Ischemic stroke (cerebral ischemia, CI) has become a major public health concern with morbidity, mortality, and health care costs [
Traditional Chinese medicine (TCM) has been shown to be beneficial in promoting developmental angiogenesis, which highlights “reinforcing qi to enrich the blood, dispelling stasis to promote regeneration” theory by associating with angiogenesis together. Radix Astragali (Huangqi) is the dry root of
Network pharmacology follows the dogma of “drug-targets-gene-disease,” to predict drug targets and improve the efficiency of drug discovery effort. Network pharmacology maintains integrity and systematic characteristic, similar to the principle of traditional Chinese medicine that involves multiple components and multiple targets [
Despite a few studies that have proved the protective effect of HH in the cerebral hemisphere, pharmacology-based prediction of complete profiling of bioactive components and the network of their target pathways has not fully been elucidated. Thus, in the present study, we have explored the proangiogenesis mechanisms of HH in the etiology of CI. In this study, we have established the herb-compound-target-disease (H-C-T-D) networks by utilizing the network pharmacology approach. Furthermore, to demonstrate angiogenesis, one key pathway of HH in cerebral protection, we have identified three key targets, which is highly associated with angiogenesis, through immunoblot assay. The workflow is shown in Figure
Workflow of network pharmacology analysis.
Information on the herbs and compounds related to HH were collected from two botanical chemistry databases: TCM Database of @Taiwan (
All compounds in HH were evaluated for their oral bioavailability (OB) and drug-likeness (DL). OB is one of the most common pharmacokinetic parameters in the drug screening process, which explains the percentage of an oral drug that remains unchanged after entering into the systemic circulation. In addition, OB provides a clue for the fusion of the ADME process. DL measures the extent of the “drug-like” property of a compound and determines whether the compound influences absorption, distribution, metabolism, and excretion (ADME) in the human body like an approved drug. In this study, chemicals only with an OB ≥30 and DL ≥0.18 (recommended by TCMSP database) were considered for further valuation [
UniProt (
The herb-compound-target-disease (H-C-T-D) networks were established using Cytoscape 3.3.0, JAVA software. Functional pathways annotation related to CI and enrichment evaluation was evaluated using the Kyoto Encyclopedia of Genes (KEGG), Genomes (GO), and the Database for Annotation, Visualization, and Integrated Discovery (DAVID) version 6.8 (
PPI data were collected from the Search Tool for the Retrieval of Interacting Genes (STRING) database (
HH granules (Huangqi : Honghua = 5 : 1, previous research has confirmed) were obtained from Guangdong Yifang Pharmaceuticals Co., Ltd. (product batch: 20170606). The rat brain microvascular endothelial cells (BMECs) were purchased from the Cell Biologics Company (#C57-6023, Chicago, IL). Primary antibodies against
Cells were divided into three groups: control group, OGD group, and OGD group treated with HH (100
BMECs were lysed with cold RIPA buffer (Rockford, IL, USA) for 30 min. The whole cell lysates were separated by 10% sepharose gel, and PVDF membranes (Millipore, USA) were used to transfer protein. The membranes were incubated with 5% bovine serum albumin (BSA) and overnight with primary antibodies against VEGFA (1 : 1000, rabbit), VEGFR2 (1 : 1000, rabbit), and eNOS (1 : 1000, rabbit) at 4°C. After that, membranes were incubated with secondary antibody at a 1 : 5000 dilution at 37°C for 1 h. After ECL-Plus reagent (Santa Cruz, USA) treatment, the blots were analyzed with Quantity One System image analysis software (Bio-Rad, USA).
The results were expressed as mean ± standard deviation (S.D.) and analyzed with one-way analysis of variance (ANOVA), followed by a Tukey’s post hoc test was used for analyzing differences between groups.
HH consists of a total of 276 compounds, 87 in Astragalus (Huangqi) and 189 in Safflower (Honghua). All 276 compounds were screened with OB and DL, out of which, only 42 compounds were recommended for the final screening. The remaining compounds were discarded. The therapeutic effect of a few selected compounds on CI was confirmed through the related literature search. Therefore, preselected active ingredients were added manually, including hydroxysafflor yellow A and astragaloside IV [
A list of the final selected compounds among the two herbal medicines for network analysis.
No. | Compound | OB (%) | DL | Herb |
---|---|---|---|---|
1 | Kaempferol | 41.88 | 0.24 | Safflower, astragalus |
2 | Quercetin | 46.43 | 0.28 | Safflower, astragalus |
3 | Lignan | 43.32 | 0.65 | Safflower |
4 | Phytoene | 39.56 | 0.5 | Safflower |
5 | Phytofluene | 43.18 | 0.5 | Safflower |
6 | Pyrethrin II | 48.36 | 0.35 | Safflower |
7 | 6-Hydroxykaempferol | 62.13 | 0.27 | Safflower |
8 | Baicalein | 33.52 | 0.21 | Safflower |
9 | Qt_carthamone | 51.03 | 0.2 | Safflower |
10 | Quercetagetin | 45.01 | 0.31 | Safflower |
11 | Beta-carotene | 37.18 | 0.58 | Safflower |
12 | Baicalin | 40.12 | 0.75 | Safflower |
13 | Beta-sitosterol | 36.91 | 0.75 | Safflower |
14 | Poriferast-5-en-3beta-ol | 36.91 | 0.75 | Safflower |
15 | Stigmasterol | 43.83 | 0.76 | Safflower |
16 | Luteolin | 36.16 | 0.25 | Safflower |
17 | CLR | 37.87 | 0.68 | Safflower |
18 | Hydroxysafflor yellow A | 4.77 | 0.68 | Safflower |
19 | Mairin | 55.38 | 0.78 | Astragalus |
20 | Jaranol | 50.83 | 0.29 | Astragalus |
21 | Hederagenin | 36.91 | 0.75 | Astragalus |
22 | Isorhamnetin | 49.6 | 0.31 | Astragalus |
23 | Bifendate | 31.1 | 0.67 | Astragalus |
24 | Formononetin | 69.67 | 0.21 | Astragalus |
25 | Isoflavanone | 109.99 | 0.3 | Astragalus |
26 | Calycosin | 47.75 | 0.24 | Astragalus |
27 | Astragaloside IV | 17.74 | 0.15 | Astragalus |
Linkage of target compounds and target genes. (a) The network of herbal medicine-compound in HH. (b) The Venn diagram of the compound genes and disease genes. (c) The Venn diagram of the target genes for safflower (Honghua) and astragalus (Huangqi). (d, e) The pharmacology networks of two herb medicines (red diamonds) which connect with target genes (blue ellipses) compounds (yellow ellipses).
The active ingredients of HH obtained from the screening assay were predicted using TCMSP and CTD database (
Nodes and edges of HH.
Safflower | Astragalus | |
---|---|---|
Compounds | 18 | 11 |
Targets of compounds | 409 | 304 |
Nodes | 391 | 292 |
Edges | 680 | 466 |
Number of maximum interactions | 159 | 159 |
Compounds of maximum interactions with target genes | Kaempferol | Kaempferol |
\Out of the 459 matching HH-associated genes and 274 CI-related genes, we streamlined 78 overlapping genes while constructing the gene network (Figure
A list of the compound and disease common target protein.
No. | Gene | Compounds |
---|---|---|
1 | PTGS2 | Lignan, pyrethrin II, 6-hydroxykaempferol, baicalein, qt_carthamone, quercetagetin, baicalin, kaempferol, luteolin, quercetin, jaranol, isorhamnetin, bifendate |
2 | TNF | Baicalein, beta-carotene, baicalin, kaempferol, luteolin, quercetin, hydroxysafflor yellow A, isorhamnetin, bifendate, Astragaloside IV, stigmasterol |
3 | CASP3 | Baicalein, beta-carotene, baicalin, beta-sitosterol, kaempferol, luteolin, quercetin, isorhamnetin, formononetin, astragaloside IV |
4 | NOS2 | 6-Hydroxykaempferol, baicalein, baicalin, kaempferol, luteolin, quercetin, jaranol, isorhamnetin, bifendate |
5 | RELA | Safflower, baicalein, baicalin, kaempferol, luteolin, quercetin, isorhamnetin, bifendate, astragaloside IV |
6 | PPARG | 6-Hydroxykaempferol, baicalein, quercetagetin, baicalin, kaempferol, quercetin, hydroxysafflor yellow A, isorhamnetin, formononetin |
7 | IL6 | Baicalin, kaempferol, luteolin, quercetin, hydroxysafflor yellow A, isorhamnetin, bifendate, astragaloside IV |
8 | BCL2 | Baicalein, beta-carotene, beta-sitosterol, kaempferol, luteolin, quercetin, isorhamnetin, formononetin |
9 | NFKBIA | Baicalein, baicalin, kaempferol, luteolin, quercetin, isorhamnetin, formononetin, astragaloside IV |
10 | IL1B | Baicalein, beta-carotene, baicalin, kaempferol, luteolin, quercetin, isorhamnetin, astragaloside IV |
11 | CAT | Beta-carotene, beta-sitosterol, kaempferol, luteolin, quercetin, isorhamnetin, bifendate |
12 | MAPK1 | Calycosin, beta-carotene, baicalein, luteolin, kaempferol, quercetin |
13 | CASP9 | Beta-sitosterol, kaempferol, luteolin, quercetin, isorhamnetin, formononetin |
14 | MAPK3 | Baicalein, beta-carotene, kaempferol, luteolin, quercetin, calycosin |
15 | TP53 | Baicalin, luteolin, quercetin, formononetin, kaempferol, beta-carotene |
16 | PARP1 | Beta-sitosterol, kaempferol, luteolin, quercetin, isorhamnetin |
17 | JUN | Baicalein, beta-carotene, kaempferol, luteolin, quercetin |
18 | VEGFA | Baicalein, kaempferol, luteolin, quercetin, calycosin |
19 | NFE2L2 | Kaempferol, luteolin, quercetin, astragaloside IV |
20 | SOD1 | Kaempferol, luteolin, quercetin, astragaloside IV |
21 | MMP9 | Baicalein, luteolin, quercetin, hydroxysafflor yellow A |
22 | ICAM1 | Kaempferol, luteolin, quercetin, hydroxysafflor yellow A |
23 | SOD2 | Beta-carotene, kaempferol, quercetin, astragaloside IV |
24 | NOS3 | Luteolin, isorhamnetin, formononetin, quercetin |
25 | CSF2 | Baicalein, kaempferol, luteolin, quercetin |
26 | CYCS | Baicalein, beta-sitosterol, quercetin, kaempferol |
27 | MPO | Baicalein, luteolin, quercetin, astragaloside IV |
28 | HIF1A | Kaempferol, luteolin, quercetin, formononetin |
29 | APP | Baicalein, kaempferol, quercetin |
30 | IL10 | Stigmasterol, luteolin, bifendate |
31 | CCL2 | Kaempferol, luteolin, quercetin |
32 | FOS | Kaempferol, luteolin, quercetin |
33 | NFKB1 | Baicalein, luteolin, quercetin |
34 | STAT3 | Luteolin, baicalein, quercetin |
35 | AGT | Isorhamnetin, quercetin |
36 | CD40 | Luteolin, hydroxysafflor yellow A |
37 | EGR1 | Luteolin, quercetin |
38 | CXCL10 | Luteolin, quercetin |
39 | SELE | Kaempferol, luteolin |
40 | CEBPB | Baicalein, quercetin |
41 | TLR4 | Baicalin, quercetin |
42 | EPO | Formononetin, calycosin |
43 | SERPINE1 | Isorhamnetin, quercetin |
44 | JAK2 | Quercetin |
45 | CCL3 | Isorhamnetin |
46 | NR3C2 | CLR |
47 | CALM1 | Lignan |
48 | RB1 | Baicalein |
49 | IGF1 | Baicalein |
50 | APOE | Kaempferol |
51 | BBC3 | Kaempferol |
52 | ATM | Kaempferol |
53 | CD14 | Kaempferol |
54 | H2AFX | Kaempferol |
55 | RIPK1 | Kaempferol |
56 | VDR | Kaempferol |
57 | PLAU | Baicalein |
58 | ADIPOQ | Beta-carotene |
59 | GOT1 | Baicalin |
60 | PIK3CG | 6-Hydroxykaempferol |
61 | HSPA1A | Quercetin |
62 | FOSB | Luteolin |
63 | GFAP | Luteolin |
64 | GPX1 | Luteolin |
65 | HBEGF | Luteolin |
66 | IL17A | Luteolin |
67 | JUNB | Luteolin |
68 | JUND | Luteolin |
69 | DDIT3 | Quercetin |
70 | SIRT1 | Quercetin |
71 | HMGB1 | Quercetin |
72 | ALB | Quercetin |
73 | PLAT | Quercetin |
74 | CREB1 | Quercetin |
75 | ACE | Luteolin |
76 | AGER | Luteolin |
77 | SP1 | Quercetin |
78 | POU5F1 | Kaempferol |
The herb-compound-gene network for HH.
To explore the signaling pathway and functions of the identified target genes, 78 candidate targets were analyzed by GO and enriched by the KEGG pathway. The top 6 enriched conditions were found to be involved in the biological process (BP), cell component (CC), and molecular function (MF) (Figure
KEGG pathway and GO analysis by DAVID database. (a) GO analysis of candidate targets. Database showed the five remarkably enriched items in the biological processes (BP), cell component (CC), and molecular function (MF). (b) KEGG pathways of target genes. (c) Main functional annotation clusters by biocarta analysis.
Functions of potential target genes based on KEGG pathway analysis.
Pathway ID | Pathway classification | Term | Number of pathway genes | |
---|---|---|---|---|
hsa04668 | Signal transduction | TNF signaling pathway | CCL2, CXCL10, CEBPB, FOS, JUN, JUNB, NFKBIA, RELA, CREB1, CASP3, CSF2, ICAM1, IL1B, IL6, MMP9, MAPK1, NFKB1, PIK3CG, PTGS2, RIPK1, SELE, TNF | 1 |
hsa04620 | Immune system | Toll-like receptor signaling pathway | CCL3, CXCL10, CD14, CD40, FOS, JUN, NFKBIA, RELA, IL1B, IL6, MAPK1, NFKB1, PIK3CG, RIPK1, TLR4, TNF | 2.1 |
hsa04066 | Signal transduction | HIF-1 signaling pathway | BCL2, RELA, EPO, HIF1A, IGF1, IL6, MAPK1, NOS2, NOS3, NFKB1, PIK3CG, SERPINE1, STAT3, TLR4, VEGFA | 9.2 |
hsa04064 | Signal transduction | NF-kappa B signaling pathway | ATM, BCL2, CD14, CD40, NFKBIA, RELA, ICAM1, IL1B, NFKB1, PLAU, PTGS2, RIPK1, TLR4, TNF | 4.7 |
hsa04210 | Cell growth and death | Apoptosis | ATM, BCL2, NFKBIA, RELA, CASP3, CASP9, CYCS, NFKB1, PIK3CG, RIPK1, TNF, TP53 | 3.4 |
hsa04660 | Immune system | T-cell receptor signaling pathway | FOS, JUN, NFKBIA, RELA, CSF2, IL10, MAPK1, NFKB1, PIK3CG, TNF | 0.0000010 |
hsa04010 | Signal transduction | MAPK signaling pathway | CD14, DDIT3, FOS, JUN, JUND, RELA, CASP3, HSPA1A, IL1B MAPK1, MAPK3, NFKB1, TNF, TP53 | 0.0000023 |
hsa04115 | Cell growth and death | p53 signaling pathway | ATM, BBC3, CASP3, CASP9, CYCS, IGF1, SERPINE1, TP53 | 0.0000065 |
hsa04068 | Signal transduction | FoxO signaling pathway | ATM, CAT, IGF1, IL10, IL6, MAPK1, PIK3CG, STAT3, SIRT1, SOD2 | 0.0000120 |
hsa04151 | Signal transduction | PI3K-Akt signaling pathway | BCL2, JAK2, RELA, CREB1, CASP9, EPO, IGF1, IL6, MAPK1, NOS3, NFKB1, PIK3CG, TLR4 | 0.0000140 |
hsa04722 | Nervous system | Neurotrophin signaling pathway | BCL2, JUN, NFKBIA, RELA, CALM1, MAPK1, NFKB1, PIK3CG, TP53 | 0.0000390 |
hsa04370 | Signal transduction | VEGF signaling pathway | CASP9, MAPK1, MAPK3, NOS3, PIK3CG, PTGS2, VEGFA | 0.0000440 |
hsa04623 | Immune system | Cytosolic DNA-sensing pathway | CXCL10, NFKBIA, RELA, IL1B, IL6, NFKB1, RIPK1 | 0.0000580 |
hsa04662 | Immune system | B-cell receptor signaling pathway | FOS, JUN, NFKBIA, RELA, MAPK1, NFKB1, PIK3CG | 0.0000890 |
hsa04062 | Immune system | Chemokine signaling pathway | CCL2, CCL3, CXCL10, JAK2, NFKBIA, RELA, MAPK1, NFKB1, PIK3CG, STAT3 | 0.0001500 |
hsa04060 | Signaling molecules and interaction | Cytokine-cytokine receptor interaction | CCL2, CCL3, CXCL10, CD40, CSF2, EPO, IL1B, IL10, IL17A, IL6, TNF | 0.0002500 |
hsa04024 | Signal transduction | cAMP signaling pathway | FOS, JUN, NFKBIA, RELA, CREB1, CALM1, MAPK1, NFKB1, PIK3CG | 0.0012000 |
hsa04630 | Signal transduction | JAK-STAT signaling pathway | JAK2, CSF2, EPO, IL10, IL6, PIK3CG, STAT3 | 0.0045000 |
In the PPI relationships network, we found 78 nodes and 1429 edges (Figure
Protein-protein interaction (PPI) networks of active ingredients of HH for the treatment of cerebral ischemia. (a) Each node represents the relevant gene, the edge. Means line thickness indicates the strength of data support. (b) Center top 20 genes in the PPI network, the darker the color, the higher the score.
To confirm the results from the network and to verify that angiogenesis is indeed one of the key pathways of HH in cerebral protection, we selected three targets related to angiogenesis (VEGFA, VEGFR2, and eNOS) for pharmacological validation (Figure
Effects of HH on the levels of VEGFA, VEGFR2, and eNOS in BMECs. (
Multicompound TCMs, with multiple biological targets, are the prime focus in Chinese clinical practice for more than thousand years. Surprisingly, TCMs are known to target multiple biological pathways to defend against diseases. However, the traditional method of usage of TCMs barely provides insights into the biological complexity of compounds, its biological targets, and associated disease, which limits the development and reformulation of TCMs. Lately, network pharmacology approach of analyzing TCMs gains more popularity that dissects the pharmacological mechanism of action [
In the current study, a network pharmacology analysis of HH identified 2 herbs, 21 compounds, as well as 78 target gene-regulated major pathways associated with CI. Through the pathway enrichment analysis, we found that the targets of active ingredients in HH against cerebral ischemia injury mainly participate in numerous signal transduction pathways such as TNF signaling pathway, toll-like receptor signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and VEGF signaling pathway. These key pathways may regulate anti-inflammatory, antiapoptotic, immune correlation, and antioxidative effects. Furthermore, the PPI system analysis indicates these genes played vital roles in CI (Figure
According to the TCM theory, Qi and blood dysfunction is one key pathogenesis of CI. In the clinic, Qi-tonifying drugs, blood-activating drugs, and reinforcing Qi and activating blood drugs team were usually treated for CI with significant efficacy. A fewer side effects [
Angiogenesis is similar to “reinforcing qi to enrich blood, Dispelling stasis to promote regeneration” theory and regulated by angiogenesis inducers and inhibitors. Angiogenesis involves basilar membrane degradation, chemotactic migration, and proliferation of EC (endothelial cell) and EPC (endothelial progenitor cell). In the PPI system analysis, top 20 center genes were recognized, and among these genes, VEGFA and eNOS are highly correlated with angiogenesis. Over the few decades, vascular endothelial growth factors (VEGFs) and their receptors (VEGFRs) have been regarded as the principal drivers of angiogenesis and the development and maintenance of vascular system [
According to the KEGG pathway analysis, these three target genes interact mainly with HIF-1 signaling pathway and VEGF signaling pathway. Low oxygenation concentrations in tissues (hypoxia) often trigger angiogenesis [
In summary, network pharmacology analysis of HH identified 2 herbs, 21 compounds, and 78 target gene-regulated major pathways associated with CI. The bioactive compounds in HH mainly participate in numerous signal transduction pathways such as TNF signaling pathway, toll-like receptor signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and VEGF signaling pathway, and these important pathways may regulate anti-inflammatory, antiapoptotic, immune correlation, and antioxidative effects. Furthermore, through the pharmacological experiment, we predict that HH can regulate VEGFA, VEGFR2, and eNOS via the HIF-1 signaling pathway and VEGF signaling pathway to promote angiogenesis and alleviate cerebral ischemia injury.
Huangqi-Honghua herb pair
Cerebral ischemia
Traditional Chinese medicine
Absorption, distribution, metabolism, and excretion
Brain microvascular endothelial cells
Oxygen-glucose deprivation
Herb-compound-target-disease networks
Kyoto Encyclopedia of Genes
Genomes
Protein-protein interaction.
The data used to support the findings of this study are included within the article.
The authors declare that they have no conflicts of interest.
C. J., L. L., W. K., S. J., W. J., W. A., and Y. Z. designed the experiments; C. J., L. L., W. K., Q. Y., D. J., and Z. C. conducted experiments and researched literature; C. J., L. L., C. J., and F. Z. collected and analyzed the data; C. J. and W. K. wrote the manuscript; C. J., L. L., W. K., D. J., and Y. Z. revised the manuscript. All authors commented on the results and approved the final manuscript. Jinyi Cao, Lu Lei, Kai Wang, and Jing Sun contributed equally to this work.
This research was funded by the National Natural Science Foundation of China (nos. 81503280, 81573549, 81603320, and 81603350).