Abstract Background This study used network pharmacology, molecular docking and experimental validation to assess the effects of Huanglian Jiedu Decoction (HLJDD) on atherosclerosis (AS). Methods The components and targets of HLJDD were analyzed using the Traditional Chinese Medicine Systems Pharmacology database, and information on the genes associated with AS was retrieved from the GeneCards and OMIM platforms. Protein–protein interactions were analyzed using the STRING platform. A component–target–disease network was constructed using Cytoscape. GO and KEGG analyses were performed to identify molecular biological processes and signaling pathways, and the predictions were verified experimentally. Molecular docking was conducted with ChemOffice software, PyMOL software and Vina to verify the correlation of targets and compounds. Results HLJDD contained 31 active compounds, with quercetin, kaempferol, moupinamide and 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone as the core compounds. The most important biotargets of HLJDD in AS were ICAM-1, CD31 and RAM-11. The molecular docking results showed that the molecular docking interaction energy between the 3 key targets and the 4 high-degree components were much less than −5 kJ∙mol^−1. The experimental validation results showed that HLJDD might treat AS mainly by reducing TC, TG and LDL-C and increasing HDL-C, upregulating CD31 expression, reducing ICAM-1 and RAM-11 expression, and downregulating inflammatory factors, including CRP, IL-6 and TNF-α. These results support the network pharmacology data and demonstrate that HLJDD affects the expression of core genes and alters the leukocyte transendothelial migration signaling pathway. Conclusion Based on network pharmacology and experimental validation, our study indicated that HLJDD exerted anti-AS effect through upregulating CD31 expression and reducing the expression of ICAM-1 and RAM-11. HLJDD may be a potential therapeutic drug to the prevention of AS. Keywords: Huanglian Jiedu Decoction, atherosclerosis, network pharmacology, molecular docking, experimental validation Introduction Atherosclerosis (AS) is an inflammatory process initiated by subendothelial retention of lipids. The unstable plaques formed by lipids can trigger cardiovascular disease (CVD), making AS a principal source of cardiovascular mortality.[42]1 At present, AS is mainly treated by blocking cholesterol ester synthesis and antiplatelet activity. However, medicines that block the cholesterol synthesis and the antiplatelet activity have obvious side effects.[43]2–4 In addition, it has been confirmed that inhibition of the inflammatory response is a potential pathway to intervene in AS.[44]5 Over the past two thousand years, traditional Chinese medicine (TCM) has been widely used in China and other Asian countries. As one of the most popular supplements and alternative medicines in the world, TCM has been gradually accepted by non-Chinese individuals because of its prominent efficacy, abundant resources, and low toxicity. In TCM, there are many theories according to the pathogenesis of AS, such as damp heat (Shi-re in Chinese), phlegm stasis (Tan-yu in Chinese), and toxic pathogen (Du-xie in Chinese). It means that the treatment principles of clearing away heat, removing dampness and detoxicating would be effective for AS.[45]6 Huanglian Jiedu Decoction (HLJDD) is a traditional Chinese medicine prescription comprising Coptidis Rhizoma (Huang-lian in Chinese), Scutellariae Radix (Huang-qin in Chinese), Phellodendri Chinensis Cortex (Huang-bo in Chinese) and Gardeniae Fructus (Zhi-zi in Chinese). HLJDD had been used for 1700 years in China and was mainly depending on clearing away heat-toxin to intervene in the inflammatory disorder, the basic pathophysiological process of AS.[46]6 Recent studies have shown that HLJDD has obvious anti-inflammatory, antibacterial and other pharmacological effects. Additionally, HLJDD protects myocardial cells by lowering blood lipids and blood pressure and demonstrating anti-atherosclerosis, anti-arrhythmia and anti-thrombosis activities.[47]7 HLJDD may inhibit the occurrence and development of AS by affecting the functional differentiation of some immune cells.[48]8 Therefore, HLJDD may be a feasible treatment considering the pharmacological mechanisms. TCM is a complex system with hundreds of pharmacological compounds.[49]9 Unlike Western medicine, the theory of TCM emphasizes the integrity of the entire human body. Because of the complexity of its composition, it is difficult to systematically investigate the molecular mechanism of action of herbs. Network pharmacology is a new subject based on the theory of systems biology, pharmacokinetic and pharmacodynamic properties of drugs as well as protein targets and their pharmacological activities, which analyzes the network of biological systems and selects specific signal nodes to perform multitarget drug molecular design.[50]10 Network pharmacology offers a new approach to the study of Chinese medicine, demonstrating the advantages of multi-compound, multi-target and multi-pathway features of Chinese medicine prescriptions and providing a systematic solution for Chinese medicine prescription research from quality control to clinical efficacy.[51]11 In the current study, we used computational resources to construct the pharmacological network of HLJDD in AS to predict the active compounds and potential protein targets and pathways. The results showed that HLJDD contained 31 active compounds, with quercetin, kaempferol, moupinamide and 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone as the core compounds. The most important biotargets of HLJDD in AS were ICAM-1, CD31 and RAM-11. The molecular docking results showed that the molecular docking interaction energy between the 3 key targets and the 4 high-degree components were much less than −5 kJ∙mol^−1. The experimental validation results showed that HLJDD significantly influenced the expression of the 3 targets predicted by network pharmacology. Materials and Methods Collection of Chemical Components and Targets of HLJDD To evaluate the pharmacokinetics of HLJDD, we used the TCMSP database ([52]http://lsp.nwu.edu.cn/) to collect information about the chemical composition of HLJDD. The TCMSP database is a systematic pharmacological resource to evaluate Chinese medicines or related compounds.[53]12 Using the pharmacokinetic information retrieval filter based on the TCMSP platform, the oral bioavailability (OB) and drug-likeness (DL) can be set to ≥30% and ≥0.18 to obtain qualified herbal compounds. Collection of Disease-Associated Targets Potential genes associated with AS were collected from GeneCards ([54]https://www.genecards.org/) and OMIM ([55]https://www.omim.org/). GeneCards is a comprehensive and authoritative human gene integrator that assembles several descriptions about human genes from over 80 digital sources.[56]13 The OMIM database is also an extensive and canonical research resource for information on genes and phenotypes that is secured from peer-reviewed biomedical literature examined by more than 45 high-impact journals.[57]14 We gathered the AS-related targets by searching the databases mentioned above using the keyword “atherosclerosis, atheroscleroses, atherogenesis and arteriosclerosis”. Construction of the Component–Common Target–Disease Network Venny2.1.0 ([58]http://bioinfogp.cnb.csic.es/tools/venny/), an interactive tool for comparing lists using Venn diagrams[59]15 is used to screen common potential therapeutic targets between HLJDD and AS-related targets. Cytoscape-v3.7.1, a free software for visualizing complex networks,[60]16 is used to build the HLJDD component–common target–AS network model for more visualized understanding of the interrelationships between them. Protein–Protein Interaction (PPI) Data The Search Tool for the Retrieval of Interacting Genes (STRING) database ([61]https://string-db.org/, ver. 10.5), a database that searches for known and predicted protein-to-protein interactions,[62]17 was used to analyze the protein–protein interactions of the common targets of the HLJDD and AS-related targets. The database defines PPIs with confidence ranges for data scores. GO and KEGG Enrichment Analyses The Cytoscape plugin (“ClueGO2.5.6”) was selected for the enrichment analysis of GO-BP, which supports over 200 species, real-time database updates, multiple annotated databases and network graph displays. We performed pathway enrichment analysis using the KEGG data obtained from the DAVID 6.8 platform ([63]https://david.ncifcrf.gov/). DAVID now provides a comprehensive set of functional annotation tools for investigators to understand the underlying biological significance of a large list of genes. The P-values were calculated in these two enrichment analyses, and specific disease pathways were excluded. P < 0.05 indicated that the enrichment degree was statistically significant. Molecular Docking The 3D structure of each compound was established, the energy was minimized in ChemOffice software and the structure was saved in *mol2 format. The protein labels relevant to the top 3 targets with the highest degree values were found through the STRING database, and then their 3D structures were downloaded in *PDB format through the PDB database ([64]https://www.rcsb.org/). PyMOL software was used to affix hydrogen atoms and remove water molecules from proteins, and the format of compounds and target proteins was transformed into *pdbqt through AutoDock software. Finally, Vina was used for docking. A binding energy less than 0 indicates that the ligand can spontaneously bind the receptor. Experimental Verification HLJDD Preparation HLJDD comprising four herbal medicines (Scutellariae Radix; Phellodendri Chinensis Cortex; Coptidis Rhizome; Gardeniae Fructus) at a ratio of 6:6:9:9 was prepared by the pharmacy of the First Affiliated Hospital of Guangzhou University of Chinese Medicine (Guangzhou, China). All the herbs were extracted twice with boiling water, and the combined filtrate was concentrated to obtain the decoction (2.0 g/mL). Animal Treatments Forty clean and healthy male New Zealand white rabbits (three months old, 2.5–3 kg) were provided by the Animal Experimental Center of Guangzhou University of Chinese Medicine (Guangzhou, China), and they were maintained individually under a controlled specific pathogen-free environment (temperature, 23° ± 2 °C; relative humidity: 50% ± 10%; 12-hr light/dark cycle) and were fed an ordinary diet for 2 weeks. The Animal Experimental Ethics Committee of Guangzhou University of Chinese Medicine previously approved all the experimental procedures, which met the standards outlined in the Guidelines for Animal Experiments of the Chinese Medical Ethics Committee. All the relevant rules on the handling of animals were strictly followed. The rabbits were randomized into the following four groups (n=10 each): control group (Control), atherosclerotic model group (Model), conventional-dose HLJDD treatment group (HLJDD) and high-dose HLJDD treatment group (High-HLJDD). The control group was fed a normal chow diet, while the other three groups were fed a high-fat diet (1% cholesterol, 5% lard, 94% standard diet, 100 g/d, provided by the animal center of Guangzhou University of Chinese Medicine) to establish the AS model.[65]18 The medical dosage of rabbit were 3.35 times that used in humans. In the present study, conventional-dose HLJDD in rabbit was selected as the clinically equivalent dose of HLJDD in humans (HLJDD clinical dose: 30 g/day, adult weight 70 kg, the dose of rabbit was: 30 g/70 kg × 3.35 ≈ 1.5 g/kg). High-dose HLJDD were twice times of the equivalent doses in rabbit. After 12 weeks of continuous feeding, the conventional-dose HLJDD treatment group received 1.5 g/kg/d of HLJDD, while the high-dose HLJDD treatment group received 3 g/kg/d of HLJDD. All the treatments were delivered by oral gavage for 12 weeks. At the end of the experimental period, all the rabbits were euthanized. The animal experiments were approved by The Animal Ethics Committee of Guangzhou University of Chinese Medicine (Guangzhou, China). Measurement of Blood Lipids The plasma concentrations of TC, TG, LDL-c, and HDL-c were detected according to manufacturer protocols using an Automatic Biochemistry Analyzer (Modular P800, Roche Diagnostics, Basel, Switzerland). Enzyme-Linked Immunosorbent Assay (ELISA) After the last administration, all the rabbits were deprived of food (but not water) for 12 hours, and 1% sodium pentobarbital was injected intraperitoneally for anesthesia. Blood samples collected from the auricular vein were centrifuged at 12,000 r/min at 4 °C for 10 min to prepare the supernatant. The concentrations of CRP, IL-6 and TNF-α in the supernatant were assayed using commercially available enzyme-linked immunosorbent assay (ELISA) kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) following the manufacturer’s protocols. Histological Analysis The abdominal aortic tissues were excised from the rabbits, fixed in 4% paraformaldehyde for 24 h, dehydrated, and embedded in paraffin. Next, the specimens were cut into 5-μm sections, immersed in xylene twice for 5 min each at room temperature and rehydrated in 100%, 95%, 90%, 80%, 70% and 50% ethanol for 1 min each. After Masson’s trichrome staining, the 5-μm sections were analyzed under a digital biological microscope (BK-DM500, Chongqing, China) to determine the collagen content of the tissue sections in plaques. Immunohistochemistry Immunohistochemical (IHC) staining of tissue sample slides obtained from different groups was observed under a BK-DM500 digital biological microscope, and the staining was brown and positive. The Ptps-2011 color pathological image and text analysis system was used to calculate the integrated optical density (IOD; IOD = OD × positive staining area), which was used as the immunohistochemical index of samples to represent the protein expression levels of ICAM-1, CD31 and RAM-11. Statistical Analysis In this study, the results from at least three independent repeats of the experiment were analyzed using GraphPad Prism 8.0 (GraphPad Software Inc., San Diego, CA, USA). The measurement data are presented as means ± SD, and the significant differences among multiple groups were evaluated by one-way analysis of variance (ANOVA). p < 0.05 was considered statistically significant. Results Screening results of Components and Target Proteins In total, 429 components in HLJDD were obtained from the TCMSP database, 48 of which belonged to Coptidis Rhizoma, 143 to Scutellariae Radix, 140 to Phellodendri Chinensis Cortex and 98 to Gardeniae Fructus. According to the screening conditions of OB ≥30% and DL index ≥0.18, 102 components from 4 herbs of HLJDD were collected, comprising 14 (29.2%) components extracted from Coptidis Rhizoma, 36 (25.2%) from Scutellariae Radix, 37 (26.4%) from Phellodendri Chinensis Cortex, and 15 (15.3%) from Gardeniae Fructus. After removing the redundancy, 87 components were selected as candidate bioactive components, whose detailed information is shown in [66]Table S1. After eliminating duplicates, 149 protein targets were harvested based on the target prediction performed using the SwissTargetPrediction website tool ([67]Table S2). Results of AS-Related Targets For disease target identification, 4481 AS-related targets were recovered from GeneCards, and 299 targets were found from the OMIM database. After eliminating the redundant parts, 4733 correlative targets of AS were collected. Network Construction Of the 4733 known AS-related targets and 149 protein targets of HLJDD, 101 therapeutic candidates for AS were dug out using Venny 2.1.0 ([68]Table 1). As described in the third step of the methods, 101 green nodes representing the therapeutic targets and 31 blue nodes representing the candidate bioactive components were utilized to construct an HLJDD–compound–target–AS network ([69]Figure 1). Additionally, 101 targets and 31 constituents were linked through 445 edges, clarifying the effectiveness of HLJDD in preventing or controlling AS depending on the surgery between multiple components and their protein targets. Among these bioactive components, 4 high-degree components were associated with multiple AS targets—quercetin (degree = 42), kaempferol (degree =35), moupinamide (degree = 32) and 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone (degree = 31). Table 1. Common Targets Between HLJDD and AS Target Common Name Uniprot ID Myeloperoxidase MPO [70]P05164 Phosphoinositide-3-Kinase Regulatory Subunit 1 PIK3R1 [71]P27986 Adenosine A2a receptor ADORA2A [72]P29274 Death Associated Protein Kinase 1 DAPK1 [73]P53355 SRC Proto-Oncogene, Non-Receptor Tyrosine Kinase SRC [74]P12931 Protein Tyrosine Kinase 2 PTK2 [75]Q05397 Matrix metalloproteinase 13 MMP13 [76]P45452 Matrix metalloproteinase 3 MMP3 [77]P08254 Carbonic anhydrase III CA3 [78]P07451 Arachidonate 15-lipoxygenase ALOX15 [79]P16050 Multidrug resistance-associated protein 1 ABCC1 [80]P33527 Matrix metalloproteinase 9 MMP9 [81]P14780 Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Gamma PIK3CG [82]P48736 Matrix metalloproteinase 2 MMP2 [83]P08253 Protein kinase N1 PKN1 [84]Q16512 Casein Kinase 2 Alpha 1 CSNK2A1 [85]P68400 Arachidonate 12-lipoxygenase ALOX12 [86]P18054 Hepatocyte growth factor receptor MET [87]P08581 CaM kinase II beta CAMK2B [88]Q13554 Anaplastic Lymphoma Receptor Tyrosine Kinase ALK [89]Q9UM73 AKT Serine/Threonine Kinase 1 AKT1 [90]P31749 Cytochrome P450 1B1 CYP1B1 [91]Q16678 Tyrosine-protein kinase receptor UFO AXL [92]P30530 ATP-binding cassette sub-family G member 2 ABCG2 [93]Q9UNQ0 Apurinic/Apyrimidinic Endodeoxyribonuclease 1 APEX1 [94]P27695 Aldo-keto reductase family 1 member C4 AKR1C4 [95]P17516 Aldo-Keto Reductase Family 1 Member A1 AKR1A1 [96]P14550 Cyclin-dependent kinase 6 CDK6 [97]Q00534 Cyclin-dependent kinase 2 CDK2 [98]P24941 Arginase-1 ARG1 [99]P05089 Tyrosinase TYR [100]P14679 Aryl hydrocarbon receptor AHR [101]P35869 Beta-galactoside alpha-2,6-sialyltransferase 1 ST6GAL1 [102]P15907 Solute carrier family 22 member 12 SLC22A12 [103]Q96S37 Poly [ADP-ribose] polymerase-1 PARP1 [104]P09874 Transthyretin TTR [105]P02766 Matrix metalloproteinase 12 MMP12 [106]P39900 CD38 Molecule CD38 [107]P28907 Aldo-keto reductase family 1 member B10 AKR1B10 [108]O60218 Matrix metalloproteinase 1 MMP1 [109]P03956 Monoamine oxidase B MAOB [110]P27338 C-C chemokine receptor type 2 CCR2 [111]P41597 Forkhead box protein O1 FOXO1 [112]Q12778 Calpain 1 CAPN1 [113]P07384 Rat anti-rabbit macrophage antibody 11 RAM11 A5HC69 Cytochrome P450 2C9 CYP2C9 [114]P11712 Cytochrome P450 3A4 CYP3A4 [115]P08684 Dihydrofolate reductase DHFR [116]P00374 Melanocortin receptor 4 MC4R [117]P32245 5-lipoxygenase activating protein ALOX5AP [118]P20292 Phosphodiesterase 4B PDE4B [119]Q07343 Intercellular cell adhesion molecule-1 ICAM1 [120]P05362 Acyl coenzyme A:cholesterol acyltransferase 1 SOAT1 [121]P35610 Nuclear factor erythroid 2-related factor 2 NFE2L2 [122]Q16236 Janus Kinase 1 JAK1 [123]P23458 Fms Related Receptor Tyrosine Kinase 4 FLT4 [124]P35916 Epoxide hydratase 2 EPHX2 [125]P34913 LYN Proto-Oncogene, Src Family Tyrosine Kinase LYN [126]P07948 Complement factor D CFD [127]P00746 Colony Stimulating Factor 1 Receptor CSF1R [128]P07333 Interleukin-1 receptor-associated kinase 4 IRAK4 [129]Q9NWZ3 P2X purinoceptor 7 P2RX7 [130]Q99572 Platelet endothelial cell adhesion molecule-1 CD31 [131]P16284 Isocitrate Dehydrogenase (NADP(+)) 1 IDH1 [132]O75874 Voltage-gated L-type calcium channel alpha-1C subunit CACNA1C [133]Q13936 Tyrosine-protein kinase TIE-2 TEK [134]Q02763 Histone deacetylase 3 HDAC3 [135]O15379 Histone deacetylase 6 HDAC6 [136]Q9UBN7 Histone deacetylase 2 HDAC2 [137]Q92769 Histone deacetylase 5 HDAC5 [138]Q9UQL6 Heat Shock Protein 90 Alpha Family Class B Member 1 HSP90AB1 [139]P08238 Butyrylcholinesterase BCHE [140]P06276 Adrenergic receptor alpha-2 ADRA2C [141]P18825 Alpha-2b adrenergic receptor ADRA2B [142]P18089 Muscarinic acetylcholine receptor M1 CHRM1 [143]P11229 Cytochrome P450 2D6 CYP2D6 [144]P10635 Histone deacetylase 7 HDAC7 [145]Q8WUI4 Histone deacetylase 4 HDAC4 [146]P56524 Histone deacetylase 9 HDAC9 [147]Q9UKV0 5-Hydroxytryptamine Receptor 3A HTR3A [148]P46098 Glucagon-like peptide 1 receptor GLP1R [149]P43220 Cell division control protein 42 homolog CDC42 [150]P60953 Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 PIN1 [151]Q13526 Lysine-specific demethylase 4C KDM4C [152]Q9H3R0 Muscarinic acetylcholine receptor M3 CHRM3 [153]P20309 Galectin-3 LGALS3 [154]P17931 Galectin-9 LGALS9 [155]O00182 Thymidylate synthase TYMS [156]P04818 Urotensin II receptor UTS2R [157]Q9UKP6 Heat Shock Protein 90 Alpha Family Class A Member 1 HSP90AA1 [158]P07900 Epoxide hydrolase 1 EPHX1 [159]P07099 Solute Carrier Family 1 Member 1 SLC1A1 [160]P43005 Protein Tyrosine Kinase 2 Beta PTK2B [161]Q14289 Neuropeptide Y receptor Y5 NPY5R [162]Q15761 Sphingosine-1-Phosphate Receptor 2 S1PR2 [163]O95136 Lysophosphatidic Acid Receptor 2 LPAR2 [164]P13569 Sphingosine-1-Phosphate Receptor 3 S1PR3 [165]Q99500 Sphingosine-1-Phosphate Receptor 1 S1PR1 [166]P21453 Platelet Derived Growth Factor Receptor Alpha PDGFRA [167]P11309 Isoprenylcysteine Carboxyl Methyltransferase ICMT [168]O60725 Monoglyceride Lipase MGLL [169]Q99685 [170]Open in a new tab Figure 1. [171]Figure 1 [172]Open in a new tab Network of HLJDD compound targets and AS targets. Notes: Drug C1 represents 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone; C2 represents 5,7,2,5-tetrahydroxy-8,6-dimethoxyflavone; C3 represents bis[(2S)-2-ethylhexyl] benzene-1,2-dicarboxylate; C4 represents 5,8,2ʹ-Trihydroxy-7-methoxyflavone; C5 represents 5,7,4ʹ-Trihydroxy-8-methoxyflavone; C6 represents (2R)-7-hydroxy-5-methoxy-2-phenylchroman-4-one. PPI Network of Common Targets By identifying the interaction score to medium confidence, a protein–protein interaction (PPI) network of the AS-related targets was formed by the STRING database and visualized using Cytoscape. The network involved 101 nodes and 900 edges, with a 19.8 average node degree and PPI enrichment p value<1.0e-16, confirming the multitarget characteristics of HLJDD. To analyze the complex PPI network, we established network topology analysis based on three parameters—degree, MCC and EPC—to filter 11 core targets, ICAM1, CD31, RAM11, MMP9, PIK3R1, AKT1, SRC, HSP90AA1, MMP2, PTK2, and HSP90AB1 ([173]Figure 2). Figure 2. [174]Figure 2 [175]Open in a new tab PPI network of common targets. The yellow squares represent the core targets. The blue circulars represent other targets. GO and KEGG Pathway Analyses To further explore the relationship of the 101 therapeutic targets with AS, GO enrichment analysis was performed using ClueGO. The representative biological processes are illustrated in [176]Figure 3A. The top 7 significantly enriched GO terms (adjusted p value <0.001) were positive regulation of nitric oxide biosynthetic process, epidermal growth factor receptor signaling pathway, lymphocyte costimulation, positive regulation of cyclin-dependent protein kinase activity, response to growth hormone, regulation of telomerase activity, and central nervous system neuron axonogenesis ([177]Figure 3B). GO analysis of common targets of HLJDD and AS is showed in [178]Figure 3C. Additionally, KEGG enrichment analysis was performed using DAVID to reveal the therapeutic mechanism underlying HLJDD in AS. Forty-four KEGG pathways were filtered with applicable thresholds p values <0.01, 20 of which with lower p values were selected for analysis, such as platelet activation, Epstein-Barr virus infection, thyroid hormone, bacterial invasion of epithelial cells, focal adhesion, and chemokine signaling pathway ([179]Figure 4). The enrichment analysis revealed that most of the therapeutic targets were associated with infection, cell adhesion and inflammation, suggesting that HLJDD may exert its effects against AS through anti-inflammatory effects. Based on the GO and KEGG analyses, we verified our prediction at the molecular level using network pharmacology, which predicted that ICAM1, CD31 and RAM11 were important biotargets of HLJDD in AS. Figure 3. [180]Figure 3 [181]Open in a new tab GO analysis. (A) The representative biological processes of therapeutic targets for the HLJDD against AS. The important terms in the group were tagged, with the related biological functional groups partially overlapped. (B) Percentage of each approach. (C) GO analysis of common targets of HLJDD and AS. The Y-axis represents significant GO biological function processes and the X-axis represents the counts of enriched targets. Notes: *Adjusted p value <0.05, **adjusted p value <0.01. Figure 4. [182]Figure 4 [183]Open in a new tab KEGG analysis for common targets of HLJDD and AS. The Y-axis represents significant KEGG pathways and the X-axis represents the ratio of enriched targets in a pathway to all common targets. The size of the nodes shows count of targets, and gradient of color represents the adjusted p value. Molecular Docking Analysis Next, molecular docking of the top 3 key targets and the 4 high-degree components were performed. It is generally believed that ligand-receptor pairs with lower-energy binding conformational stability have a higher possibility of interaction. The molecular docking results showed that the molecular docking interaction energy between the 3 key targets and the 4 high-degree components were much less than −5 kJ∙mol^−1, indicating that the 3 key targets could interact with the 4 high-degree components. The result of the molecular docking between ICAM-1 and the 4 high-degree components are presented in [184]Figure 5. Figure 5. [185]Figure 5 [186]Open in a new tab Molecular docking charts of quercetin and ICAM-1 (A), kaempferol and ICAM-1 (B), moupinamide and ICAM-1 (C), 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone and ICAM-1 (D). Potential Marker Validation Effect of HLJDD on Lipid Levels in Rabbits Compared with those in the control group, the levels of TC, TG and LDL-C were higher in the model group, and those of HDL-C were lower (p <0.01). HLJDD significantly reduced TC, TG and LDL-C and increased HDL-C (p < 0.05 or 0.01) in the HLJDD and High-HLJDD groups ([187]Figure 6). Figure 6. [188]Figure 6 [189]Open in a new tab The TC, TG, LDL-C and HDL-C levels in rabbits. Notes: *p<0.05 versus the model group; **p< 0.01 versus the model group. Data are the means ± SD. Effects on Inflammatory Cytokines Compared with the control group, the serum levels of CRP, IL-6 and TNF-α were significantly increased (p < 0.01) in the model group. Relative to the levels in the model group, the concentrations of CRP, IL-6 and TNF-α were significantly decreased (p < 0.05 or 0.01) in the HLJDD and High-HLJDD groups ([190]Figure 7A,[191]Figure 8,[192]Figure 9,[193]Figure 10). Figure 7. [194]Figure 7 [195]Open in a new tab (A) The serum CRP, IL-6 and TNF-α levels in rabbits. *p<0.05 versus the model group; **p< 0.01 versus the model group. Data are the means ± SD. (B) Representative Masson’s trichrome staining of rabbit aortic tissue (×40). Figure 8. [196]Figure 8 [197]Open in a new tab Effect of HLJDD on the protein expression levels of ICAM-1 (×40). (A) Control group (B) model group (C) HLJDD (1.5g/kg) group (D) HLJDD (3g/kg) group. (E) The integrated optical density of ICAM-1 was calculated by Ptps-2011 software. Notes: **p< 0.01 versus the model group. Figure 9. [198]Figure 9 [199]Open in a new tab Effect of HLJDD on the protein expression levels of CD31 (×40). (A) Control group (B) model group (C) HLJDD (1.5g/kg) group (D) HLJDD (3g/kg) group. (E) The integrated optical density of CD31 was calculated by Ptps-2011 software. Notes: **p< 0.01 versus the model group. Figure 10. [200]Figure 10 [201]Open in a new tab Effect of HLJDD on the protein expression levels of RAM-11 (×40). (A) Control group (B) model group (C) HLJDD (1.5g/kg) group (D) HLJDD (3g/kg) group. (E) The integrated optical density of RAM-11 was calculated by Ptps-2011 software. Notes: **p< 0.01 versus the model group. Histopathological Examination of Rabbit Aortic Tissue Masson’s trichrome staining was performed. The rabbits in the model group had collagen fibers in their ECs. By contrast, the rabbits in the control group had no collagen fibers. Compared with the model group, the rabbits in the HLJDD group had thinner collagen fibers ([202]Figure 7B). Immunohistochemistry Analysis Using tissue immunofluorescence, the protein expression of ICAM-1 and RAM-11 was significantly increased (p < 0.01) and that of CD31 was significantly decreased (p < 0.01) in the model group compared with that in the control group. Additionally, ICAM-1 and RAM-11 expression was significantly downregulated (p < 0.01), while that of CD31 was significantly upregulated (p < 0.01) in the HLJDD group at all doses ([203]Figures 8–10). Discussion AS is characterized by various biological processes, including vascular injury, inflammation, oxidation of low-density lipoprotein (LDL) cholesterol, lipid deposition, cellular differentiation, and neointimal hyperplasia.[204]19,[205]20 AS leads to lipid accumulation, extracellular matrix protein deposition and calcification of the arterial intima and media, resulting in decreased arterial elasticity.[206]21 HLJDD exhibits extensive pharmacological activities with multiple targets and pathways, benefiting AS treatment. However, because of the limitations of TCM research, conducting in-depth studies on the potential mechanisms of drugs is challenging. The network pharmacology approach, which integrates systems biology and in silico technologies, is beneficial for mechanistic studies of Chinese medicine.[207]22 In the current study, we used this approach to confirm that HLJDD positively affects AS treatment. In the TCM system, compounds lacking proper pharmacokinetic properties cannot reach target organs to exert biological activities. In the current study, the compounds in HLJDD with OB ≥ 30% and DL index ≥ 0.18 were considered pharmacokinetically active because they might be absorbed and distributed in the human body. Compounds with a high degree in the compound–target network may account for the major therapeutic effects of HLJDD on AS. In this study, quercetin was the most significant compound, followed by kaempferol, moupinamide and 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone. Quercetin is a dietary flavonoid compound extracted from various plants, such as apples and onions. Previous studies have revealed its anti-inflammatory, anti-cancer, antioxidant and anti-apoptotic activities.[208]23 Clinical application and pharmacological studies have found that quercetin might prevent the onset of atherosclerosis-related acute aortic syndromes through its anti-inflammatory and endothelial cell-protective effects.[209]24 Kaempferol is an anti-inflammatory flavonoid commonly found in plants.[210]25 Oxidized low-density lipoprotein (ox-LDL) induces endothelial cell (EC) apoptosis, and kaempferol was reported to alleviate ox-LDL-induced apoptosis of human umbilical vein endothelial cells and provide benefits for atherosclerosis treatment.[211]26 Moupinamide, also known as N-trans-feruloyltyramine (NTF), is an active phenylpropanoid compound that possesses antioxidant, antimicrobial, anti-melanogenesis and anticancer activities;[212]27 thus, it may affect AS treatment. 5-Hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone, also called gardenin A (Gar-A), exhibits a broad spectrum of biological properties, including anticancer, antiatherogenic and neuroprotective effects.[213]28 Steatotic HepG2 cells treated with Gar-A showed a significant reduction in lipid accumulation concentrations in vitro. In hyperlipidemic rats, the treatment significantly reduced the lipid levels at the synthesis phase. Treatment of the animals with Gar-A significantly lowered steatosis and the transaminase levels. Other biochemical parameters, such as TC, TG, LDL-c, ALP and ACP, were also decreased significantly.[214]29 Treatment with Gar-A significantly lowered hyperlipidemia and fat accumulation in the liver, suggesting new options for atherosclerosis treatment. Our network pharmacology analysis predicted that the important predictive biotargets of HLJDD in AS were ICAM-1, CD31, and RAM-11. Studies have found that the endothelial cells, intima and matrix on the arterial wall of patients with atherosclerosis all express ICAM-1. ICAM-1 is a transmembrane protein that plays an important role in innate and adaptive immune responses and is involved in the interaction between antigen-presenting cells and T cells and the migration of leukocytes through the endothelium to the site of inflammation.[215]30 The activation of endothelial cells mainly performed by cytokines. Some cytokines induce the expression of leukocyte and monocyte adhesion molecules on the endothelial surface, particularly intercellular adhesion molecules. Monocytes and T lymphocytes accumulate in the lining of blood vessel walls mediated by these adhesion molecules. Specific chemokines cause smooth muscle cells to migrate from the culture medium to the inner membrane, and then cell proliferation occurs.[216]31 The only constitutively expressed factor in vascular interface cells is the transhomophilic inhibitory immune receptor CD31, which may play an important role in vascular homeostasis. Notably, experiments have shown that CD31 signal transduction prevents blood adhesion, chronic inflammatory diseases and platelet thrombosis.[217]32 CD31 shows unique cross-affinity and receptor co-signaling properties; thus, it can coordinate the cross-reaction of biomechanics, metabolism and inflammatory stimuli to exert cell-specific effects. CD31 is at the center of mediating mechanical, metabolic and immunological changes and provides a single target with beneficial pleiotropic effects in the cardiovascular system.[218]33 RAM-11 and HIF-1α are highly positively correlated, and the target genes regulated by HIF-1α are involved in cell proliferation, differentiation and survival. Smooth muscle cells and macrophages play important roles in the formation and development of AS. Additionally, they secrete vascular growth factors and decompose the basement membrane to promote new blood vessel formation in AS. Studies have shown that HIF-1α is involved in the infiltration and activation of macrophages and smooth muscle cell migration and proliferation in AS lesions, thereby promoting new blood vessel formation in plaques, a key event in AS lesions.[219]34 The KEGG results indicated that HLJDD regulates leukocyte transendothelial migration as the pharmacological mechanism of the therapeutic effect of HLJDD against AS. Inflammation is tightly regulated by the body and associated with the transient crossing of leukocytes through the blood vessel wall, a process called transendothelial migration (TEM) or diapedesis.[220]35 TEM is one of the crucial steps during inflammation.[221]36 Pro-inflammatory cytokines are synthesized and secreted into the blood following over-activation of the NF-κB signaling pathway, causing oxidative stress and inflammation that result in endothelial cell damage. The adhesion molecule ICAM-1 is a central mediator of TEM, and interfering with ICAM-1 is sufficient to block transmigration.[222]35,[223]36 The high expression of ICAM-1 and other adhesion molecules further promotes the adhesion and migration of monocytes in the early stage of atherosclerosis. A reduced expression of ICAM-1 inhibits the migration and adhesion of monocytes, antagonizing proliferation in atherosclerotic vessels.[224]21 TEM involves an orchestrated series of events within endothelial cells to facilitate the passage of leukocytes while maintaining tight apposition to prevent plasma leakage.[225]35 Thus, targeting leukocyte transendothelial migration may be a potential therapeutic approach for AS. In the present study, we investigated the impact of HLJDD on AS development by establishing hypercholesterolemic rabbit models fed a high-fat diet. The results reflected that HLJDD might treat AS mainly by reducing TC, TG and LDL-C and increasing HDL-C, upregulating CD31 expression, reducing ICAM-1 and RAM-11 expression, and downregulating inflammatory factors, including CRP, IL-6 and TNF-α. These results support the network pharmacology data and demonstrate that HLJDD affects the expression of core genes and alters the leukocyte transendothelial migration signaling pathway. In conclusion, the pharmacological mechanism by which HLJDD-treated AS was investigated by combining network pharmacology prediction and experimental validation. The core targets identified included ICAM-1, CD31 and RAM-11 in the network of HLJDD and AS, and we demonstrated that HLJDD might affect AS mainly by upregulating CD31 expression and reducing ICAM-1 and RAM-11 expression. Moreover, leukocyte transendothelial migration plays an important regulatory role in the mechanism of HLJDD in AS treatment. This study has some drawbacks that require further research, which include the need for in-depth study on bioactive components and further experimental validation to verify the effect of the HLJDD on AS. However, this study confirmed the feasibility of exploring AS treatment using the classical prescription of HLJDD based on network pharmacology. Funding Statement This work was supported by National Natural Science Foundation of China (81673923), Foundation for scientific research platforms and projects in Higher Education of Guangdong Province in China (2018KQNCX038), and Incubation of Innovative Program of First Clinical Medical College of Guangzhou University of Chinese Medicine (2018XXDT01). Disclosure The authors declare that there are no conflicts of interest. References