Evidence-Based Complementary and Alternative Medicine
Volume 2017 (2017), Article ID 4198035, 21 pages
https://doi.org/10.1155/2017/4198035

Research Article

Systems Pharmacological Approach of Pulsatillae Radix on Treating Crohn’s Disease

Su Yeon Suh and Won G. An

Department of Pharmacology, School of Korean Medicine, Pusan National University, Yangsan, Gyeongnam 50612, Republic of Korea

Correspondence should be addressed to Won G. An; wgan@pusan.ac.kr

Received 20 January 2017; Revised 28 February 2017; Accepted 1 March 2017; Published 1 June 2017

Academic Editor: Jae Youl Cho

Copyright © 2017 Su Yeon Suh and Won G. An. 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.

Abstract.

In East Asian traditional medicine, Pulsatillae Radix (PR) is widely used to treat amoebic dysentery and renowned for its anti-inflammatory effects. This study aimed to confirm evidence regarding the potential therapeutic effect of PR on Crohn’s disease using a system network level based in silico approach. Study results showed that the compounds in PR are highly connected to Crohn’s disease related pathways, biological processes, and organs, and these findings were confirmed by compound-target network, target-pathway network, and gene ontology analysis. Most compounds in PR have been reported to possess anti-inflammatory, anticancer, and antioxidant effects, and we found that these compounds interact with multiple targets in a synergetic way. Furthermore, the mRNA expressions of genes targeted by PR are elevated significantly in immunity-related organ tissues, small intestine, and colon. Our results suggest that the anti-inflammatory and repair and immune system enhancing effects of PR might have therapeutic impact on Crohn’s disease.

1. Introduction

Inflammatory bowel disease (IBD) may be categorized clinically as Crohn’s disease or ulcerative colitis [1]. Crohn’s disease usually causes a variety of systemic symptoms, which include chronic inflammation of the bowel [2]. Although any part of the digestive tract from mouth to anus may be affected, usually the small intestine (ileum) and the large intestine (colon) are involved; ileocolic Crohn’s accounts for 50% of cases, ileal Crohn’s for 30%, and colic Crohn’s for 20% of cases [3]. Symptoms vary though its common manifestations include persistent diarrhea, rectal bleeding, abdominal cramps, and pain, though fever, extreme fatigue, and weight loss are also common [1, 2, 4]. Constipation is also a frequent symptom and can lead to bowel obstruction and, thus, increase the risk of bowel cancer. Complications involving other than the gastrointestinal (GI) tract include anemia, arthritis, liver disease, eye inflammation, and skin rashes [2, 4].

According to a statistical report issued by the Health Insurance Review and Assessment Service in Korea in 2016, the number of Crohn’s disease patients increased from 13,920 in 2011 to 18,332 in 2015, an average annual increase of 7.1%. Furthermore, over the same period, total medical cost has increased by 19.4% annually, and more than half of patients are in 20s or 30s. A systematic review about the economic and quality-of-life burden of Crohn’s disease reported that, in the USA, Germany, France, UK, Italy, and Spain, in all countries combined, Crohn’s medical costs totaled 30 billion annually and that patient quality of life was substantially diminished by the physical, emotional, and social effects of the disease [5].

Although Crohn’s disease is a global health problem [5], its pathology remains poorly understood [1, 6]. Nevertheless, it has been established that its etiology is associated with complex interactions between environmental, immune, microbial, and genetic factors [4, 7], though a number of authors have suggested that the primary defect in Crohn’s disease is one of relative immunodeficiency [6, 8, 9].

A systematic review of publications from 1947 to 2013 involving controlled studies of herbal therapies in IBD indicated that at least 50 percent of IBD patients used some form of complementary and alternative medicine (CAM), since most herbal therapies had been reported to have anti-inflammatory effects and plausible action mechanisms in IBD with minimal adverse effects [10]. Moreover, herbal medicines are being increasingly used and requested by IBD patients not only in Asia, but also in Western countries [11].

Of the anti-inflammatory herbal medicines, Pulsatillae Radix (Baekduong, PR) is worth considering as a potential treatment for Crohn’s disease as it was widely used in traditional medicine to treat amoebic dysentery and has also been demonstrated scientifically to have anti-inflammatory effects experimentally [12, 13]. PR is traditional Korean herbal medicine prepared from the roots of Pulsatilla koreana Nakai and contains several phytochemicals, including anemonin, hederagenin, oleanolic acid, and deoxypodophyllotoxin [14, 15]. Some experimental study results have shown that PR has various biological activities. For instance, aqueous and ethanol extracts of PR have been reported to demonstrate anticancer effects in anaplastic thyroid cancer [16], methanol extract of PR was found to have anti-inflammatory effects in lipopolysaccharide (LPS) exposed rats [17], and PR has also been reported to inhibit adipocyte differentiation and to suppress adipogenesis [13].

According to the meridian tropism theory of traditional medicine, the effects of PR reach to the stomach meridian and the large intestine meridian, which is in accord with the organs commonly affected by Crohn’s disease. In terms of the selection of traditional medication, meridian tropism theory plays an important role, as it is one of the core principles of traditional medicine [18]. Based on meridian tropism theory, each herbal medicine possesses different affinities for certain organs and meridians of the body [19].

In the present study, we sought to confirm the therapeutic effects of PR in Crohn’s disease using system level analysis and a network based in silico approach. A schematic of the network pharmacological study is summarized in Figure 1.

Figure 1: Workflow: network analysis, relevant organ location network analysis, gene ontology, and pathway analysis were performed on active compounds identified in Pulsatillae Radix (PR) by screening and target fishing.

2. Material and Methods

2.1. Identification of Active Compounds

According to the Traditional Chinese Medicine Systems Pharmacology (TCMSP, http://ibts.hkbu.edu.hk/LSP/tcmsp.php) database (a free phytochemical database of herbal medicine), PR contains 57 identified compounds. Parameters related to absorption, distribution, metabolism, and excretion (ADME), namely, human drug-likeness (DL) [20], oral bioavailability (OB) [21], and Caco-2 permeability (Caco-2) [22], were employed to filter out potential active compounds.

2.1.1. Drug-Likeness Evaluation

DL helps filter out “drug-like” compounds in oriental herbs, as DL represents a qualitative concept for valuations based on how “drug-like” prospective compound is [23]. Accordingly, a high DL may lead to a greater possibility of therapeutic success, and compounds with a higher DL value are more likely to possess certain biological properties [24]. Calculations of DL in the TCMSP database are based on the Tanimoto coefficient formula [25] as follows:

where represents the molecular parameters of herbal compounds and is the average molecular parameter of all compounds in the DrugBank database (http://www.drugbank.ca/) [26]. In the present study, we excluded compounds with a DL value of < 0.18.

2.1.2. Oral Bioavailability (OB) Prediction

Oral bioavailability (OB) is defined as the absorption ratio of an active compound into the systemic circulation, which represents convergence of the ADME process [21]. OB values are dependent on drug dissolution in the gastrointestinal (GI) tract, intestinal and hepatic first-pass metabolisms, and intestinal membrane permeation, and, thus, OB is considered a major pharmacokinetic parameter for drug evaluations [24]. In this study, the OB threshold was set as ≥ 15%.

2.1.3. Caco-2 Permeability Screening

Caco-2 permeability is used to predict the absorption of an orally administered drug [22]. Surface absorptivity of the small intestine is maximized by villi and microvilli; for this reason, orally administered drugs are mostly absorbed in the small intestine [27]. Moreover, the movement of orally administered drugs across the intestinal epithelial barrier determines the rate and extent of human absorption and ultimately affects drug bioavailability [28]. In the present study, compounds with OB, DL, and Caco-2 values of >15%, >0.18, and >−0.4, respectively, were regarded as active and subjected to analysis. In addition, we included some compounds with lower ADME profile than above thresholds, for the reason that those were reported to possess anti-inflammatory, antioxidant, anticancer, and antibacterial effects. This study was about only one single herb, and for this reason we did not use a high threshold of ADME profile to filter potential active compounds. Instead, we lowered the standard of OB in order to analyze the most potential targets of PR.

2.2. Target Fishing

Molecular targets of filtered potential active compounds were found in the TCMSP [29], Similarity Ensemble Approach (SEA, http://sea.bkslab.org), and the Binding Database (http://www.bindingdb.org). In addition, filtered compound-target interaction profile mapping was performed using the UniProt database (http://www.uniprot.org/) [30].

2.3. Gene Ontology (GO) Analysis

Biological process (BP) of gene ontology (GO) analysis was employed to determine the biological properties of target genes [31]. GO annotation provides statistical analyses on gene function information. In this research, GO BP terms with values < 0.01 were employed and the data was collected using the DAVID 6.8 Gene Functional Classification Tool (http://david.abcc.ncifcrf.gov/).

2.4. Network Construction and Analysis

In order to understand the multiscale interactions between the active compounds of PR and targets, two types of networks were built: (1) a compound-target network (C-T network), in which nodes represented either compounds or target proteins, and edges indicated compound-target connections; and (2) a target-pathway network (T-P network), which was used to extract pathways from the KEGG database (http://www.genome.jp/kegg/) and to filter out terms highly associated with Crohn’s disease and values of < 0.01. Related targets were mapped onto relevant pathways to produce the T-P network. Both networks were generated in Cytoscape 3.4.0, an open-source biological network visualization and data integration software package [32].

2.5. Target Organ Location Network

Tissue-specific patterns of mRNA expression can indicate important associations with particular biological events or gene functions [33]. Thus, to explore the beneficial effects of PR on Crohn’s disease, it was important to determine the tissue mRNA expression profiles of target proteins at the organ level [34]. The target organ location network was used with the Dataset: GeneAtlas U133A, gcrma (http://biogps.org). The BioGPS database provides expression data acquired by direct measurements of gene expressions by microarrays analysis [35]. First, the mRNA expression patterns of each target gene in 84 parts of organ tissues were obtained. Second, average values were calculated for each gene. Third, above average mRNA expressions in relevant organ tissues were extracted and arranged by frequency. Finally, a target organ location network was constructed using Cytoscape 3.4.0 and organ-specific, Crohn’s disease related, gene overexpression data.

2.6. GEO2R Analysis

Using Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo), we compared mRNA expression pattern of normal groups and Crohn’s disease groups. GEOquery and limma R packages of GEO2R tool were employed to identify highly expressed genes.

2.7. Network Pathway

In order to elucidate the action mechanisms of PR in Crohn’s disease, filtered target proteins were input into the pathway map of inflammatory bowel disease acquired from the Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.kegg.jp/) database.

3. Results

3.1. Identification of Active Compounds

Of the 57 compounds (as shown in Supplementary Table S1 in Supplementary Material available online at https://doi.org/10.1155/2017/4198035) in PR acquired from the TCMSP, excluding compounds with no target information, 19 compounds with a known target met the criteria OB ≥ 15%, Caco-2 ≥ −0.4, and DL ≥ 0.18. Additionally 13 compounds reported to have anti-inflammatory, antioxidant, anticancer, and antibacterial effects were added, and finally 32 compounds were analyzed (as shown in Table 1).

Table 1: 32 potential active compounds of Pulsatillae Radix.

ID
Active compounds
Structure
OB (%)
Caco-2
DL

C1
3-Methylcoumarin

19.66
1.27
0.05

C2
5,6,7-Trimethoxycoumarin

32.54
0.94
0.12

C3
AIDS045703

21.37
0.55
0.87

C4
Androstane-3,11,17-triol

13.19
−0.04
0.38

C5
Anemosapogenin

17.87
0.07
0.77

C6
Anemoside A3

15.46
−1.6
0.15

C7
Aureusidin

53.42
0.07
0.24

C8
Beta-sitosterol

36.91
1.32
0.75

C9
Betulonic acid

16.83
0.65
0.78

C10
Campesterol

5.57
1.6
0.72

C11
Cauloside A

6.84
−0.82
0.4

C12
Cernuoside

2.69
−1.51
−2.18

C13
Dauricine (8CI)

23.65
0.9
0.37

C14
Ergosterol

14.29
1.47
0.72

C15
Fraxinol

24.19
0.7
0.1

C16
Hederagenol

22.42
0.1
0.74

C17
Isorhamnetin

49.6
0.31
0.31

C18
LAN

42.12
1.52
0.75

C19
Lignoceric acid

14.9
1.24
0.33

C20
Mairin

55.38
0.73
0.78

C21
Oleanolic acid

29.02
0.59
0.76

C22
Oleanolic acid deriv.

14.24
0.65
0.7

C23
Pinoresinol

4.25
0.52
0.52

C24
Pulchinenoside A_qt

16.91
0.12
0.77

C25
Scoparone

74.75
0.85
0.09

C26
Sitogluside

20.63
−0.14
0.62

C27
Sitosteryl acetate

40.39
1.39
0.85

C28
Stigmasterol

43.83
1.44
0.76

C29
Tricosanoic acid

15.29
1.18
0.3

C30
Ursolic acid

16.77
0.67
0.75

C31
ZINC01615307

56.38
0.53
0.87

C32
β-Sitosterol

5.84
1.42
0.71

A number of these 32 compounds have been shown experimentally to have various biological activities. For example, antioxidative effect of cernuoside (C12; DL = 0.79, OB = 2.69, Caco-2 = −1.51) was experimentally identified [36]. Pinoresinol (C23; DL = 0.52, OB = 4.25, Caco-2 = 0.52) was reported to have anti-inflammatory properties [37]. β-Sitosterol (C32; DL = 0.71, OB = 5.84, Caco-2 = 1.42) and campesterol (C23; DL = 0.72, OB = 5.57, Caco-2 = 1.6) were reported to have the protecting effect by natural and synthetic antioxidants during heating [38]. Antiallergic effects of scoparone (C25; DL = 0.09, OB = 74.75, Caco-2 = 0.85) was experimentally demonstrated in rat model, which attenuates IgE-mediated allergic response in mast cells [39]. Aureusidin (C7; DL = 0.24, OB = 53.42, Caco-2 = 0.07) was reported to have marked antioxidant activity and to be useful for the treatment of several diseases [40, 41], and anemosapogenin (C5; DL = 0.77, OB = 17.87, Caco-2 = 0.07) has antitumor effects [42, 43]. Betulonic acid (C9; DL = 0.78, OB = 16.83, Caco-2 = 0.65) possesses various medical effects, such as antiviral (HIV-1), anticancer, and immunomodulatory activities [44]. Cauloside (C11; DL = 0.4, OB = 6.84, Caco-2 = −0.82) from blue cohosh was reported to inhibit proinflammatory cytokine induction by LPS [45]. Dauricine (C13; DL = 0.9, OB = 23.65, Caco-2 = 0.37) from Asiatic moonseed was reported to have significant antibacterial and anti-inflammatory effects [46], and ergosterol (C14; DL = 0.72, OB = 14.29, Caco-2 = 1.47) [47] from the mushroom and isorhamnetin (C17; DL = 0.31, OB = 49.6, Caco-2 = 0.31) [48] were both found to have anti-inflammatory effects. Furthermore, oleanolic acid (C21; DL = 0.76, OB = 29.02, Caco-2 = 0.59) and ursolic acids (C30; DL = 0.75, OB = 16.77, Caco-2 = 0.67) have been reported to have antioxidative and anti‐inflammatory effect [49, 50]. As mentioned above, PR contains many compounds, which are ubiquitous in plants, herbs, and fruits, with anti-inflammatory, anticancer, and antioxidative effects.

3.2. Target Fishing

These 32 identified active compounds interact with 182 target proteins (Table 2); that is, on average, they interact with 5.7 target genes, which does much to explain the polypharmacological and synergistic effects of PR on multiple targets [51].

Table 2: Related targets of Pulsatillae Radix.

UniProt ID
Target
Gene name

Q92887
Canalicular multispecific organic anion transporter 1
ABCC2

P12821
Angiotensin-converting enzyme
ACE

P22303
Acetylcholinesterase
ACHE

P24666
Low molecular weight phosphotyrosine protein phosphatase
ACP1

P00326
Alcohol dehydrogenase 1C
ADH1C

P35348
Alpha-1A adrenergic receptor
ADRA1A

P35368
Alpha-1B adrenergic receptor
ADRA1B

P25100
Alpha-1D adrenergic receptor
ADRA1D

P08913
Alpha-2A adrenergic receptor
ADRA2A

P18825
Alpha-2C adrenergic receptor
ADRA2C

P08588
Beta-1 adrenergic receptor
ADRB1

P07550
Beta-2 adrenergic receptor
ADRB2

P15121
Aldose reductase
AKR1B1

O60218
Aldo-keto reductase family 1 member B10
AKR1B10

P09917
Arachidonate 5-lipoxygenase
ALOX5

P09923
Intestinal-type alkaline phosphatase
ALPI

P04746
Pancreatic alpha-amylase
AMY2A

P10275
Androgen receptor
AR

P15336
Cyclic AMP-dependent transcription factor ATF-2
ATF2

P05023
Sodium/potassium-transporting ATPase subunit alpha-1
ATP1A1

P15291
Beta-1,4-galactosyltransferase 1
B4GALT1

Q07812
Apoptosis regulator BAX
BAX

P10415
Apoptosis regulator Bcl-2
BCL2

Q07817
Bcl-2-like protein 1
BCL2L1

O15392
Baculoviral IAP repeat-containing protein 5
BIRC5

O43570
Carbonic anhydrase 12
CA12

Q8N1Q1
Carbonic anhydrase 13
CA13

P00918
Carbonic anhydrase II
CA2

P22748
Carbonic anhydrase IV
CA4

P35218
Carbonic anhydrase 5A, mitochondrial
CA5A

Q16790
Carbonic anhydrase VI
CA9

P62158
Calmodulin
CALM1

P29466
Caspase-1
CASP1

P42574
Caspase-3
CASP3

Q14790
Caspase-8
CASP8

P55211
Caspase-9
CASP9

P13500
C-C motif chemokine 2
CCL2

P20248
Cyclin-A2
CCNA2

P24385
G1/S-specific cyclin-D1
CCND1

P30279
G1/S-specific cyclin-D2
CCND2

P60033
CD81 antigen
CD81

P24941
Cell division protein kinase 2
CDK2

P11802
Cell division protein kinase 4
CDK4

Q00534
Cell division protein kinase 6
CDK6

P38936
Cyclin-dependent kinase inhibitor 1
CDKN1A

O14757
Serine/threonine-protein kinase Chk1
CHEK1

P11229
Muscarinic acetylcholine receptor M1
CHRM1

P08172
Muscarinic acetylcholine receptor M2
CHRM2

P20309
Muscarinic acetylcholine receptor M3
CHRM3

P08173
Muscarinic acetylcholine receptor M4
CHRM4

Q15822
Neuronal acetylcholine receptor subunit alpha-2
CHRNA2

P36544
Neuronal acetylcholine receptor protein, alpha-7 chain
CHRNA7

O15111
NF-kappa-B inhibitor alpha
CHUK

P16220
Cyclic AMP-responsive element-binding protein 1
CREB1

P15509
Granulocyte-macrophage colony-stimulating factor
CSF2RA

P17538
Chymotrypsinogen B
CTRB1

P07858
Cathepsin B
CTSB

P10145
Interleukin-8
CXCL8

Q16850
Lanosterol 14-alpha demethylase
CYP51A1

Q9UBM7
7-Dehydrocholesterol reductase
DHCR7

P27487
Dipeptidyl peptidase IV
DPP4

P21728
Dopamine D1 receptor
DRD1

Q9NRD8
Dual oxidase 2
DUOX2

Q6UWV6
Intestinal alkaline sphingomyelinase
ENPP7

Q99814
Endothelial PAS domain-containing protein 1
EPAS1

P03372
Estrogen receptor
ESR1

Q92731
Estrogen receptor beta
ESR2

P00742
Coagulation factor Xa
F10

P00734
Thrombin
F2

P08709
Coagulation factor VII
F7

P48023
Tumor necrosis factor ligand superfamily member 6
FASLG

P49327
Fatty acid synthase
FASN

P05230
Fibroblast growth factor 1
FGF1

P09038
Heparin-binding growth factor 2
FGF2

P01100
Proto-oncogene c-Fos
FOS

P14867
Gamma-aminobutyric acid receptor subunit alpha-1
GABRA1

P47869
Gamma-aminobutyric-acid receptor alpha-2 subunit
GABRA2

P34903
Gamma-aminobutyric-acid receptor alpha-3 subunit
GABRA3

P31644
Gamma-aminobutyric-acid receptor alpha-5 subunit
GABRA5

P17677
Neuromodulin
GAP43

Q8TDU6
G-protein coupled bile acid receptor 1
GPBAR1

P42262
Glutamate receptor 2
GRIA2

P49841
Glycogen synthase kinase-3 beta
GSK3B

Q9UII4
Probable E3 ubiquitin-protein ligase HERC5
HERC5

P09601
Heme oxygenase 1
HMOX1

P01112
GTPase HRas
HRAS

P28845
Corticosteroid 11-beta-dehydrogenase isozyme 1
HSD11B1

P80365
Corticosteroid 11-beta-dehydrogenase isozyme 2
HSD11B2

P08238
Heat shock protein HSP 90
HSP90AB1

P28223
5-Hydroxytryptamine 2A receptor
HTR2A

P46098
5-Hydroxytryptamine receptor 3A
HTR3A

P05362
Intercellular adhesion molecule 1
ICAM1

P01857
Ig gamma-1 chain C region
IGHG1

P01584
Interleukin-1 beta
IL1B

P60568
Interleukin-2
IL2

P05231
Interleukin-6
IL6

O15357
Phosphatidylinositol-3,4,5-trisphosphate 5-phosphatase 2
INPPL1

P05412
Transcription factor AP-1
JUN

Q12809
Potassium voltage-gated channel subfamily H member 2
KCNH2

Q12791
Calcium-activated potassium channel subunit alpha 1
KCNMA1

O75164
Lysine-specific demethylase 4A
KDM4A

P35968
Vascular endothelial growth factor receptor 2
KDR

Q99732
Lipopolysaccharide-induced tumor necrosis factor-alpha factor
LITAF

P09960
Leukotriene A-4 hydrolase
LTA4H

P21397
Amine oxidase [flavin-containing] A
MAOA

P27338
Amine oxidase [flavin-containing] B
MAOB

P11137
Microtubule-associated protein 2
MAP2

Q16539
Mitogen-activated protein kinase 14
MAPK14

P45983
Mitogen-activated protein kinase 8
MAPK8

Q13387
C-Jun-amino-terminal kinase-interacting protein 2
MAPK8IP2

Q07820
Induced myeloid leukemia cell differentiation protein Mcl-1
MCL1

P14174
L-Dopachrome tautomerase
MIF

P03956
Interstitial collagenase
MMP1

P09238
Stromelysin-2
MMP10

P08253
72 kDa type IV collagenase
MMP2

P08254
Stromelysin-1
MMP3

P14780
Matrix metalloproteinase-9
MMP9

P42345
Serine/threonine-protein kinase mTOR
MTOR

P14598
Neutrophil cytosol factor 1
NCF1

Q15788
Nuclear receptor coactivator 1
NCOA1

Q15596
Nuclear receptor coactivator 2
NCOA2

Q9GZQ4
Neuromedin-U receptor 2
NMUR2

P35228
Nitric oxide synthase, inducible
NOS2

P29474
Nitric oxide synthase, endothelial
NOS3

P15559
NAD(P)H dehydrogenase [quinone] 1
NQO1

P04150
Glucocorticoid receptor
NR3C1

P08235
Mineralocorticoid receptor
NR3C2

P01111
GTPase NRas
NRAS

P78380
Oxidized low-density lipoprotein receptor 1
OLR1

P35372
Mu-type opioid receptor
OPRM1

P07237
Protein disulfide-isomerase
P4HB

Q14432
CGMP-inhibited 3′,5′-cyclic phosphodiesterase A
PDE3A

P16284
Platelet endothelial cell adhesion molecule
PECAM1

P06401
Progesterone receptor
PGR

P42336
Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform
PIK3CA

P48736
Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit, gamma isoform
PIK3CG

P11309
Proto-oncogene serine/threonine-protein kinase Pim-1
PIM1

P61925
cAMP-dependent protein kinase inhibitor alpha
PKIA

P00749
Urokinase-type plasminogen activator
PLAU

P19174
1-Phosphatidylinositol 4,5-bisphosphate phosphodiesterase gamma-1
PLCG1

P09884
DNA polymerase alpha catalytic subunit
POLA1

P06746
DNA polymerase beta
POLB

P54098
DNA polymerase catalytic subunit
POLG

P27169
Serum paraoxonase/arylesterase 1
PON1

Q03181
Peroxisome proliferator activated receptor delta
PPARD

P37231
Peroxisome proliferator activated receptor gamma
PPARG

P17612
mRNA of PKA catalytic subunit C-alpha
PRKACA

P17252
Protein kinase C alpha type
PRKCA

P05129
Protein kinase C gamma type
PRKCG

P07477
Trypsin-1
PRSS1

P43115
Prostaglandin E2 receptor EP3 subtype
PTGER3

O14684
Prostaglandin E synthase
PTGES

P23219
Prostaglandin G/H synthase 1
PTGS1

P35354
Prostaglandin G/H synthase 2
PTGS2

P18031
Protein-tyrosine phosphatase 1B
PTPN1

P17706
T-cell protein-tyrosine phosphatase
PTPN2

P29350
Hematopoietic cell protein-tyrosine phosphatase
PTPN6

P11217
Glycogen phosphorylase, muscle form
PYGM

Q04206
Transcription factor p65
RELA

P19793
Retinoic acid receptor RXR-alpha
RXRA

Q14524
Sodium channel protein type 5 subunit alpha
SCN5A

P16581
E-selectin
SELE

Q9HAS3
Solute carrier family 28 member 3
SLC28A3

O43826
Glucose-6-phosphate translocase
SLC37A4

P13866
Sodium/glucose cotransporter 1
SLC5A1

P31639
Sodium/glucose cotransporter 2
SLC5A2

Q9NY91
Low affinity sodium-glucose cotransporter
SLC5A4

P23975
Sodium-dependent noradrenaline transporter
SLC6A2

Q01959
Sodium-dependent dopamine transporter
SLC6A3

P31645
Sodium-dependent serotonin transporter
SLC6A4

Q9Y6L6
Solute carrier organic anion transporter family member 1B1
SLCO1B1

P40763
Signal transducer and activator of transcription 3
STAT3

P59538
Taste receptor type 2 member 31
TAS2R31

P01137
Transforming growth factor beta-1
TGFB1

P01375
Tumor necrosis factor
TNF

P11388
DNA topoisomerase II alpha
TOP2A

P04637
Cellular tumor antigen p53
TP53

P17752
Tryptophan 5-hydroxylase 1
TPH1

P14679
Tyrosinase
TYR

P17643
5,6-dihydroxyindole-2-carboxylic acid oxidase
TYRP1

P15692
Vascular endothelial growth factor A
VEGFA

P47989
Xanthine dehydrogenase/oxidase
XDH

3.3. GO Analysis

For the filtered 182 target genes, 469 biological process terms with values of < 0.01 were sorted using the functional annotation chart of the DAVID 6.8 Gene Functional Classification Tool and values were adjusted using Benjamini-Hochberg method. This process resulted in the identification of 25 biological process terms. GO analysis showed that the 182 genes were highly related to inflammation, proliferation, oxidation reduction, and the regulations of apoptosis and signal transduction (Figure 2).

Figure 2: GO analysis: 25 biological process (BP) of gene ontology (GO) terms sorted by value < 0.01. Counts of genes and value related to each BP terms are shown. The -axis represents BP terms for the target genes, and the -axis shows counts of genes and ( value).

In detail, phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit, gamma isoform (PIK3CG), interleukin-6 (IL6), tumor necrosis factor (TNF), C-C motif chemokine 2 (CCL2), prostaglandin E2 receptor EP3 subtype (PTGER3), oxidized low-density lipoprotein receptor 1 (OLR1), prostaglandin G/H synthase 2 (PTGS2), and others are related to “inflammatory response.”

Androgen receptor (AR), interleukin-6 (IL6), heparin-binding growth factor 2 (FGF2), GTPase HRas (HRAS), hematopoietic cell protein-tyrosine phosphatase (PTPN6), and signal transducer and activator of transcription 3 (STAT3) are related to both the “positive regulation and negative regulation of cell proliferation.”

Xanthine dehydrogenase/oxidase (XDH), 5,6-dihydroxyindole-2-carboxylic acid oxidase (TYRP1), prostaglandin G/H synthase 2 (PTGS2), neutrophil cytosol factor 1 (NCF1), lanosterol 14-alpha demethylase (CYP51A1), amine oxidase [flavin-containing] A (MAOA), dual oxidase 2 (DUOX2), and others are associated with “oxidation-reduction process.”

Bcl-2-like protein 1 (BCL2L1), interleukin-6 (IL6), mitogen-activated protein kinase 8 (MAPK8), and cellular tumor antigen p53 (TP53) are associated with both the “positive regulation and negative regulation of apoptotic process.”

To summarize, it is likely that the therapeutic effect of PR in Crohn’s disease is due to its anti-inflammatory and repair process and immune system enhancing effects.

3.4. Network Construction and Analysis

To visualize more conveniently the multitargeted effects of PR, network analysis was used to investigate its actions within the context of the whole human genome [52, 53]. As shown in Figure 3, constructed (A) C-T and (B) T-P network demonstrated multicompound and multitargeted effects and relations between various pathways and targets. Circular nodes represent compounds and targets in the C-T network and triangles and circular nodes show pathways and compounds in the T-P network. In both networks, node size was regulated by degree centrality and edges showed interactions between nodes.

(a)

(b)

Figure 3: C-T network and T-P network: (a) is a compound-target (C-T) network, and nodes represent compounds and targets; and (b) shows a target-pathway (T-P) network, and circular nodes represent compounds and triangles pathways. Node size is related to the degree and edges demonstrate interactions between nodes.

The C-T network showed 415 interactions between the 182 targets and 32 active compounds of PR. Ursolic acid (C30, degree = 55) had the highest number of interactions with targets, followed by beta-sitosterol (C8, degree = 37) and isorhamnetin (C17, degree = 36), and, thus, these results demonstrated that single molecules can target multiple receptors [54]. Likewise, prostaglandin G/H synthase 2 (PTGS2, degree = 15) displayed the most affinitive connections with compounds, followed by prostaglandin G/H synthase 1 (PTGS1, degree = 13) and nuclear receptor coactivator 2 (NCOA2, degree = 11). According to betweenness centrality results, protein-tyrosine phosphatase 1B (PTPN1, betweenness = 0.11) was second highest followed by PTGS2 (betweenness = 0.12). 28 (88%) Of the 32 active compounds were connected with more than two targets and 86 (47%) of the 182 targets interact with more than one compound. This network analysis results clearly demonstrated the multitargeting natures of herbal compounds; besides it showed that ursolic acid (C30) is the most essential compound in PR.

In addition, 40 pathways related to Crohn’s disease were extracted to construct the T-P network. According to degree centrality, “pathways in cancer” (degree = 49) had the highest number of connections with the targets, followed by the “PI3K-Akt signaling pathway” (degree = 34) and “hepatitis B” (degree = 33). In the same manner, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA, degree = 33), phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit gamma isoform (PIK3CG, degree = 33), and nuclear factor NF-κB p65 subunit (RELA, degree = 25) demonstrate higher affinitive connections with pathways. Betweenness centrality and degree centrality results were similar; there was only little difference. “Pathways in cancer” (betweenness = 0.19) had the highest betweenness among the targets, which concurred with degree centrality, and this was followed by “neuroactive ligand-receptor interaction” (betweenness = 0.15) and “PI3K-Akt signaling pathway” (betweenness = 0.10). Regarding highest betweenness targets, PIK3CA (betweenness = 0.10), PIK3CG (betweenness = 0.10), and prostaglandin E2 receptor EP3 subtype (PTGER3, betweenness = 0.04) showed most affinitive connections with pathways.

3.5. Target Organ Location Network

The tissue mRNA expression profiles of target genes at the organ level were investigated to identify effects of PR on Crohn’s disease. No mRNA expression information of three of genes, muscarinic acetylcholine receptor M1 (CHRM1), G-protein coupled receptor TGR-1 (NMUR2), and taste receptor type 2 member 31 (TAS2R31), was found in the BioGPS. In total, the mRNA expression profiles of 179 of 182 genes were analyzed (Supplementary Table S2). 158 Of the genes displayed above average mRNA expressions in 17 relevant organ tissues, namely, in BDCA4+ dendritic cells, bone marrow, CD14+ monocytes, CD19+ B cells, CD33+ myeloid cells, CD34+ hematopoietic stem cells, CD4+ T cells, CD56+ NK cells, CD8+ T cells, colon, colorectal adenocarcinoma, liver, lymph nodes, lymphoblasts, small intestine, smooth muscle, and thymus. In addition, these 17 organ tissues, retina, prefrontal cortex, pineal, amygdala, cardiac myocyte, heart, whole blood, and other tissues, were also associated with relatively high mRNA expressions. Networks of the tissue mRNA expressions of 158 target genes and PR compounds are shown in Figure 4, nodes represent organs and genes, and node sizes indicate the number of interactions between nodes.

Figure 4: Target organ location network: the tissue-specific patterns of the mRNA expressions of targets in organs related to the immune system, colon, and small intestine. Nodes represent targets and organ locations. Node size is relative to the degree. Gene expression data was based on gene expression microarrays analysis results in BioGPS.

In detail, among 84 organ tissues, CD33+ myeloid showed the most overexpressed mRNA expression, 104 genes of 158 target genes were overexpressed in CD33+ myeloid, followed by 97 genes in lymphoblasts, 95 in each of smooth muscle and CD34+ hematopoietic stem cells, 91 genes in liver and CD56+ NK cell, 84 in bone marrow and colorectal adenocarcinoma, 82 in BDCA4+ dendritic cells, 75 in CD14+ monocytes, 73 in small intestine, 72 in CD4+ T cells, 70 in CD19+ B cells, 67 in colon, 38 in CD8+ T cells, 23 in thymus, and 22 in lymph nodes. It is evident that most genes were overexpressed in several organs at the same time.

Additionally, intestinal alkaline sphingomyelinase (ENPP7), DNA polymerase catalytic subunit (POLG), and carbonic anhydrase 13 (CA13) recorded beyond average mRNA expressions in all 17 organs. Furthermore, more than 146 (92%) of 158 target genes were overexpressed in two or more organ tissues, suggesting that these organs and compounds in PR are closely related. Furthermore, because the above 17 organs are highly related to immunity, our study results indicate that the therapeutic effects of PR on Crohn’s disease are due to its targeting and activating the immune system.

The other 21 target genes, such as acetylcholinesterase (ACHE), pancreatic alpha-amylase (AMY2A), and muscarinic acetylcholine receptor M3 (CHRM3), did not show above average mRNA expression in the 17 organs.

3.6. GEO2R Analysis

Comparison data between normal tissue and Crohn’s disease patients’ mRNA expression pattern from Gene Expression Omnibus (GEO) was collected. We employed GEOquery and limma R packages of GEO2R tool to identify highly expressed genes in 6 datasets. Dataset accession numbers are as follows: GSE24287, GSE60083, GSE6731, GSE36807, GSE68570, and GSE72780. To sum up, 86 normal samples and 149 Crohn’s disease samples were analyzed in each dataset. GEO2R presented the top 250 highly expressed genes in Crohn’s disease group compared to the control group and we deleted overlaps, so, in the end, 1182 genes were sorted out.

We found out that there were 23 common genes (Table 3) between target genes of PR and highly expressed genes of Crohn’s disease dataset from GEO.

Table 3: Highly expressed targets in Crohn’s disease.

UniProt ID
Target
Gene name

Q92887
Canalicular multispecific organic anion transporter 1
ABCC2

O60218
Aldo-keto reductase family 1 member B10
AKR1B10

P09917
Arachidonate 5-lipoxygenase
ALOX5

P62158
Calmodulin
CALM1

Q00534
Cell division protein kinase 6
CDK6

P10145
Interleukin-8
CXCL8

Q99814
Endothelial PAS domain-containing protein 1
EPAS1

P01100
Proto-oncogene c-Fos
FOS

P47869
Gamma-aminobutyric-acid receptor alpha-2 subunit
GABRA2

P49841
Glycogen synthase kinase-3 beta
GSK3B

P09601
Heme oxygenase 1
HMOX1

P05362
Intercellular adhesion molecule 1
ICAM1

P01584
Interleukin-1 beta
IL1B

P05231
Interleukin-6
IL6

P03956
Interstitial collagenase
MMP1

Q15788
Nuclear receptor coactivator 1
NCOA1

P35228
Nitric oxide synthase, inducible
NOS2

P01111
GTPase NRas
NRAS

P11309
Proto-oncogene serine/threonine-protein kinase Pim-1
PIM1

P61925
cAMP-dependent protein kinase inhibitor alpha
PKIA

P00749
Urokinase-type plasminogen activator
PLAU

P35354
Prostaglandin G/H synthase 2
PTGS2

P40763
Signal transducer and activator of transcription 3
STAT3

P17752
Tryptophan 5-hydroxylase 1
TPH1

3.7. Network Pathway

In order to investigate further the effect of PR in Crohn’s disease, we performed pathway enrichment analysis (Figure 5). Using the IBD pathway provided by the KEGG pathway database, we confirmed the pathway mapping effect of PR in Crohn’s disease by inputting the filtered human target genes into the pathway. The KEGG pathway was constructed according to the current knowledge of the pathogenesis IBD.

Figure 5: Network pathway: pathway enrichment analysis was performed. 182 filtered target genes were mapped into the Crohn’s disease pathway from the Kyoto Encyclopedia of Genes and Genomes (KEGG) to confirm the possible effect pathway of Pulsatillae Radix (PR) on Crohn’s disease.

The synthesis of inflammatory cytokines, such as IL-1, IL-6 and TNF-α, is mediated by NF-κB, which is a key regulator of inflammation [55, 56]. We found that oleanolic acid derivative (C22) targets IL-1; ursolic acid (C30) targets all of IL-1, IL-6, and TNF; isorhamnetin (C17), scoparone (C25), and ursolic acid (C30) target nuclear factor NF-κB p65 subunit (RELA); and scoparone (C25) and ursolic acid (C30) target NF-κB inhibitor alpha (CHUK), which suggests that these compounds affect NF-κB activity. Cernuoside (C12) targets IL-2. Beta-sitosterol (C8) targets transforming growth factor beta-1 (TGFB1) and transcription factor AP-1 (JUN), and ursolic acid (C30) also targets transcription factor AP-1 (JUN) and signal transducer and activator of transcription 3 (STAT3). Furthermore, NF-κB and AP-1 in combination are highly related to the initial inflammatory response and to the development of acquired immunity [57]. Moreover, IL-6-mediated STAT3 activation on mucosal T cells may has been suggested to play a role in the development of IBD [58].

4. Discussion

In this study, a network pharmacology method with active compounds filtration, multiple drug target prediction, gene ontology, network analysis, relevant organ location network, and pathway enrichment analysis were employed to determine the targets of PR in relation to Crohn’s disease. Our study shows that PR is highly connected to the pathways, biological processes, and organs of Crohn’s disease. A pharmacological approach was used to identify the actions of PR at the systems network level.

In this study, pathway mapping result showed that the target genes of PR overlap more with Crohn’s disease than with ulcerative colitis. Experimental study also suggested that the markers of both diseases are different from each other [59, 60]. The clinical symptoms of these diseases also differ; for instance, Crohn’s disease affect any region of the entire gastrointestinal (GI) tract and all layers of the bowel wall, whereas ulcerative colitis affects only the mucosa and submucosa of colon [61]. Furthermore, ulcerative colitis can be cured by surgery, but Crohn’s disease of any part of GI tract tends to relapse after surgery [62]. For this reason, long term management using herbal medicines might be highly recommendable treatment option for Crohn’s disease, since herbal medicines have advantages for managing chronic diseases [63, 64].

In addition, IBD is usually referred to as an autoimmune disorder [65], whereas Crohn’s disease does not meet the criteria of an autoimmune disorder; rather it is associated with immune deficiency or a secondary immune response to altered intestinal microbiota [65]. Furthermore, ulcerative colitis is a mucosal disease where autoimmune autoantibodies are commonly detected [66], whereas Crohn’s disease is a transmural disease, in which pathological changes in gut wall are thought to result from submucosal inflammatory changes [67]. Accordingly, the areas targeted for treatment in these two diseases should be differentiated.

In the present study, we focused on the use of PR as a potential therapy for Crohn’s disease. However, herb pairs and combinations are more commonly prescribed and are regarded to be more effective and safer [68]. In terms of the Gunsinjwasa theory of traditional medicine combinations, there are four different roles for each herb in the formula. First, the major component targets the main symptom. Second, the supportive component assists the effect of the major component or targets the secondary symptoms. Third, the neutralizing component allays the side effects or toxins of the major and the supportive component. Fourth, the deliver/retaining component guides the medicine to the targeting part of the body [69, 70]. This combination principle enables not only the enhancement of synergistic medicinal effects but also potentially reduces toxicities [69]. In order to induce better effects and reduce toxicities, an extended analysis of the Pulsatillae Radix (Baekduong, PR), Phellodendri Cortex (Hwangbaek), Coptidis Rhizoma (Hwangryeon), and Citrus reticulata (Jinpi) herb combination (a widely prescribed formula, known as Baekduong decoction) should be explored in the future.

Through GO analysis, we found out that targets of PR are associated with liver diseases such as hepatitis B, hepatitis C, and nonalcoholic fatty liver. In addition, the mRNA expression of 91 of 179 genes in liver was overexpressed according to the target organ location network result. Liver inflammation is as common extraintestinal symptom of Crohn’s disease [71], and the number of liver abscesses in Crohn’s disease patients is 15 to 20 times higher than that found in the general population [72]. Besides biochemical liver dysfunction [73] and hepatic fibrosis [74] are also frequently found in Crohn’s disease, and a number of drugs used to treat IBD have been reported to be associated with liver injury [75]. Furthermore, in an experimental study using a mice model of Crohn’s disease-like ileitis, it was found that TLR9 plays an important role in hepatic involvement in IBD [71]. More detailed pathways and relations between liver and Crohn’s disease should be discussed in the future.

This study demonstrated that 73 and 67 of 158 targets of PR were highly expressed in small intestine and colon, respectively, results which were accordance with not only the organs commonly affected by Crohn’s disease but also the properties of PR in terms of meridian tropism theory. However stronger evidence with another research design is required to support this result.

We confirmed a multicompound and multitarget interaction through the C-T network, which showed that 88% of the active compounds were connected with more than two targets and 47% of the targets interacted with more than one compound. Although it demonstrated the synergetic network of multitarget actions, we should explore more differentiated drug action based on degree centrality and how different the drug actions are when more compounds target one gene in simultaneous way compared to the case of one compound targeting one gene.

5. Conclusion

Previous studies indicate that most compounds in PR have anti-inflammatory, anticancer, and antioxidant effects. In the present study, we found that these compounds interact with multiple targets in a synergetic manner and that PR is highly connected to Crohn’s disease related pathways, biological processes, and organs. C-T and T-P network results demonstrated complex multicompound and multitarget drug actions and the relations between targets and various pathways. Furthermore, target genes were found to be overexpressed in organs highly related to immunity. These findings suggest the anti-inflammatory effects of PR, and its enhancements of repair processes and immune system might be of therapeutic benefit in Crohn’s disease.

Conflicts of Interest

The authors have no conflicts of interest to declare.

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01059994).

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