacological approaches tocounteract excessive accumulation of ROS are sufficient inthe prevention or treatment of heart failure. Besides, en-dothelial dysfunction and vascular remodeling caused by IL-6, TGF-β, TNF-α, EGFR, and VEGFA are also some of thecore features of CVD.
Our results showed that MHC integrated various sig-naling pathways which have been testified as accurate targetpathways to modulate CVD, such as TNF, PI3K-Akt, HIF-1,FoxO, apoptosis, calcium, MAPK, Toll-like receptor, VEGF,and NF-κB pathways. Most signaling pathways significantlyenriched by targets were associated with multiple chronicinflammatory diseases, not merely CVD, which is consistent
with the enriched GO terms in our study. Among 177pathways, PI3K-Akt and TNF signaling as critical pathwaysregulate the process of apoptosis, inflammation, and oxi-dative stress in the development and severity of CVD. Forinstance, the master factors contributing to the initiation andevolution of inflammatory responses in cardiovascular tis-sues include the elevated level of TNF and the activation ofNF-κB in the TNF signaling pathway. Notably, our researchindicated that the main biological function of MHC in CVDis negatively regulating the TNF signaling pathway by theinteraction between bioactivity compounds and the po-tential targets including TNF, VCAM1, COX-2, MMP3,MMP9, IKBKB, IL-1β, IL-6, CCL2, CXCL2, CXCL10, cas-pase-3, and caspase-8. Moreover, our results also show thatMHC can exert the protective effect by modulating thePI3K-Akt signaling pathway. In the cardiovascular system, agreat number of studies targeting PI3K/Akt have elucidatedthe contribution of this pathway to cardiac and vascularfunction regulation both in the normal and diseased states.
PCOLCECOL3A1
KLF7CTRB1
COL1A1
ACPPPRSS1 MT-ND6
SLPINKX3-1 HERC5 CLDN4AHSA1 OLR1ALOX5
MMP3HAS2F7 DUOX2
LTA4HCTSD RUNX2HSF1 IGFBP3
CASP9 MMP1SPP1 PTGS1HSPB1PARP1 DIO1LYZFASN IGF2 PLATMMP2CHEK2 CASP8BAX CRPTGFB1
CCNB1 STAT1 F10PPARD BCL2L1 SERPINE1NR3C2 MMP9HMOX1TOP1 IL10SIRT1PCNA DPP4IL4 KCNH2NCF1ERBB2HIF1A IL1APPARG CCL2 GJA1CHEK1CASP3 IFNGPTGS2BIRC5 MPORXRB
VEGFAHSPA5 F3NPEPPS THBDRB1E2F1 PTEN VCAM1BCL2 IL6 MAPK14 IRF1TOP2BMYC IL1BAR TNFAKT1TP53 MAPK1 CD40LGIL2CDKN1ANCOA1 SELEEGF SCN5ACXCL10RXRA NOS3 PLAUCCNA2 CCND1 MAPK8ESR1TOP2A CDK2
JUN ERBB3IL8HSP90AA1 KCNMA1RELAEGFRPIM1 AHRABCG2ATP5B FOS PTGER3METNCOA2 PIK3CG BACE1NOS2 ELK1
CAV1E2F2 CDK1 CXCL2PPARA F2RASSF1 CATNFKBIAKDRPGR PRKCD CXCL11 CHRM4SOD1 GSK3B EPXINSRAKR1B1
NR3C1SLC2A4AKR1C3 PRKACAIKBKBHK2 RAF1CHUKNR1I2 ADRA2CPRKCA CA2
CALM2 PRKCENR1I3 ESR2CYP1A1 PKIACHRM2PSMD3ACACAADRA2APRKCBNQO1 PTPN1CYP1B1 NFE2L2ODC1DCAF5 OPRD1OPRM1 ADRA1DRASA1
CHRNA2CHRM1HSD3B2 ADRA1BADRB2CYP1A2 PON1
CYP3A4ACHE CHRM5HSD3B1 MGAM CHRM3 CHRNA7PPP3CA MAP2GSTP1
HTR2APORADRA1APDE3ASLC6A4
GRIA2 GABRA5GSTM1
GABRA1RUNX1T1 PYGM ADRB1SLC6A3XDHHTR7
SLC6A2DRD1SULT1E1HTR3A GABRA2GSTM2
GABRA6
ADH1BMAOA GABRA3
MAOB
Figure 8: Network pharmacology analysis through the protein interaction of predicted protein targets of MHC. *e network nodes werepredicted proteins and the edges represented the functional associations.
12 Evidence-Based Complementary and Alternative Medicine
GSK-3β, AKT1, eNOS, and VEGFA, which have beenscreened as the targets of MHC, are considered to modulateimportant cellular physiological processes in the vessels,heart, and brain. *e eNOS protein shows pharmacologicalproperties by producing NO, which can rapidly diffuseacross cell membranes to act as a potent paracrine mediator.*e PI3K/Akt signaling pathway has been proven to beinvolved in the resistance response to hypoxia ischemia. Itcan regulate the expression of HIF-1α, which furthermodulates the expression of downstream targets that relatedto glucose metabolism and angiogenesis to facilitate ische-mic adaptation [42]. In cardiomyocytes and smooth musclecells, calcium fluxes are the best characterized receptor-regulated signaling events. Recent studies have proven thatactivation of PI3K/Akt signaling is interconnected withcalcium signaling in cardiovascular system, which isemerging to make great influence in disease development[43]. Based on the results of our study, in this complexsystem with MHC-compounds-targets-CVDs interactions,the abovementioned active ingredients, targets, and path-ways are associated with the pharmacological mechanisms ofMHC in the treatment process of CVDs.
5. Conclusion
*e current study uses a network pharmacology approachthat combines active compounds, potential targets, GO, andKEGG enrichment analysis to investigate the molecularmechanism of MHC against CVDs from a systematic per-spective. Among these crucial biological functions, 303targets were identified as key active factors involved in the177 related pathways. We found that our prediction-basedresults were generally consistent with previous research onpathways and diseases treated with MHC extracts. Fur-thermore, we can suggest more comprehensive mechanismsof therapeutic effects of MHC in terms of target proteins,pathways, and diseases thanmanual reviews of the literature.Nonetheless, more experimental researches were warrantedto validate these hypotheses, and experimental verification ofthe potential effective compounds after candidate screeningis needed, which will lay a foundation for further experi-mental research and clinical rational application of MHC.
Abbreviations
MHC: Mahai capsulesCVD: Cardiovascular diseasesTCM: Traditional Chinese medicineHQ: Hedysarum Multijugum Maxim (Huangqi)MQ: Strychni semen (Maqianzi)DG: Angelicae Sinensis Radix (Danggui)HFT: Caulis Piperis Kadsurae (Haifengteng)QN: Homalomena Occulta (Lour.) Schott
(Qiannianjian)DH: Radix Rhei Et Rhizome (Dahuang)TCMSP: Traditional Chinese Medicine Systems
PharmacologyADME: Absorption, distribution, metabolism, and
excretion
OB: prediction of oral bioavailabilityDL: Prediction of drug-likenessGO: Gene ontologyPPI: Protein-protein interaction.
Data Availability
We have presented all our main data in the form of figuresand additional file. *e datasets supporting the conclusionsof this article are included within the article.
Conflicts of Interest
*e authors declare that they have no conflicts of interest.
Authors’ Contributions
MS and Bl contributed equally to this work. ZL conceivedand designed the experiments; MS and QY performed theexperiments and wrote the paper; XG, XR, and SJ analyzedthe data. All authors read and approved the final manuscript.
Supplementary Materials
Table S1: targets of the 75 candidate compounds of Haima.Table S2: targets-diseases. (Supplementary Materials)
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