Deciphering the mechanisms of Yinlan Tiaozhi capsule in treating hyperlipidemia by combining network pharmacology, molecular docking and experimental verification

Yinlan Tiaozhi capsule (YLTZC) has been widely used to treat hyperlipidemia (HLP). However, its material basis and underlying pharmacological effects remain unclean. The current study aimed to explore the mechanisms involved in the treatment of YLTZC on HLP based on network pharmacology, molecular docking, and experimental verification. Firstly, UPLC-Q-TOF–MS/MS was used to comprehensively analyze and identify the chemical constituents in YLTZC. A total of 66 compounds, mainly including flavonoids, saponins, coumarins, lactones, organic acids, and limonin were characterized and classified. Simultaneously, the mass fragmentation pattern of different types of representative compounds was further explored. By network pharmacology analysis, naringenin and ferulic acid may be the core constituents. The 52 potential targets of YLTZC, including ALB, IL-6, TNF, and VEGFA, were considered potential therapeutic targets. Molecular docking results showed that the core active constituents of YLTZC (naringenin and ferulic acid) have a strong affinity with the core targets of HLP. Lastly, animal experiments confirmed that naringenin and ferulic acid significantly upregulated the mRNA expression of ALB and downregulated the mRNA expression of IL-6, TNF, and VEGFA. In sum, the constituents of YLTZC, such as naringenin and ferulic acid, might treat HLP by regulating the mechanism of angiogenesis and inhibiting inflammatory responses. Furthermore, our data fills the gap in the material basis of YLTZC.

Liquid chromatography-mass spectrometry analysis. Liquid chromatography analysis was conducted by using a SHIMADZU ExionLC system (Japan). Chromatographic separation was used Waters ACQUITY BEH C 18 column (100 mm × 2.1 mm, 1.7 μm) at 30 °C, with mobile phases A (0.1% formic acid) and B (acetonitrile). The flow rate was 0.3 ml/min, and the gradient profile was showed as follows: 0-3 min, 8 The MS analysis was acquired using an AB SCIEX X500R Q-TOF-MS/MS system (United States) with an electrospray ionization (ESI). The results of the mass spectrometry optimization conditions are as follows: ion voltage: − 4.0 kV and + 5.5 kV, Gas1 (nebulizer gas): 55 psi; Gas2 (heater gas): 55psi; curtain gas: 35 psi; declustering potential voltage: 80 V; ion source temperature: 500 °C; collision energy: 60 V; collision energy spread: 15 V; scan range: m/z 50-1000. Data were collected in information-dependent acquisition mode, and the instrument was recalibrated every four hours in order to exclude dynamic background. All data collected and analyzed by SCIEX OS v2.1 software (Framingham, MA, United States, 2021).
Establishment of a chemical constituents library for YLTZC. The chemical constituents of the 4 herbs in YLTZC were collected from existing databases, including CNKI (https:// www. cnki. net/), SciFinder (https:// scifi nder. cas. org/) and literature searches, etc. Then, a self-built database of YLTZC chemical constituents containing component names and molecular formula information was established (Supplementary Table S1). MS data was imported into SCIEX OS v2.1 for analysis. Chemical identifications were combined with reference to relevant literatures and standards, precise relative molecular masses, mass spectrometry fragment information, and mass spectrometry library (Natural Products HR-MS/MS Spectral Library, Version 1.0, AB Sciex, United States).
Network pharmacology analysis. Active constituent screening of YLTZC. The SwissADME tool (http:// www. swiss adme. ch/) was used for analyzing active constituents with absorption, distribution, metabolism, and www.nature.com/scientificreports/ excretion (ADME) properties and druglikeness evaluation to screen for active constituents with potential therapeutic effects. We applied in this study screening criteria of (1) pharmacokinetics "high" and (2) druglikeness (DL) with more than two "yes" 12 .
Target network analysis. In this research, the targets of active constituents in YLTZC were searched by Swiss Target Prediction database (http:// www. swiss targe tpred iction. ch/), and targets with probability greater than 0 were selected. The HLP-related targets were selected from CTD (http:// ctdba se. org/) and GeneCards (https:// Quantitative real-time PCR. About 50 mg of liver was weighed and transferred into a 1.5 ml grinding tube. After adding 500 µl Trizol reagent (Beijing, China) and 2 grinding beads to the grinding tube, the liver was crashed by a freezing grinder (Shanghai Jingxin, China). The grinding liquid was centrifuged (4 °C, 10 min, 12,000 rpm) and the supernatant (about 400 µl) was transferred into a 1.5 mL centrifuge tube. 100 µl chloroform was added to the centrifuge tube and they were fully mixed by sharking. After centrifuging at 12,000 rpm at 4 °C for 10 min, the supernatant (about 200 µl) and the equivalent isopropyl alcohol were added into a 1.5 mL centrifuge tube and stored overnight in a − 20 °C refrigerator. The crushed total RNA was settled at the bottom of the centrifuge tube after centrifugation at 12,000 rpm at 4 °C for 10 min. After washing with 75% ethanol 2 times, the pure total RNA was gained and dissolved in 50 µl RNase-free water. The content of total RNA was measured by UV and 500 ng total RNA was reverse transcribed by using the Evo M-MLV RT Premix for qPCR (Accurate Biology, China). RT-qPCR reactions were performed on iQ5 Multicolor Real-Time PCR detection system (BIO-RAD, Hercules, California, United States) with SYBR Green Dye detection. The relative gene expression was determined by the 2 −ΔΔCt method, and Gene-expression data were normalized to that of the internal control GAPDH. The primer sequences are shown in Table 1.

Statistical analysis.
Results were expressed as the mean ± standard deviation (SD), and analyzed by SPSS 20.0 software. Statistical significance was assessed using one-way analysis of variance (ANOVA). The value of p < 0.05 was considered statistically significant.

Network pharmacology analysis. Collection and screening of potential constituents and targets.
We performed an in-depth assessment of the absorption, distribution, metabolism, and excretion-related properties of 66 constituents in YLTZC using the online tool SwissADME. A total of 38 constituents in YLTZC were screened from the SwissADME tool (Table 3). The YLTZC-related targets and HLP-related targets were acquired by the SwissTargetPrediction, GeneCards, and CTD database, respectively. A total of 568 YLTZC-related and 179 HLP-related targets were acquired after searching, integrating and deduplicating steps. www.nature.com/scientificreports/

Construction of C-T-D and PPI network.
We used Venny 2.1 to obtain the therapeutic targets of YLTZC against HLP (Fig. 5A). 52 overlapping targets were obtained. The C-T-D network contains 91 nodes and 368 edges, including 38 active constituents, and 52 common targets (Fig. 5B). In network analysis, edges represent the interactions between different nodes, and the degree value is decided by the number of connections between a node and other nodes. The higher the degree value, the more significant it represents. According to the degree analysis, the top three compounds were naringenin (N28), asiatic acid (N52), and morin (N25), which may be the active ingredients of YLTZC in alleviating HLP. In addition, a PPI network was constructed based on common targets. As a result, 52 nodes and 996 edges were involved in this network (Fig. 5C). According to the degree analysis, the top 5 potential targets of DC values were selected as the core target, such as ALB, TNF, IL6, PPARG, and VEGFA.
Enrichment analysis and C-T-P network. Gene Ontology (GO) and KEGG pathway enrichment analysis were undertaken on the 52 common targets mentioned above using the DAVID 6.8 database. The top 10 GO enrichment analysis results listed in BP, MF and CC are shown in Fig. 6A. Among them, the BP entries, including extracellular space regulation of lipid metabolic process, positive regulation of smooth muscle cell proliferation, MAPK cascade, inflammatory response, etc. The CC entries, including extracellular space, extracellular  Fig. 6B. A C-T-P network was constructed to further study the relationship between ingredients, targets and pathways. As shown in Fig. 7, containing 39 targets, 38 active constituents and 20 KEGG pathways was established, including 97 nodes and 422 edges. With topological analysis, we selected two compounds with the highest degree value, naringenin (DC = 12) and ferulic acid (DC = 9) as the core active constituents in YLTZC.
Core target molecular docking. Based on the PPI and C-T-P network, we selected molecular docking between the 2 core active constituents and the top 5 core targets. The docking score and local structure of the results are presented in Table 4 and Fig. 8. The binding sites on the protein surface are indicated by different colors and the hydrogen bonds are shown as dashed lines. Furthermore, the chemical constituent acts on multiple amino acid residues suggesting the multi-target property of TCM preparation. The results showed that most of the affinity energies of the core active constituents docking with core proteins were less than − 5.0 kcal/mol, indicating stable binding 34 . Naringenin and ferulic acid had good affinity with the core targets, which was consistent with the results of literature reports, indicating that naringenin and ferulic acid have good anti-HLP effects. Based www.nature.com/scientificreports/ on these data, we suggested that the core active constituents have a good affinity for the core targets, which also demonstrated that YLTZC exerted its efficacy through multi-target combination.
Experimental evaluation. Active ingredients of YLTZC modulated serum lipid levels. Firstly, we investigate ferulic acid and naringenin on serum lipid levels in acute hyperlipidemia in triton WR-1339-induced mice. As shown in Fig. 9A, the levels of serum TC, TG, and LDL-C (p < 0.01) were significantly increased in model group compared with the control group, and the levels of HDL-C (p < 0.05) was decreased. Compared with the model group, the levels of serum TC, TG, and LDL-c (p < 0.05, p < 0.01) were reduced in the naringenin and ferulic acid group, and the levels of serum HDL-C (p < 0.01) was significantly increased. These results suggested that naringenin and ferulic acid from YLTZC have good effect on improving blood lipid levels.  www.nature.com/scientificreports/

Effect of active ingredients of YLTZC on the expression of mRNA of key targets.
To clarify the molecular mechanism of YLTZC treatment for HLP, the mRNA expressions of the targets predicted above were measured by RT-PCR. As shown in Fig. 9B, compared to the control group, the triton WR-1339-induced group showed significantly decreased ALB mRNA expression and increased IL6, TNF and VEGFA mRNA expression (all p < 0.01), while naringenin and ferulic acid treatment markedly reversed these key targets. As expected, naringenin and ferulic acid treatment significantly increased ALB mRNA expression and decreased IL6, TNF and VEGFA mRNA expression compared to the model group.
In conclusion, these results demonstrated that naringenin and ferulic acid from YLTZC may modulate the mechanism of angiogenesis and inhibiting inflammatory responses by regulating the expression of ALB, IL-6, TNF-α, and VEGFA to alleviate HLP.

Discussion
HLP is one of the leading risk factors for the development and progression of cardiovascular diseases, characterized by elevated TC, TG, LDL-c, and decreased HDL-c 1 . In our previous study, YLTZC showed a strong hypolipidemic effect, the results showed that YLTZC significantly decreased the levels of serum TC, TG, and LDL-c, and enhanced the level of serum HDL-c in HLP mice [5][6][7] . However, previous studies provided clues for the current study, but were not comprehensive, and relevant studies on the material basis and related mechanisms of action of YLTZC in the treatment of HLP are still lacking. This limits the further clinical studies and quality control and evaluation of YLTZC. Therefore, this study fills these shortages by developing a comprehensive research method combining chemical profile with network pharmacology, molecular docking, and experimental verification.
In recent years, along with the generalization of systems biology, network pharmacology has become an important method to clarify the potential mechanisms of multiple constituents, targets, and pathways of TCM. In this study, the chemical constituent of YLTZC was comprehensively characterized by UPLC-Q-TOF-MS, and a total of 66 constituents, including naringenin, and ferulic acid, were identified. The results of the study provide more information on the chemical substance basis for further studies of YLTZC. According to the C-T-P and PPI network analysis, naringenin and ferulic acid were discovered to be the core active constituents associated with the most targets, and the HLP-related core targets of YLTZC were ALB, TNF, IL6, and VEGFA. In this study, enrichment analysis of GO and KEGG pathways was performed on 52 common targets. GO function enrichment analysis results showed that YLTZC treatment of HLP may involve the following BP: lipid metabolic process, positive regulation of smooth muscle cell proliferation, positive regulation of MAPK cascade, and positive regulation of inflammatory response. We hypothesized that the response to lipid metabolic process and inflammatory may be the most important BP in the treatment of HLP by YLTZC. KEGG pathway enrichment analysis results demonstrated that HIF-1 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, PPAR signaling pathway, PI3K-Akt signaling pathway, IR, and TNF signaling pathway were highly involved in YLTZC treatment of HLP. These pathways are highly associated with the regulation of angiogenesis and anti-inflammation systems, which may be significant pathways for the alleviation of the symptoms of HLP. Consequently, our findings suggest that the modulating the mechanism of angiogenesis and inhibiting inflammatory are potential therapeutic strategies of YLTZC for the treatment of HLP.
Naringenin has an antioxidative activity to relieve oxidative stress, alleviate IR, and inhibit the production of inflammatory mediators 35,36 . It has been shown that naringenin prevents HLP, IR, and atherosclerosis by decreasing TC, TG, and LDL and increasing HDL 37 . In addition, naringenin inhibited fibroblast activation and inflammatory cell recruitment. The mRNA and protein expression levels of TNF-α, IL-1β, IL-6, and TGF-β1 were downregulated following naringenin treatment 38 . Meanwhile, some studies have found that the effects of naringenin are related to the activation of PPARs, which can regulate hepatic lipid metabolism at the transcriptional level in human and rat by activating PPARα, PPARβ, or PPARγ, respectively, and reduces serum lipids in HLP rats 39,40 . Ferulic acid has been shown to have anti-HLP, antioxidant, and anti-inflammatory effects. Compared www.nature.com/scientificreports/ with the placebo, the ferulic acid supplementation showed a statistically significant decrease in TC, LDL-c, and TG, and increased HDL-c 41,42 . In addition, ferulic acid could inhibit the expression of several pro-inflammatory cytokines including IL-1β, TNF-α, IL-10, and IL-6, and also inhibit angiogenesis by reducing the expression of VEGFA mRNA [43][44][45] . In our study, we established a triton WR-1339-induced HLP mice model, supplied with core active constituents of YLTZC for confirming its hypolipidemic effect. The results showed that naringenin and ferulic acid treatment significantly decreased the levels of serum TC, TG, and LDL-c, and enhanced the level of serum HDL-c in HLP mice. Therefore, naringenin and ferulic acid as the two core active constituents may be the potential material basis for YLTZC to alleviate HLP. On the one hand, YLTZC may treat HLP by regulating the mechanism of angiogenesis. VEGFA was found to be a significant factor in the regulation of vascular endothelial cells. Vascular remodeling during atherosclerosis www.nature.com/scientificreports/ was also associated with the expression of VEGFA, which has the effect of inducing angiogenesis, promoting their survival, and enhancing vascular permeability 46 .
On the other hand, YLTZC can alleviate HLP by regulating inflammatory and oxidative stress targets. For example, TNF-α is one of the most significant pro-inflammatory mediators and a critical factor in IR, which is involved in the pathophysiology of various CVDs 47 . IL6 is also a pro-inflammatory cytokine that plays a crucial role in inflammation, atherosclerosis, and thrombosis, and can influence the rate of lipid metabolism, specifically the metabolism of TCs and TGs 48 . ALB is an important substance for maintaining plasma colloid osmotic pressure, and studies have found that ALB levels are closely related to cardiac function, and play a critical role in regulating the osmotic pressure and metabolic processes 49 . Meanwhile, studies have also shown that ALB is the most important carrier/transporter protein in vivo and plays an essential role in plasma antioxidant activity. In addition, in the HLP model, the decreased levels of ALB may be closely associated with the decline of liver function leading to reduced liver production 50,51 . Therefore, we speculate that ALB is mainly used as a drug transport platform to treat HLP by YLTZC. PPARs play a vital role in regulating the systemic inflammatory response, and they also modulate several biological processes that perturbed obesity, including inflammation, lipid and glucose metabolisms 52 .
The HIF-1 signaling pathway is primarily involved in maintaining the steady state of oxygen in the body, and is also engaged in regulating angiogenesis and inflammation 47,53 . Activation of the AGE-RAGE signaling pathway can trigger the production of tissue factors, and inflammatory factors 54 . Moreover, the PPAR signaling pathway plays an essential part in cholesterol metabolism and cholesterol efflux 55 . IR is associated with hyperinsulinemia and HLP 56 . These pathways are highly involved in YLTZC treatment of HLP, among which the PI3K-Akt signaling pathway, PPAR signaling pathway, and IR play critical roles in insulin secretion and lipid metabolism. Furthermore, fluid shear stress and atherosclerosis, the HIF-1 signaling pathway, and the TNF signaling pathway are highly participated in angiogenesis, pro-inflammatory factor secretion, and vascular tone regulation 47,48 .
In summary, we identified 2 core active constituents in YLTZC and the potential targets and pathways underlying the effects of YLTZC in HLP using the network pharmacology method. The results identified some pathways and biological processes that could be related to the lipid-lowering effects of YLTZC. To further validate the feasibility of network pharmacology analysis, IL-6, TNF-α, VEGFA, and ALB were selected as candidate targets of YLTZC against HLP. The molecular docking verified that the core active constituents have good binding properties with the core targets. In vivo experiment, compared with the control group, the mRNA expression of IL-6, VEGFA, and TNF-α mRNA were significantly increased (p < 0.01), and decreased the mRNA expression of ALB (p < 0.01) in the model group. However, compared with the model group, the naringenin and ferulic acid groups inhibited the mRNA expression of IL-6, VEGFA, and TNF-α (p < 0.01), and promoted the mRNA expression of ALB (p < 0.05, p < 0.01). Therefore, we reasoned that YLTZC can effectively alleviate HLP by modulating the mechanism of angiogenesis and inhibiting inflammatory responses. The results of molecular docking and www.nature.com/scientificreports/ experimental verification were consistent with the predicted results of network pharmacology, indicating the accuracy of this method in screening the active constituents and action targets of YLTZC.

Conclusion
In this study, we revealed the therapeutic effect and underlying mechanism of YLTZC against HLP based on network pharmacology, molecular docking, and experimental validation. 66 chemical constituents of YLTZC were rapidly characterized by UPLC-Q-TOF-MS/MS. Based on the network pharmacology approach, the core active constituents including naringenin and ferulic acid, as well as core targets such as ALB, TNF, IL6, and VEGFA were screened for YLTZC for the treatment of HLP. Functional enrichment analysis through GO and KEGG pathways demonstrated the regulation of lipid metabolism, angiogenesis, and anti-inflammation systems, which may be important pathways in alleviating HLP. Molecular docking verified the possibility of the core active constituents binding to the core targets. In vivo experiments further showed that the hypolipidemic mechanisms of YLTZC were associated with the down-regulation of TNF-α, IL6, and VEGFA mRNA expression levels, and the up-regulation of ALB mRNA expression levels. Collectively, this work demonstrated that YLTZC may act against HLP by modulating the mechanism of angiogenesis and inhibiting inflammatory responses, and provided an efficient way to understand the active constituents and underlying mechanisms of YLTZC.

Data availability
The datasets used and/or analysed during the current study were available from the corresponding author on reasonable request. The main supporting data can be found in the supplementary material of the article.