Composite ingredients of ZJP
A total of 156 chemical ingredients of the two herbal medicines in ZJP were collect from TCMSP, CASC and related literatures, including 32 ingredients in R. coptidis and 129 ingredients in E. rutaecarpa. There are 5 shared components: berberine, obacunone, quercetin, isovanillin, limonin (Fig.2A).
Putative targets of components
249 direct acting targets of Coptis chinensis and 357 direct acting targets of Evodia rutaecarpa were obtained. After removing repeated targets, 386 targets were obtained for subsequent analysis. And there were 220 overlapping targets between the two herbs (Fig.2B), which suggested that there might be interaction between Coptis chinensis and Evodia rutaecarpa in the treatment process.
The known therapeutic targets of UC
1458 targets of UC were obtained from DisGeNET database and 180 targets of UC obtained from OMIM database. A total of 1527 targets of UC were obtained after removing the repeats for subsequent analysis (Fig.2C). By comparing the components targets and the disease targets through the veen diagram, 146 targets for the treatment of UC were identified (Fig.2D). These targets may be the key proteins of ZJP in the treatment of UC.
(A) Distribution of active compounds among the herbs(C: Coptidis Rhizoma ingredients; E: Evodiae Fructus ingredients). (B) Distribution of potential targets among the herbs(C: Coptidis Rhizoma targets; E: Evodiae Fructus targets; S: Shared targets). (C) Distribution of the known therapeutic targets of UC from two databases. (D) Distribution of ZJP targets and the disease targets.
The ingredient-target-disease interactive network
In order to comprehensively reveal the possible effective ingredients and potential targets of ZJP against UC, the ingredient-target-disease interactive network was established with 542 nodes and 1953 edges (Fig.3), containing 156 ingredients and 386 targets. Nodes have larger degree values and more edges, which play a more pivotal role in network regulation. Accordingly, the network of ingredients with common targets of drugs and the disease was constructed to display the interactions between active compounds and potential targets directly. There were 696 edges and 302 nodes containing 156 ingredients and 146 common targets of drugs as well as disease in the network. The 146 common targets were regarded as potential targets in ZJP for the treatment of UC (Fig.4). Degree represented the total number of routes connected to this node by other nodes in the network. The higher value, the more important corresponding ingredient or target was. Table 1 showed that the ingredient with the highest degree was quercetin (degree = 82). The following compounds were isorhamnetin (degree = 25), caffeine (degree = 20), (R)-Canadine (degree = 19) and so on. In terms of targets, PTGS2 (degree = 95) was the most interacting ligands. The following targets were PTGS1 (degree = 73), ADRB2 (degree = 48), NOS3 (degree = 27) ,CALM1(degree =20) and so on. As a result, it was recognized that ZJP achieved the effect on UC mainly through the key targets above.
Tab.1.The top 5 ingredients in the ingredients and common targets network
Code name
|
Ingredient
|
Degree
|
Source
|
CR3
|
quercetin
|
82
|
Coptidis Rhizoma;Evodiae Fructus
|
R78
|
isorhamnetin
|
25
|
Evodiae Fructus
|
R50
|
caffeine
|
20
|
Evodiae Fructus
|
C6
|
(R)-Canadine
|
19
|
Coptidis Rhizoma
|
C22
|
Magnoflorine
|
18
|
Coptidis Rhizoma
|
The PPI network
To explore the mechanism of target genes of ZJP for the treatment of UC, the PPI network was constructed by STRING (confidence score ≥0.9) with 125 nodes and 645 edges (Fig.5). Based on the topological parameters, we identified 26 key targets (Tab.2). The outcomes demonstrated that the target protein levels of JUN, MAPK1, TNF, PIK3CA and RELA were excessively crucial in ZJP for UC (Fig.6).
Tab.2. Hub genes in PPI network
Gene name
|
Degree
|
Betweenness Centrality
|
closeness centrality
|
JUN
|
40
|
0.0866053
|
0.52765957
|
MAPK1
|
35
|
0.10522212
|
0.51239669
|
TNF
|
33
|
0.06737271
|
0.49206349
|
PIK3CA
|
32
|
0.09809998
|
0.49011858
|
RELA
|
31
|
0.04010596
|
0.50612245
|
AKT1
|
31
|
0.07469638
|
0.49011858
|
TP53
|
30
|
0.06701158
|
0.49011858
|
FOS
|
28
|
0.03619664
|
0.484375
|
SRC
|
27
|
0.05381998
|
0.496
|
IL6
|
27
|
0.05383839
|
0.484375
|
MAPK14
|
26
|
0.02930984
|
0.47328244
|
MAPK8
|
24
|
0.0236753
|
0.46096654
|
VEGFA
|
23
|
0.05077093
|
0.5
|
CTNNB1
|
22
|
0.03781139
|
0.46268657
|
EGFR
|
22
|
0.05992162
|
0.48627451
|
SP1
|
21
|
0.03912481
|
0.46441948
|
ESR1
|
21
|
0.00980253
|
0.47148289
|
CXCL8
|
21
|
0.06791767
|
0.44604317
|
MYC
|
20
|
0.00939055
|
0.46969697
|
IL1B
|
19
|
0.01687947
|
0.46441948
|
JAK2
|
19
|
0.01407263
|
0.45925926
|
IL2
|
18
|
0.00668683
|
0.45588235
|
IL4
|
17
|
0.01066433
|
0.44765343
|
SMAD3
|
17
|
0.01141516
|
0.43055556
|
STAT1
|
16
|
0.01339176
|
0.44927536
|
NR3C1
|
16
|
0.00783583
|
0.44765343
|
GO and KEGG enrichment analysis
To investigate the biological functions and pathway of the key targets of ZJP, the gene ontology (GO) biological process (BP) and KEGG were performed through the functional annotation tool of DAVID and Cytoscape3.7.1. The top 10 GO terms and pathways were significantly enriched respectively (Fig.7, 8).
In UC, the BPs mainly regulated by ZJP were signal transduction, response to drug, cellular response to lipopolysaccharide, MAPK cascade, inflammatory response, immune response, transcription from RNA polymerase II promoter, apoptotic process, regulation of sequence-specific DNA binding transcription factor activity and lipopolysaccharide-mediated signaling pathway.
In UC, the pathways mainly regulated by ZJP were Pathways in cancer, Chagas disease, Hepatitis B, Toll-like receptor signaling pathway, Influenza A, Proteoglycans in cancer, MAPK signaling pathway, HTLV-I infection, PI3K-Akt signaling pathway and Prolactin signaling pathway (Tab.3). Among them, the changes of Toll-like receptor signaling pathway, MAPK signaling pathway and PI3K-Akt signaling pathway are most closely related to UC.
Tab.3. Top 10 KEGG pathways of hub genes
Term
|
Count
|
%
|
PValue
|
Pathways in cancer
|
16
|
61.54
|
3.36E-13
|
Chagas disease
|
14
|
53.85
|
4.42E-18
|
Hepatitis B
|
14
|
53.85
|
3.88E-16
|
Toll-like receptor signaling pathway
|
13
|
50.00
|
4.12E-16
|
Influenza A
|
13
|
50.00
|
1.84E-13
|
Proteoglycans in cancer
|
12
|
46.15
|
2.98E-11
|
MAPK signaling pathway
|
12
|
46.15
|
3.79E-10
|
HTLV-I infection
|
12
|
46.15
|
3.96E-10
|
PI3K-Akt signaling pathway
|
12
|
46.15
|
1.02E-08
|
Prolactin signaling pathway
|
11
|
42.31
|
2.05E-14
|
Component-Target-Pathway Network
The key targets of ZJP in treatment of UC enriched to 3 signaling pathways. We constructed components-targets-pathways network with 7 directly linked components screened by ADME, 18 directly regulated targets and 3 UC-related signaling pathways (Fig.9). The network showed that these 7 molecules were involved in regulating toll-like receptor signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway. In this network, we identify directed molecules and targets (Tab.4). In order to further characterize the safety of these active ingredients, toxicity prediction of 7 active components in ZJP were shown in tab.5. Six of seven active components ingredients in ZJP, namely, Obacunone, quercetin, Palmidin A, beta-sitosterol, isorhamnetin and rutaecarpine which corresponded to the hub genes were identified (Fig.10). From the Fig.10, we can see that quercetin, shared by Coptidis Rhizoma and Evodiae Fructus, targets most of the hub genes.
Tab.4. Directly linked components screened by OB and DL.
Code name
|
Molecule Name
|
MW
|
OB (%)
|
DL
|
Linked targets
|
CR2
|
Obacunone
|
454.56
|
43.29
|
0.77
|
MAPK1,MAPK14
|
CR3
|
quercetin
|
302.25
|
46.43
|
0.28
|
AKT1,CXCL8,FOS,IL1B,IL2,IL6,JUN,MAPK1,MYC,PIK3CA,RELA,STAT1,TNF,TP53,VEGFA
|
C9
|
Palmidin A
|
510.52
|
35.36
|
0.65
|
MAPK1,PIK3CA
|
C10
|
Moupinamide
|
313.38
|
86.71
|
0.26
|
EGFR
|
R48
|
beta-sitosterol
|
414.79
|
36.91
|
0.75
|
JUN
|
R78
|
isorhamnetin
|
316.28
|
49.6
|
0.31
|
MAPK14,RELA
|
R102
|
rutaecarpine
|
287.34
|
40.3
|
0.6
|
TNF,IL4
|
Tab.5. Toxicity prediction of 7 active components in ZJP.
Code name
|
Molecule Name
|
Ames mutagenesis
|
Hepatotoxicity
|
Acute Oral Toxicity
|
Acute oral toxicity evaluation
|
CR2
|
Obacunone
|
--
|
+
|
51.827 mg / kg
|
Toxicity
|
CR3
|
quercetin
|
++
|
+
|
698.794 mg/kg
|
low
|
C9
|
Palmidin A
|
+
|
---
|
147.569 mg/kg
|
Toxicity
|
C10
|
Moupinamide
|
-
|
++
|
1603.37 mg/kg
|
low
|
R48
|
beta-sitosterol
|
---
|
---
|
273.371 mg/kg
|
Toxicity
|
R78
|
isorhamnetin
|
---
|
+
|
604.02 mg/kg
|
low
|
R102
|
rutaecarpine
|
---
|
++
|
624.265 mg/kg
|
low
|
Note: the “+” and “-” represent the predicted toxicity possibility. 0.1(---); 01-0.3(--); 0.3-05(-); 0.5-0.7(+); 0.7-0.9(++); 0.9-10(+++).Acute oral toxicity evaluation involves High-toxicity (1~50 mg/kg), Toxicity (51~500 mg/kg) and low-toxicity (501~5000 mg/kg).