Network pharmacology and in vitro studies show the pharmacological effects and molecular mechanisms of salidroside against coronary artery disease

doi:10.21203/rs.3.rs-2268351/v1

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Network pharmacology and in vitro studies show the pharmacological effects and molecular mechanisms of salidroside against coronary artery disease

https://doi.org/10.21203/rs.3.rs-2268351/v1

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Background

Salidroside (Sal) has many pharmacological effects, including anti-fatigue, anti-aging, immunoregulation and so on. However, its effects and related regulatory mechanisms on coronary artery disease (CAD) are elusive. We hypothesize that Sal may play a role in CAD through autophagic pathway. Herein, we used autophagy agonist (sirolimus, Sir) and inhibitor (chloroquine diphosphate, CQ) as the autophagic control group. And network pharmacology prediction was employed to explore the pharmacological effects and molecular mechanisms of Sal on CAD using network pharmacology prediction, and validated the results through in vitro experiments.

Methods

Through a search in the Swisstarget Prediction database, chemical composition and targets were retrieved. The related-autophagic targets for CAD were then obtained from the GEO and human autophagy databases. The network was constructed that depicted the interactions between putative drugs (Sal, Sir and CQ) and known related-autophagic targets for CAD using Cytoscape 3.8.0. Analysis of protein-protein interaction (PPI) was achieved via STRING software, followed by gene ontology (GO) functional enrichment and kyoto enrichment of gene and genome (KEGG) pathway analyses. The 3D structure of target protein was downloaded from RSCB PDB database, the 2D structure of drug was obtained from PubChem database, then the molecular docking was constructed by using AutoDockTools 1.5.6 and AutoDock Vina software, and the results were visualized by using PyMoL sofeware. To validate the computer-predicted results, in vitro experiments based on an anoxic injury model were designed by using CoCl₂-exposed H9C2 cells, and treated with various concentrations of Sal/Sir/CQ. The effects of drugs on cells were detected by using the CCK-8, inverted microscope (IM), transmission electron microscope (TEM), MDC staining and AO staining. Moreover, the expression profiles of related-proteins were analyzed via western blot.

Results

Three compounds were identified a total of 399 targets, GEO revealed a total of 576 CAD-related genes, and 36 overlapping genes of drug-disease were obtained. The PPI network was employed for the analysis of 36 target proteins, including CASP3, mTOR, VEGFA and EGFR. The enrichment analysis demonstrated candidate targets of three compounds were more frequently involved in inflammation, lipid response, oxidative stress, autophagy, apoptosis, diabetic cardiomyopathy and estrogen signaling pathways. In vitro experiments revealed that Sal could induce autophagy in CoCl2-exposed H9C2 cells, significantly reverse cell death in the early period, and decrease the levels of Caspase-3 protein in CoCl₂-exposed H9C2 cells. However, Sal-induced autophagy also could promoted the process of CoCl₂-exposed H9C2 cells death in the late period.

Conclusions

This study revealed that Sal existed the effect of treating CAD by regulating multi-targets and multi-channels through the method of network pharmacology. Furthermore, in vitro results confirmed that Sal-induced autophagy played a protective role in the early period of CAD, while aggravated the condition in the late period of CAD.

Salidroside

Myocardial infarction

Network pharmacology

Autophagy

Potential targets

In vitro study

Coronary artery disease (CAD) is one of the most dangerous diseases in the world, and has high morbidity and mortality, which brings about a large burden on society and patients’ families [1, 2]. From the pathogenesis, CAD is mainly caused by coronary atherosclerosis lumen stenosis, obstruction or (and) coronary artery spasm, leading to myocardial ischemia, hypoxia or necrosis caused by heart disease [3]. At present, according to the degree of coronary artery stenosis, it can be divided into three treatment methods, including pharmacological intervention, percutaneous coronary intervention (PCI) and coronary artery bypass graft [4, 5]. Although there are many treatments available, their effectiveness is still limited. Hence, the development of therapy for CAD has become an essential but unmet need. A large number of experimental researches and clinical observations have verified that Chinese medicine has unique advantages in the treatment of CAD. Various empirical prescriptions and active ingredient extracts have shown clear protective effects on CAD [6–8].

Salidroside (Sal) is a phenylethanol compound extracted from the root of traditional Chinese medicine (TCM) rhodiola rosea L. In previous pharmacological study, it has been found many functions, such as anti-oxidation [9], anti-aging [10], anti-hypoxia [11], anti-cancer [12] and so on. Thus, the application of Sal has a good development prospect. Recent studies have also found that Sal has a variety of pharmacological effects in cardiovascular disease, including anti-arteriosclerosis, anti-inflammatory, anti-myocardial infarction and so on [13–15]. However, reports about the therapeutic effects and mechanisms of action of Sal on CAD are scanty. The molecular mechanism of Sal has not been certainly clear.

Network pharmacology technologies have been proven to be a powerful way for mechanistic exploration of Chinese medicine from the perspective of multi-components, multi-targets, and multi-channels, which is consistent with the holistic view of Chinese medicine [16, 17]. This study was aimed to explore the potential molecular mechanisms of Sal in treating CAD by using network pharmacology technologies and its effect on CoCl₂-induced injury by in vitro experiment based on network pharmacology prediction. We hope to these findings can provide a new scientific basis for the future development of Sal. A flowchart of the experimental procedures of this study is outlined in Fig. 1.

Figure 1 The flowchart of network pharmacology-based strategies for investigating the mechanisms of acting on CAD.

Predicting drugs therapeutic targets and CAD significant targets

The 2D structures of Sal, chloroquine diphosphate (CQ), and sirolimus (Sir) were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). And these structures were uploaded to the Swisstarget Prediction database (http://www.Swiss-Target-tprediction.ch/) and the Pharmmapper server platform (http://www.lilab-ecust.cn/pharmmapper/) for docking targets, so as to identify the candidates of potential target in the two databases. To explore whether drugs can treat CAD via targeting autophagy, we downloaded the original CEL data of CAD from the GEO database (http://www.ncbi.nlm.nih.gov/GEO/). After patients with incomplete data were excluded, the remaining patients were included in the analysis. A list of 576 autophagy-related genes was obtained from human autophagy database (http://www.autophagy.lu/index.html). Subsequently, the analysis of differential expression was performed by using “limma” R package. And the screening conditions were log2 fold change (logFC) > 1, false discovery rate (FDR) < 0.05. After autophagy-related genes were identified, an intersection between the active targets of drugs and CAD significant targets was determined through Venny 2.1.0 software.

Network construction and analysis

The drugs, active components and intersecting targets of drug-disease were input into Cytoscape 3.8.0 software, and the network figure of “drug-component-target-disease” was constructed. The network topology analysis was achieved using a cytoNCA plugin, after which a protein-protein interaction (PPI) network was constructed via the STRING (https://string-db.org/) software. The obtained data were imported into the Cytoscape 3.8.0 software for analysis, and the core genes of the network were found to generate a graph.

Analysis of gene ontology (GO) function enrichment and kyoto enrichment of genes and genomes (KEGG) pathway

GO functional enrichment and KEGG pathway enrichment analyses were conducted using the R language package (bioconductor package) to explore gene functions and uncover potential therapeutic targets of Sal/Sir/CQ. The Analysis of pathways provided scientific connotation for Sal/Sir/CQ.

Analysis of molecular docking

The 3D structure of the target protein was downloaded from the RSCB PDB database (http://www.rcsb.org/), the water and impurities of the protein were removed via using PyMOL software. The 2D structure of the active components in drugs was downloaded from the PubChem database (https://PubChem.ncbi.nlm.nih.gov/), which was converted into a 3D structure through the Chem 3D software. Subsequently, the target protein and small molecule were hydrogenated by AutoDockTools 1.5.6 software, and the Grid Box was established with original ligand as the center. After the data was obtained, the AutoDock Vina was used for molecular docking, and the results were visualized by PyMoL software.

Materials and reagents for biological experiments

Sal (purity: 99.56%), CQ (purity: 99.65%) and Sir (purity: 99.30%) were obtained from Selleck (Houston, USA). DMEM medium and phosphate buffered saline (PBS) were purchased from Hyclone (Logan, USA). Trypsin-EDTA solution, 1% osmium tetroxide, saturated uranyl acetate, lead citrate, MDC staining kit, radioimmunoprecipitation assay (RIPA), phenylmethylsulfonyl fluoride (PMSF), SDS-PAGE gel preparation kit, Tween-20, 10x TBS, 20x Tris-HCl buffered saline, 10x transfer buffer, BCA protein assay kit and 4x bromophenol blue buffer were purchased from Solarbio (Beijing, China). Penicillin-streptomycin was purchased from BasalMedia (Shanghai, China). Fetal bovine serum (FBS) was purchased from BI (Grand Island, USA). 4% paraformaldehyde, 2.5% paraformaldehyde and extra-enhanced chemiluminescence substrate kit were purchased from Biosharp (Beijing, China). Cell counting kit − 8 (CCK-8) kit and three-color pre-stained protein marker were purchased from YEASEM (Shanghai, China). 95% absolute ethanol was purchased from DAMAO (Tianjin, China). Non-fat milk was purchased from Biotopped (Beijing, China). Anti-GAPDH and anti-HIF-1α antibody were purchased from Gene Tex (respectively, cat. no. GTX109639 and GTX30105; Los Angeles, USA). Anti-Bax, anti-Bcl-2, anti-Caspase-3 and anti-Beclin-1 antibody were purchased from Proteintech (respectively, cat. no. 60267-1-Ig, 12789-1-AP, 19677-1-AP and 1C10C4; Proteintech; Chicago, USA). Anti-LC3B-I/II was purchased from Abcam (cat. no. ab192890; Cambridge, UK). Horseradish peroxidase (HRP)-conjugated goat anti-rabbit secondary antibody was purchased from Zhongshan Golden Bridge (cat. no. ZB-2301; Beijing, China).

Cell culture and modeling intervention

Rat H9C2 cardiomyocytes were obtained from the cell bank of Shanghai institute of biological sciences (SIBS, Shanghai, China). Cells were cultured in DMEM complete medium at 95% humidity, 5% cardon dioxide (CO₂), and a temperature of 37°C. To mimic hypoxic conditions, cells were treated with various concentrations of CoCl₂ (200, 400, 600, 800 or 1,000 µmol/L) for different periods of time (0, 3, 6, 12 and 24 h).

Treatment with Sal, Sir and CQ

To evaluate the safety of Sal, H9C2 cells were treated with various concentrations of Sal (10, 20, 40 and 80 µmol/L) for 24 h. To investigate the protective effects of Sal on CoCl₂ injury, CoCl₂-exposed H9C2 cells were treated with Sal (10, 20, 40 and 80 µmol/L) for 24 h. H9C2 cells were incubated in normoxic medium (DMEM, 10% FBS, and 1% penicillin-streptomycin solution) in an incubator with 5% CO₂ at 37°C served as the blank group. To inhibit autophagy, H9C2 cells were incubated with autophagy inhibitor CQ (5 µmol/L) for 24 h. To induce autophagy, H9C2 cells were incubated with autophagy agonist Sir (400 nmol/L) for 24 h.

Cell viability and cell death assays

Cell viability was assessed using a CCK-8 kit according to the manufacturer's protocol. Briefly, H9C2 cells were added to 96-well plates (5 X 10³ cells/well) and cultured. Following treatment as described above, the media from each group were replaced with serum-free DMEM (90 µl) plus CCK-8 reagent (10 µL), and incubated for 1 h at 37°C. The absorbance was measured at 450 nm using a microplate reader (Bio-Rad Corporation, New York, USA). Cell viability as a percentage was calculated by comparing the value of the treated group to that of the blank group. Moreover, to observe the effect of drugs on the morphology of H9C2 cells, the cells in blank group and treated cells were wished twice with PBS and fixed with 4% paraformaldehyde at room temperature for 30 min. After the cells were wished again twice with PBS, the images were obtained using an inverted microscope (IM, Olympus Corporation, Tokyo, Japan).

Cell autophagy using transmission electron microscope (TEM)

H9C2 cells were fixed with 2.5% paraformaldehyde for 90 min and 1% osmium tetroxide for 30 min at 37˚C. After gradient dehydration with 95% absolute ethanol, the cells were embedded, sectioned and stained with saturated uranyl acetate and lead citrate. Observations and photographs were obtained using a TEM (Hitachi Corporation, Tokyo, Japan).

MDC staining and AO staining

The H9C2 cells were cultured in 12-well glass-covered chamber slides and then treated with related drug. Following treatment, the cells were wished twice with PBS, incubated with MDC or AO dye for 15 min at 37˚C in the dark and fixed with 4% paraformaldehyde for 30 min. After the cells were wished again twice with PBS, stained cells were observed using a fluorescence microscope ( Olympus Corporation, Tokyo, Japan).

Western blot analysis

The treated H9C2 cells were lysed using RIPA lysis buffer containing 1 mM PMSF and centrifuged at 12,000 g for 15 min at 4˚C. The concentration of proteins was determined using a BCA kit. Equivalent quantities of proteins (40 µg) were loaded on a 10% or 15% SDS-PAGE gel. After the proteins reached the bottom of SDS-PAGE gel, the imprints of proteins were transferred to PVDF membranes. Blocking with 5% non-fat milk in TBS containing 0.01% Tween-20 (TBST) for 2 h at 4˚C, the membranes were incubated with the following primary antibodies: Anti-GAPDH antibody (1:5,000), anti-Bax antibody(1:1,000), anti-Bcl-2 antibody (1:1,000), anti-Caspase-3 antibody (1:1,000), anti-LC3B-I/II antibody(1:500), anti-Beclin-1 antibody (1:2,000) and anti-HIF-1α antibody (1:1,000) at 4˚C overnight. After washing twice with TBST, the membranes were incubated with HRP-conjugated goat anti-rabbit secondary antibody (1:5,000) at room temperature for 2 h. Finally, the bands were visualized using extra-enhanced chemiluminescence reagent. Densitometric analysis was performed using the Microscopic Imaging system and Image Lab software (Bio-Rad Corporation, New York, USA).

Statistical analysis

All data were analyzed using GraphPad Prism 8.0.2 software (GraphPad Software, San Diego, USA) and SPSS 22.0 software (SPSS Inc., Chicago, USA). Each experiment included at least three independent experiments. Data were expressed as the means ± standard deviation (SD). Differences between multiple groups were compared using a one-way ANOVA analysis. P < 0.05 was considered to indicate a statistical difference, P < 0.01 was considered to indicate a significant difference. P > 0.05 was considered to indicate no statistical difference.

Predicted targets for three compounds, CAD significant and therapeutic targets

Names of component targets in three compounds were corrected using the Swisstarget Prediction database, after which repeated targets were eliminated. Eventually, 107, 241, 100 potential targets for Sal, Sir and CQ were obtained respectively (Fig. 2A-C). From the GEO and human autophagy databases, 576 autophagy-related therapeutic genes of CAD were acquired. Moreover, the volcano map and heat map analysis of the 576 genes revealed that 226 up-regulated and 350 down-regulated genes (Fig. 2D and E). Integrating potential targets of three compounds with those of CAD revealed exactly 36 therapeutic targets (Fig. 2F).

Figure 2 The scheme of overlapped targets between Sal/Sir/CQ potential targets and CAD targets was constructed. (A) The network diagram of Sal-related targets. (B) The network diagram of Sir-related targets. (C) The network diagram of CQ-related targets. (D) Volcano diagram of CAD-related differential genes in the GSE71226 dataset. (E) Heat diagram of CAD-related differential genes in GSE71226 dataset. (F) The venn diagram of overlapped targets between Sal/Sir/CQ targets and CAD targets.

Network construction and analysis

The “drug-target-disease” network of Sal, CQ and Sir for CAD was successfully constructed via Cytoscape 3.8.0 software for topological analysis. As shown in Fig. 3, it comprised 40 nodes and 78 edges; a red rectangle represented disease (1), a purple diamond depicted active compounds (3), and a blue triangle denoted therapeutic targets (36).

Figure 3A network of active compounds-CAD targets. Red node stands for CAD, purple nodes stand for active compounds (including Sal, Sir and CQ), blue nodes represent the shared targets between Sal potential targets and CAD targets.

36 therapeutic targets were input into the STRING software, so as to generate targets-related data. Subsequently, network topology analysis and calculations were performed via Cytoscape 3.8.0 software, for the construction of a PPI network (Fig. 4A). Based on the degree of the nodes, we identified 5 core targets, including GAPDH, CASP3, MTOR, VEGFA, and EGFR (Fig. 4B and Table 1).

Table 1

Specific information on the 5 core goals.
NO.	Name	Protein name	Degree
1	GAPDH	Glyceraldehyde-3-phosphate dehydrogenase	21
2	CASP3	Caspase-3	20
3	MTOR	Serine/threonine-protein kinase mTOR	20
4	VEGFA	Vascular endothelial growth factor A	18
5	EGFR	Epidermal growth factor receptor	16

Figure 4 Topological analysis of the target proteins of CAD and active compounds (Sal, Sir and CQ). (A) PPI network diagram of the common targets of CAD and active compounds. (B) Interactive network diagram of critical targets.

GO and KEGG pathway enrichment analyses

GO enrichment analysis was performed on 36 target proteins in the PPI network (P < 0.05). GO enrichment analysis included molecular function (MF), biological pathway function (BP), and cellular component (CC). The top 10 items were taken to make bar graph (Fig. 6), and the lower the bar, the smaller the P value. The MF of target proteins were mainly focused on serine/threonine-protein kinase activity, endopeptidase activity, L-cysteine endopeptidase activity and so on. The BP included response to oxidative stress, cellular response to chemical stress, response to reactive oxygen species, response to UV and so on. And the CC included vacuole, ficolin-1-rich granule, vesicle lumen, lysosomal lumen and so on (Fig. 5A and B).

Figure 5 Results of GO enrichment analysis. (A) Histogram of biological process in the GO enrichment analysis. (B) Bubble plot of biological process in the GO enrichment analysis.

Meanwhile, KEGG pathway analysis of 36 target proteins in the PPI network was performed (P < 0.05), and the top 20 high-concentration pathways were selected. Analysis of the enrichment results showed that Sal, Sir and CQ were used to treat CAD through multi-channels, including autophagy, apoptosis, lipid response, diabetic cardiomyopathy, estrogen signaling pathway and so on (Fig. 6A and B, Table 2). Among them, the Sal/Sir/CQ-related targets and pathway associated with autophagy-mediated CAD progression have been presented in Fig. 6C.

Table 2

KEGG enrichment results for key genes.
ID	Description	Gene ID	Count
hsa04140	Autophagy - animal	MTOR/CTSB/CTSD/DAPK1/ERN1/MAPK1/MAPK8/PRKCD/PRKCQ	9
hsa04210	Apoptosis	CTSK/CASP3/CTSB/CTSD/ERN1/MAPK1/MAPK8/PARP1	8
hsa05219	Bladder cancer	MMP9/DAPK1/EGFR/MAPK1/VEGFA	5
hsa05417	Lipid and atherosclerosis	MMP9/CASP1/CASP3/ERN1/HSPA5/HSPA8/MAPK1/MAPK8	8
hsa05212	Pancreatic cancer	MTOR/EGFR/MAPK1/MAPK8/VEGFA	5
hsa05415	Diabetic cardiomyopathy	MMP9/MTOR/CTSD/GAPDH/MAPK8/PARP1/PRKCD	7
hsa04915	Estrogen signaling pathway	MMP9/CTSD/EGFR/HSPA8/MAPK1/PRKCD	6
hsa05206	MicroRNAs in cancer	MMP9/PTGS2/EZH2/MTOR/CASP3/EGFR/MAPK1/VEGFA	8
hsa05210	Colorectal cancer	MTOR/CASP3/EGFR/MAPK1/MAPK8	5
hsa04930	Type II diabetes mellitus	MTOR/MAPK1/MAPK8/PRKCD	4
hsa04657	IL-17 signaling pathway	MMP9/PTGS2/CASP3/MAPK1/MAPK8	5
hsa01522	Endocrine resistance	MMP9/MTOR/EGFR/MAPK1/MAPK8	5
hsa05131	Shigellosis	MTOR/CASP1/EGFR/MAPK1/MAPK8/PRKCD/PRKCQ	7
hsa04933	AGE-RAGE signaling pathway in diabetic complications	CASP3/MAPK1/MAPK8/PRKCD/VEGFA	5
hsa04625	C-type lectin receptor signaling pathway	PTGS2/CASP1/MAPK1/MAPK8/PRKCD	5
hsa04066	HIF-1 signaling pathway	MTOR/EGFR/GAPDH/MAPK1/VEGFA	5
hsa04668	TNF signaling pathway	MMP9/PTGS2/CASP3/MAPK1/MAPK8	5
hsa05010	Alzheimer disease	MME/PTGS2/MTOR/CASP3/ERN1/GAPDH/MAPK1/MAPK8	8
hsa05167	Kaposi sarcoma-associated herpesvirus infection	PTGS2/MTOR/CASP3/MAPK1/MAPK8/VEGFA	6
hsa05205	Proteoglycans in cancer	MMP9/MTOR/CASP3/EGFR/MAPK1/VEGFA	6

Figure 6 Results of KEGG enrichment analysis. (A) Histogram of the top 20 pathways based on KEGG enrichment analysis. (B) Bubble plot of the top 20 pathways based on KEGG enrichment analysis. (C) Pathway map associated with autophagy of active compounds against CAD.

Molecular docking analysis

Molecular docking is a method of theoretical simulation to study the interaction between molecules and predict their binding mode and affinity. In this study, the top five target proteins (GAPDH, CASP3, MTOR, VEGFA, EGFR ) were selected for docking with three compounds (Sal, Sir, CQ). Notably, if the binding energy is less than 0 kcal/mol, it is considered that the molecules can self-bind. As seen in Fig. 7A-E and Table 3, the results of molecular docking showed that the active compounds all had good binding ability with the selected targets. Although molecular docking techniques provide a strategy for evaluating binding patterns between herbal compounds and disease-related targets, the potential herbal compounds still need to be verified via related-experiments.

Figure 7 The diagram of molecular docking. (A) Sirolimus and GAPDH. (B) Sirolimus and EGFR. (C) Salidroside and GAPDH. (D) Sirolimus and CASP3. (E) Sirolimus and MTOR.

CoCl₂ induced H9C2 cells death and autophagy

To investigate the toxic effects of CoCl₂ on H9C2 cells, the cells were incubated with various concentrations of CoCl₂ (200, 400, 600, 800 and 1000 µmol/L) for different periods of time (3, 6, 12 and 24 h). The results of CCK-8 assay revealed that CoCl₂ significantly reduced cell viability in a concentration- and time-dependent manner (Fig. 8A). CoCl₂ (400 µmol/L) treatment for 6 h significantly decreased cell viability (P < 0.01) to 60% of the blank. Thus, this concentration and treatment duration were used in subsequent experiments. Moreover, we further investigated this processing condition. The results of IM observation showed that compared with the blank group, cells treated with 400 µmol/L for different periods of time (6, 12 and 24 h) exhibited low viability (Fig. 8B). Western blot analysis revealed that following treatment with CoCl₂, the levels of Caspase-9 (P < 0.01) and the Bax/Bcl-2 ratio (P < 0.01) were both significantly up-regulated compared with the blank group (Fig. 8C). As we all known, the HIF-1α signaling pathway has been shown to play an essential role in hypoxia-induce injury. To assess whether the model was successful in inducing hypoxic injury, the expression of HIF-1α protein was detected by using western blot. The result revealed that CoCl₂-treated H9C2 cells increased the expression of HIF-1α protein (P < 0.05), indicating that CoCl₂ promoted the activity of the HIF-1α signaling pathway in the CoCl₂-treated H9C2 cells and induced cells hypoxia (Fig. 8D).

Figure 8 CoCl₂ induced H9C2 cells anoxic injury. H9C2 cells were incubated with various concentrations of CoCl₂ (200, 400, 600, 800 and 1000 µmol/L) for different periods of time (3, 6, 12 and 24 h). (A) Cell viability was determined using a CCK-8 assay. ^*P < 0.05, ^**P < 0.01 vs. blank group. (B) The morphology of cells was observed using IM, magnification, x100. (C) Expression of Bax, Bcl-2 and Caspase-3 proteins was assessed by western blot analysis. ^*P < 0.05, ^**P < 0.01 vs. blank group. (D) Expression of HIF-1α protein was assessed by western blot analysis. ^*P < 0.05, ^**P < 0.01 vs. blank group.

Autophagy is closely related to cell death in the hypoxic-ischemic process (31,32). To confirm the role of autophagy in CoCl₂-induced injury to H9C2 cells, the ultramicrostructure of autophagy was observed. The results of TEM (Fig. 9) revealed that the autophagic phenomenon (including autophagosomes and autophagolysosomes) was appeared in the CoCl₂ or Sir-treated H9C2 cells, compared with the blank and CQ groups. Following with the MDC and AO staining, the existence of autophagosomes and autophagolysosomes were further verified (Fig. 10A and B). The results showed that following with treatment of CoCl₂ or Sir, the number and brightness of green fluorescence associated with autophagosomes and red-yellow fluorescence associated with autophagolysosomes were both increased compared with the blank and CQ groups. Subsequently, the expression of autophagy-related markers was determined via western blot. As seen in Fig. 10C, the levels of Beclin-1 expression (P < 0.01) and the LC3-II/LC3-I ratio (P < 0.05) were both obviously up-modulated in the CoCl₂-treated group compared with the blank and CQ groups.

Figure 9 The autophagic ultrastructure (including autophagosomes and autophagolysosomes) was appeared in the CoCl₂-treated H9C2 cells through the observation of TEM, magnification, x8000.

Figure 10 CoCl₂ induced H9C2 cells autophagy. H9C2 cells were incubated with CoCl₂ (400 µmol/L) for 6 h. (A) The green fluorescence associated with autophagosomes was detected by using MDC staining, magnification, x400. (B) The red-yellow fluorescence associated with autophagolysosomes was detected by using AO staining, magnification, x200. (C) Expression of LC3-I, LC3-II and Beclin-1 proteins was assessed by western blot analysis. ^*P < 0.05, ^**P < 0.01 vs. blank group.

Validation of the protective effect of Sal-mediated autophagy against CoCl ₂ ‑induced H9C2 cell death in the early period

As seen in Fig. 11, following with the treatment of Sal, Sir or CoCl₂ in H9C2 cells, the levels of Beclin-1 expression (P < 0.01) and the LC3-II/LC3-I ratio (P < 0.01) were both obviously up-modulated compared with the blank groups, indicating that Sal could induce autophagy in H9C2 cells.

Figure 11 Sal induced autophagy in H9C2 cells. The expression of LC3-I, LC3-II and Beclin-1 proteins was assessed by western blot analysis. ^*P < 0.05, ^**P < 0.01 vs. blank group.

Notably, the results from the network pharmacological analysis demonstrated that inflammation, lipid response, oxidative stress, autophagy and apoptosis were associated with multiple synergies of Sal on CAD treatment. The cytotoxicity of Sal in H9C2 cells was evaluated using CCK-8 and then the protective effects of Sal-mediated autophagy against CoCl₂-induced cell death were validated. The results of CCK-8 (Fig. 12A) showed that treatment with various concentrations of Sal (10, 20, 40 or 80 µmol/L) alone for 24 h did not exert any cytotoxic effects on the H9C2 cells ( P > 0.05). Interestingly, following with treatment of Sal (10, 20, 40 or 80 µmol/L) for 24 h could reverse the CoCl₂-caused H9C2 cells injury compared with the CoCl₂-treated groups (P < 0.05, Fig. 12B). Moreover, the results of western blot further confirmed that the expression levels of Caspase-3 protein (P < 0.01) and the Bax/Bcl-2 ratio (P < 0.01) were both down-regulated in the CoCl₂ + Sal group compared with the CoCl₂-treated group (Fig. 12C).

Figure 12 Sal-mediated autophagy protected H9C2 cells from CoCl₂-induced injury. (A) H9C2 cells were incubated with various concentrations of Sal (10, 20, 40 or 80 µmol/L) and cell viability was measured by CCK-8 assay. ^*P < 0.05, ^**P < 0.01 vs. blank group. (B) Cell viability was assessed by CCK-8 assay. Results were presented as the means ± standard deviation; n = 3. ^*P < 0.05, ^**P < 0.01 vs. blank group; ^#P < 0.05, ^##P < 0.01 vs. CoCl₂ group. (C) Expression of Bax, Bcl-2 and Caspase-3 proteins was assessed by western blot analysis. ^*P < 0.05, ^**P < 0.01 vs. blank group; ^#P < 0.05, ^##P < 0.01 vs. CoCl₂ group.

Validation of the deleterious effect of Sal-mediated autophagy against CoCl ₂ ‑induced H9C2 cell death in the late period

However, the results from the network pharmacological analysis also demonstrated that inflammation, lipid response, oxidative stress, autophagy and apoptosis were associated with multiple synergies of autophagy inhibitor (CQ) on CAD treatment, suggesting that autophagy may exist a double-sided function in the treatment of CAD. To verify our hypothesis, we extended the processing time of CoCl₂ on H9C2 cells to 12 h, so as to decreased cell viability (P < 0.01) to 40% of the blank (Fig. 8A). At this moment, the CCK-8 assay (Fig. 13A) showed that H9C2 cells treated with 80 µmol/L Sal for 12 h could not reversed the CoCl₂-caused injury, while promoted the process of cell death, compared with the CoCl₂-treated groups (P < 0.05). Additionally, the results of western blot further confirmed that the expression levels of Caspase-3 protein (P < 0.01) and and the Bax/Bcl-2 ratio (P < 0.01) were both increased in the CoCl₂ + Sal group compared with the CoCl₂-treated group (Fig. 13B).

Figure 13 Sal-mediated autophagy promoted CoCl₂-induced H9C2 cells injury. (A) Cell viability was assessed by CCK-8 assay. Results were presented as the means ± standard deviation; n = 3. ^*P < 0.05, ^**P < 0.01 vs. blank group; ^#P < 0.05, ^##P < 0.01 vs. CoCl₂ group. (B) Expression of Bax, Bcl-2 and Caspase-3 proteins was assessed by western blot analysis. ^*P < 0.05, ^**P < 0.01 vs. blank group; ^#P < 0.05, ^##P < 0.01 vs. CoCl₂ group.

According to the theory of TCM, CAD belongs to the category of “chest pain” or “heartache”, the main treatment is promoting blood circulation to remove blood stasis [18]. The pathogenesis of CAD in TCM is the syndrome of deficiency in origin and excess in superficiality. Deficiency in origin is the deficiency of yin-yang and qi-blood, and excess in superficiality is the interaction of phlegm, blood stasis, Qi stagnation and cold coagulation [19]. Since CAD lasts longer, blockage of the Qi and blood may cause cardiovascular ischemia, hypoxia and necrosis, so as to aggravate the severity of diseases [20]. Moreover, the blockage of Qi and blood can also produce many harmful products, including blood lipids, blood clots and so on [21]. Thus, approaches that recovery the cardiovascular patency are extremely crucial in the treatment of CAD.

Previous studies have shown that many components of TCM play a therapeutic role in CAD through autophagic pathway. For example, Han J et al. [22] have found that when human umbilical vein endothelial cells are subjected to oxidative stress, curcumin can induce autophagy through FOXO1 signaling pathway and protect vascular endothelial cells from oxidative stress. Similarly, in the mouse model of acute myocardial infarction, polydatin can activate Sirt3, up-regulate autophagic flux of myocardial cells and improve mitochondrial dysfunction, so as to protect myocardial cells from myocardial infarction injury [23]. Hu J et al. [24] have found that in the model of myocardial infarction, luteolin can up-regulate autophagic flux of myocardial cells and improve mitochondrial viability through Mst1 inhibitor, so as to alleviate myocardial dysfunction. Contrary to the cardiovascular protection by inducing autophagy, some Chinese medicines can also inhibit the excessive expression of autophagy. For instance, Huang Z et al. [25] have found that berberine can alleviate myocardial ischemia-reperfusion injury (IRI) by inhibiting the over-expression of autophagy-related proteins (SIRT1, BNIP3 and Beclin-1). Additional reports have demonstrated that danshensu can inhibit IRI-induced excessive autophagy through activating mTOR signaling pathway and reduce cell apoptosis, so as to alleviate myocardial cells IRI and improve cardiac function [26]. Thus, It can be seen that autophagy plays a role of “double-edged sword” in cardiovascular diseases: in the early stage of the disease, induction of autophagy is protective due to less damage. When the cardiovascular system continues to be invaded by damaging factors, the disease can worsen to the late stage. At this moment, the disease also has an autophagic effect, while the induction of autophagy may cause autophagic cell death.

In the present study, 107 Sal-related targets, 241 Sir (autophagy agonist)-related targets, 100 CQ (autophagy inhibitor)-related targets, and 576 CAD-related targets were obtained from the public databases. Integrating potential targets of three compounds with those of CAD revealed exactly 36 therapeutic targets. Based on the topological analysis of PPI network, the top 5 core targets were selected, consisting of GAPDH, CASP3, MTOR, VEGFA, and EGFR. GO functional analysis showed that the role of active compounds (Sal, Sir and CQ) in CAD was related to many biological processes, including serine/threonine-protein kinase activity, endopeptidase activity, L-cysteine endopeptidase activity, response to oxidative stress, cellular response to chemical stress, response to reactive oxygen species, response to UV and so on. KEGG signaling pathway enrichment technology retrieved many related pathways from these core targets, such as inflammation, lipid response, oxidative stress, autophagy, apoptosis, diabetic cardiomyopathy, estrogen signaling pathway and so on. Apparently, those three compounds may be used to treat CAD via autophagic pathway. Meanwhile, this fact implies that both induction and inhibition of autophagy seem to be beneficial for CAD, which is consistent with the concept of previous literature. To verify 5 key proteins of GAPDH, CASP3, MTOR, VEGFA, and EGFR, we respectively imported them into the online tool AutoDock Vina, we found that the three active compounds all had good binding ability with the selected targets. It not only suggests that these compounds can regulate autophagy in a multi-target and multi-channel manner, thus affecting the occurrence and development of CAD, but also suggests that they may be important potential targets for the treatment of CAD, so as to provide novel ideas for succeeding researches.

Among those 5 core targets, CASP3 (Caspase-3), a member of the cysteine protease family, is a downstream protein in the apoptosis pathway and an apoptotic enzyme that functions through the death receptor and mitochondrial pathways [27]. Previous studies have found a significant increase in Caspase-3 expression in the models of CAD rats [28], while the expression of Caspase-3 is decreased through the treatment of PCI [29], which demonstrates that Caspase-3-mediated apoptosis may be an important molecular mechanism of CAD. mTOR is a serine/threonine protein kinase that belongs to the phosphatidylinositol 3 kinase (PI3K) [30]. There are two different sub-types of mTORC1 and mTORC2. mTORC1 is involved in the synthesis of proteins, controlling ribosome biogenesis, inhibiting autophagy, regulating the biological activity of mitochondria and regulating cell cycle [31]. mTORC2 is mainly involved in the regulation of apoptosis and proliferation, maintaining cytoskeleton structure and polarity [32]. Studies have shown that PI3K/Akt/mTORC1 and AMPK/mTORC1 signaling pathways play important roles in the progression of coronary atherosclerosis [33]. The PI3K/Akt/mTORC1 pathway is involved in the proliferation and migration of vascular smooth muscle cells during coronary atherosclerosis. Activated vascular smooth muscle cells may promote the progression of atherosclerotic plaques [34], inhibition of the PI3K/Akt/mTORC1 signaling pathway not only promotes autophagy in macrophages and stabilizes arteriosclerosis plaques [35], but also inhibits the damage of endothelial cells and delays the progression of coronary arteriosclerosis [36]. Thus, inhibition of the PI3K/Akt/mTORC1 signaling pathway can effectively enhance autophagy, attenuate lipid metabolic disorders, and reduce plaque area [35]. Similarly, inhibition of AMPK/mTORC1 signaling pathway effectively prevents vascular smooth muscle cells proliferation and intimal thickening, activates autophagy in endothelial cells, and delays endothelial cells senescence [37, 38]. However, the platelet-derived growth factors-induced vascular smooth muscle cells proliferation via inhibition of mTORC1/S6K pathway is not associated with AMPK [39]. VEGFA is a member of the VEGF family, also known as vascular endothelial factor A, which plays an important role in angiogenesis and endothelial cell growth. It can induce proliferation and migration of endothelial cells and induce vascular permeability, which are necessary for physiological and pathological angiogenesis [40]. Studies have shown that VEGFA can bind to VEGFR-2 in the endothelial membrane under the condition of myocardial ischemia and hypoxia, and induce new capillary in the infarcted area and promote the establishment of collateral circulation in the ischemic peripheral tissues through multiple approaches (including SRC, Raf-mek, PI3K-Akt and DII4-Notch pathways), so as to improve the function of heart [41–44]. It is also reported that the cardiac function of rats with acute myocardial infarction tends to improve after the introduction of VEGFA [45]. Moreover, Shi ZZ et al. [46] have found that in coronary artery disease, HIF-1α expression is stable and binds to the VEGFA gene in the nucleus, so as to activate the HIF-1α/VEGFA pathway, which promotes angiogenesis and improves myocardial ischemia. EGFR is the expression product of c-erbB1 (a proto-oncogene), and a member of the human epidermal growth factor (HER) family. It is mainly distributed in vascular epithelial cells and can interfere the growth, differentiation and proliferation of vascular epithelial cells through RAS/RAF/MEK/MAPK and PI3K/PDK1/Akt pathways [47, 48]. EGFR-specific binding to ligand (EGF) promotes ROS formation in the cardiovascular system and contributes to cardiovascular system [49]. Moreover, Li WX et al. [50] have found that EGFR may be a therapeutic target for obesity-related cardiovascular diseases, which is associated with myocardial inflammation, fibrosis, apoptosis and dysfunction. According to the literature review, these 5 core targets are closely related to the occurrence and development of cardiovascular diseases, which is also consistent with the results of network pharmacological analysis.

Subsequently, based on the analysis results of network pharmacology, we investigated the role of Sal in CAD through cell experiments, focusing on the autophagic pathway. Moreover, in order to evaluate the efficacy via autophagic pathway, we seclected autophagy agonist (Sir) and autophagy inhibitor (CQ) as the autophagic control group. Due to the pathogenesis of CAD, which indirectly triggered cardiovascular hypoxia, the cardiomyocytes (H9C2) were exposed to CoCl2, so as to induce cells hypoxia. In order to evaluate whether the film was successfully made, we used the Hypoxia-inducible factor (HIF-1α) as a standard. More and more evidences have shown that HIF-1α signaling pathway plays an essential role in the process of hypoxia. Under the condition of hypoxia, the organism produces a series of compensatory regulation to resistance the low-oxygen stress, among which HIF-1α is the critical transcriptional regulator of hypoxia-induced regulation, so as to mediate the process of cell growh, proliferation, migration, apoptosis and autophagy [51–53]. Meanwhile, HIF-1α is also the critical molecule in many physiological and pathological regulation. HIF-1α is expressed under the condition of normoxia, but HIF-1α protein can be rapidly degraded by the pathway of intracellular oxygen-dependent ubiquitin protease, and can only be stably expressed under the condition of hypoxia [54, 55]. Cheng JK et al. [56] have found that the SENP1/HIF-1α signaling pathway enables the stable expression of HIF-1α, and the lack of erythropoietin in SENP1-depleted mouse embryos can cause severe ischemia. Tian H et al. [57] have found that chronic hypoxia induces the increased expression of SUMO-1, degradation of SENP1 protein, increase of desumoylation-modified HIF-1α, and increase of HIF-1α stability and transcriptional activity in the wall of pulmonary arterioles of mice, so as to cause hypoxic pulmonary hypertension (HPH). Other studies have shown that VEGF is an important target gene of HIF-1α transcriptional activation, and the expression of VEGF is regulated by HIF-1α. Under the condition of hypoxia, HIF-1α can improve hypoxia by promoting VEGF and its receptor 1, increasing vascular permeability and inducing angiogenesis. The levels of HIF-1α and VEGF are significantly increased in patients with acute exacerbation of high altitude pulmonary heart disease, and are negatively correlated with arterial partial pressure of oxygen, and prolonged hypoxemia can cause pulmonary hypertension and pulmonary vascular remodeling, which suggesting that HIF-1α/VEGF signaling pathway may be an important factor in the high altitude heart disease [58]. Thus, it be seen that HIF-1α not only plays a regulatory role in hypoxia stress, but also its related signaling pathways are closely associated with the occurrence and development of diseases. Following treatment with Sal for 24 h in CoCl₂-exposed H9C2 cells, we found that Sal could not only induce cells autophagy, but also reverse the CoCl₂-caused injury, which suggested that autophagy may play a protective role in this process. However, further studies showed that Sal-mediated autophagy was not always beneficial to H9C2 cells. When H9C2 cells were treated with CoCl₂ for 12 h, Sal-mediated autophagy does not reverse this chemical damage, and accelerates the procedure of cell death, suggesting that autophagy may exist a function of assisting injury. Thus, autophagy plays different roles at different stages of injury, which is consistent with our analysis of network pharmacology.

However, there are still some limitations for this study. On the one hand, the network pharmacology research relies more on various existing databases, but the sifted condition of compounds in databases may not be accurate enough. On the other hand, the screened active ingredients may exist the difference of those actually absorbed in the blood of patients with CAD. Due to the accuracy and reliability of the data have a great impact on the predicted results, it is extremely necessary to further verify the reliability and quality of the predicted results and optimize the screening criteria of the TCM database, so as to improve network pharmacology research. Hence, further experiment in vivo and clinical verification of the effect of Sal on heart and blood vessels is demanded to validate theoretical predictions.

In this study, the characteristics of “multi-target and multi-channel” of Sal in the treatment of CAD were systematically analyzed by network pharmacodynamic method and in vitro experiments. Notably, the experimental results are in agreement with those predicted from the network analysis of the Sal, especially the role of this compound-induced autophagy in the different periods of the hypoxia model of myocardial cells. Our study not only provided a theoretical and experimental basis for the ingredients of TCM against CAD, but also provided new insights of targeting autophagy of Sal as a adjuvant strategy for CAD. Meanwhile, in terms of the double-sided role of Sal-mediated autophagy in disease progression, on the road to explore the treatment of cardiovascular disease through autophagy, we should choose appropriate methods to obtain better curative effects, induction or inhibition of autophagy is entirely dependent on the specific cases and analyses.

Sal

Salidroside

Sir

Sirolimus

Chloroquine diphosphate

CAD

Coronary artery disease

PPI

Protein-protein interaction

Gene ontology

KEGG

Kyoto enrichment of gene and genome

Inverted microscope

PCI

Percutaneous coronary intervention

TEM

Transmission electron microscope

LogFC

Log2 fold change

FDR

False discovery rate

PBS

Phosphate buffered saline

RIPA

Radioimmunoprecipitation assay

PMSF

Phenylmethylsulfonyl fluoride

FBS

Fetal bovine serum

CCK-8

Cell counting kit − 8

CO₂

Cardon dioxide

Standard deviation

Molecular function

Biological pathway function

Cellular component

IRI

Ischemia-reperfusion injury

PI3K

phosphatidylinositol 3 kinase

HER

Human epidermal growth factor. HIF:Hypoxia-inducible factor.

Acknowledgments

We would like to extend our gratitude to all the researchers of Gansu Province Academic Institute for Medical Research for their help and support to this study.

Authors’ contributions

BJ contributed to the experiments and writing original draft. XF contributed to network pharmacology analysis. WZ and JX contributed to methodology and software. TY, LFF and XZ contributed to supervision. LLW and HXS contributed to the revision of English grammar. ZZ contributed to the design of the work, funding acquisition, and revision. All authors have read and approved the final manuscript.

Funding

This study was supported by the National Natural Science Foundation of China with grant number 82060807 and the Natural Fund project of Gansu Province with grant number 18JR2FA005.

Availability of data and materials

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

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that there is no conflict of interest regarding the publication of this paper.

Disclosure

Bing Jiang and Xin Feng are co-first authors.

Author details

^1,2,4Gansu University of Traditional Chinese Medicine, No.35 Dingxi East Road, Chengguan District, Lanzhou 730000, China. ³Lanzhou University, No.199 Donggang West Road, Chengguan District, Lanzhou 730000, China. ⁵Gansu Province Academic Institute for Medical Research, Gansu Provincial Cancer Hospital, No.2 Xiaoxihu East Road, Qilihe District, Lanzhou 730050, China. ⁶First Hospital of Lanzhou University, No. 1, Donggang West Road, Chengguan District, Lanzhou 730030, China.

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No competing interests reported.

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Network pharmacology and in vitro studies show the pharmacological effects and molecular mechanisms of salidroside against coronary artery disease

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Predicting drugs therapeutic targets and CAD significant targets

Network construction and analysis

Analysis of molecular docking

Materials and reagents for biological experiments

Cell culture and modeling intervention

Treatment with Sal, Sir and CQ

Cell viability and cell death assays

Cell autophagy using transmission electron microscope (TEM)

MDC staining and AO staining

Western blot analysis

Statistical analysis

Results

Predicted targets for three compounds, CAD significant and therapeutic targets

Network construction and analysis

GO and KEGG pathway enrichment analyses

Molecular docking analysis

CoCl₂ induced H9C2 cells death and autophagy

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1

Network pharmacology and in vitro studies show the pharmacological effects and molecular mechanisms of salidroside against coronary artery disease

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Predicting drugs therapeutic targets and CAD significant targets

Network construction and analysis

Analysis of molecular docking

Materials and reagents for biological experiments

Cell culture and modeling intervention

Treatment with Sal, Sir and CQ

Cell viability and cell death assays

Cell autophagy using transmission electron microscope (TEM)

MDC staining and AO staining

Western blot analysis

Statistical analysis

Results

Predicted targets for three compounds, CAD significant and therapeutic targets

Network construction and analysis

GO and KEGG pathway enrichment analyses

Molecular docking analysis

CoCl2 induced H9C2 cells death and autophagy

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1

CoCl₂ induced H9C2 cells death and autophagy