Abstract [48]graphic file with name ao3c10163_0010.jpg The Qilongtian capsule (QLT) is a Chinese patent medicine that has been approved for the treatment of chronic obstructive pulmonary disease (COPD). However, the precise pharmacodynamic material basis and molecular mechanism have not been well illustrated. In this study, we identified the effect of QLT on COPD through a cigarette smoke extract (CSE)/lipopolysaccharide (LPS) induced COPD mice model. The absorption of blood components in QLT were identified using ultrahigh performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Network pharmacology was used to predict the potential targets and therapeutic mechanisms of QLT, which were further validated using in vivo experiments and molecular docking. Pharmacodynamic studies revealed that QLT could ameliorate pulmonary function and pulmonary pathology, reduce collagen fiber accumulation, and attenuate inflammatory responses in mice with CSE/LPS induced COPD. A total of 21 components of QLT absorbed in the blood were detected. Network pharmacology analysis indicated that TNF, IL-6, EGFR, and AKT1 may be the core targets, mainly involving the MAPK signaling pathway. Besides, Sachaloside II, Ginsenoside Rh1, Ginsenoside F1, Rosiridin, and Ginsenoside Rf were the key compounds. Molecular docking results showed that the key components could spontaneously bind to EGFR and MAPK to form a relatively stable conformation. In vivo experiments revealed that QLT could suppress the activation of the EGFR/MAPK signaling pathway, thereby improving lung injury in mice with COPD. Overall, these findings provide evidence for the treatment of COPD with QLT. 1. Introduction Chronic obstructive pulmonary disease (COPD) is a respiratory disease that mainly results from exposure to toxic particles and gases. It is characterized by an expiratory tract obstruction and recurrent symptoms of the respiratory system. Airway inflammation, oxidative stress, protease–antiprotease imbalance, and apoptosis are the commonly reported pathogenesis of COPD.^[49]1−[50]3 Moreover, the World Health Organization speculates that COPD will become the third-highest cause of mortality worldwide by 2030.^[51]4,[52]5 Modern medicine mainly uses long-acting bronchodilators (LABD) and inhaled corticosteroids (ICS), including roflumilast, tiotropium bromide, and budesonide, for the treatment of COPD. The combination of ICS and LABD to form a double or triple therapy is commonly used as first-line treatment.^[53]6−[54]8 However, long-term use of bronchodilators or glucocorticoids can cause side effects such as arrhythmia, metabolic disorders, and immune suppression.^[55]9 Additionally, the treatment effect is not attainable in patients with stable COPD.^[56]10−[57]12 Compared with Western medicine, Chinese medicine has a long history of application, plays a vital role in the management of chronic respiratory diseases with fewer side effects, and can be used to prevent and control multiple targets and pathways. Thus, seeking the help of an herbal medicine may be a new strategy for treating COPD. The Qilongtian capsule (QLT) is a clinical prescription developed by the Kunming Municipal Hospital of Traditional Chinese Medicine (Yunnan, China). It has been used in treating COPD in several hospitals in Yunnan since 2008 and has achieved ideal clinical efficacy. QLT was also approved by the Yunnan Provincial Emergency Approval Document for the prevention and control of COVID-19 (approval number 2020003A). QLT comprises three Chinese herbal medicines, namely, Rhodiola crenulate (Hongjingtian; HJT), Pheretima aspergillum (Dilong; DL), and Panax notoginseng (Sanqi; SQ), with the functions of tonifying Qi and strengthening healthy Qi, removing blood stasis and dredging collaterals, and eliminating phlegm and relieving asthma.^[58]13 HJT is the sovereign drug and has been reported to have anti-inflammatory, immunomodulatory, antioxidant, and adaptogenic effects^[59]14,[60]15 with clinical efficacy in the treatment of COPD.^[61]16,[62]17 SQ, a minister drug, is widely used to prevent and treat various conditions. It has good effects in anti-inflammation,^[63]18−[64]20 antitumor capabilities,^[65]21 promoting blood circulation and removing blood stasis,^[66]22,[67]23 immune regulation,^[68]24 neuroprotection,^[69]25 antioxidant capabilities,^[70]26,[71]27 and other aspects.^[72]28 DL as a supplementary drug is recorded in the Shennong Materia Medica Classic, which has the effects of clearing heat and relieving fright, promoting circulation, and calming asthma and diuretic symptoms.^[73]29 Owing to the regional characteristics of “plateau hypoxia, changeable climate, and numerous smokers”, residents of the Yunnan-Guizhou plateau are prone to COPD. A randomized controlled clinical trial demonstrated that treatment with QLT had no significant effect on liver and kidney function (AST, ALT, BUN, Scr levels) and coagulation function (PT, APTT, TT, FIB) of patients with stable COPD. Besides, the levels of TGF-β1 and MMP-9, CAT score, symptom score, and total score reduced significantly, and the pulmonary function indices (FVC, FEV1, FEV1/FVC) increased significantly after treatment of patients with COPD with QLT.^[74]30 Furthermore, pharmacological research has shown that QLT can ameliorate the oxidative stress balance by regulating the levels of Nrf2 and DJ-1, thereby exerting a certain therapeutic effect on rats with COPD.^[75]31 The above research provides new insights into the protective effect of QLT in COPD. The efficacy of QLT in treating diseases is thought to be linked to its multicomponent, multitarget, and multipathway effects. However, the effective components and mechanisms of action of QLT in treating COPD remain unclear. Hence, in order to explore the therapeutic effect of QLT, a mouse model of COPD induced by cigarette smoke extract (CSE)/lipopolysaccharide (LPS) was established. Next, the pharmacodynamic substances and molecular mechanisms were explored by using a combination of UPLC-Q-TOF-MS/MS and network pharmacology, which were further validated by using molecular docking and in vivo experiments. In conclusion, this study sets the stage for the further exploration of the mechanism of action of QLT against COPD in a clinical setting. 2. Results 2.1. Effect of QLT on the Pulmonary Function in Mice with COPD Airflow limitations are the hallmark features of COPD, which lead to a reduction in pulmonary function. Therefore, unrestrained pulmonary function was determined to evaluate the therapeutic effects of QLT on mice with COPD. The 50% vital capacity (EF50), minute ventilation (MV), and peak expiratory flow rate (PEF) after treatment with CSE/LPS decreased markedly in comparison with those in the control group (p < 0.01) and increased markedly after treatment with high-dose QLT (4.8 g/kg) and Rof (5 mg/kg) compared with those in the model group (p < 0.05 or p < 0.01) ([76]Figure [77]1 ), suggesting that QLT could improve the pulmonary function that was damaged by CSE/LPS. Figure 1. [78]Figure 1 [79]Open in a new tab Effect of QLT on the pulmonary function. EF50 (A), MV (B), and PEF (C) were examined using unrestrained whole-body plethysmography. *p < 0.05 and **p < 0.01 vs the model group; ^##p < 0.01 vs the control group (n = 6). 2.2. Effect of QLT on Pulmonary Histological Damage in Mice with COPD H&E staining was used to determine the protective effects of QLT in pulmonary histological damage. As shown in [80]Figure [81]2 , the lung tissues of mice in the control group showed an unobvious airway inflammation around the bronchial epithelium, and the structures of the lung alveolar cavity were intact. However, mice exposed to CSE/LPS exhibited severe pathological changes. Bronchial inflammatory cell infiltration, thickening of the bronchial wall, expansion of the alveolar cavity, and thinning of the alveolar wall were observed in the model group. QLT (1.2, 2.4, and 4.8 g/kg) and Rof (5 mg/kg) treated mice exhibited an alleviation in CSE/LPS induced pathologic changes in the lungs compared with those in the model group. The improvement was more obvious with an increase in QLT dosage. These results indicate that QLT ameliorated CSE/LPS induced pathological lesions in the lungs. Figure 2. Figure 2 [82]Open in a new tab Effect of QLT on pulmonary histological damage in mice with COPD. Representative micrographs of H&E staining. (A) Peribronchial region. (B) Alveolar region. The green arrow represents thickening of the bronchial wall, and the blue arrow represents incomplete alveolar structure. 2.3. Effect of QLT on Collagen Deposition in Mice with COPD Next, Masson’s staining was used to determine the role of QLT in collagen deposition. As shown in [83]Figure [84]3 , CSE/LPS treatment induced fibrosis in the lung tissues of mice, and there was a significantly increased area of fibrosis compared with that in mice in the control group (p < 0.01). After QLT (1.2, 2.4, and 4.8 g/kg) treatment, the fibrotic area in the lung tissues reduced in a dose-dependent manner compared with that of mice in the model group (p < 0.05 or p < 0.01), indicating the inhibition of CSE/LPS induced fibrosis. The administration of Rof (5 mg/kg) also led to similar effects (p < 0.01). Therefore, QLT could ameliorate CSE/LPS induced accumulation of collagen fibers. Figure 3. [85]Figure 3 [86]Open in a new tab Effect of QLT on collagen deposition in mice with COPD. (A) Representative micrographs of Masson’s staining. (B) Fibrotic areas were quantified using ImageJ software. *p < 0.05 and **p < 0.01 vs the model group; ^##p < 0.01 vs the control group (n = 6). 2.4. Effect of QLT on the Inflammatory Cytokines in Mice with COPD The inflammatory response may interfere with the normal repair and defense mechanisms of the lung, resulting in emphysema and small-airway fibrosis. Thus, the inflammatory cytokine levels in the lung homogenate and serum were determined by ELISA. The results showed that after exposure to CSE/LPS, IL-1β and IL-6 levels in the lung and serum increased significantly compared with those in the control group (p < 0.01). However, the increments were attenuated after QLT (1.2, 2.4, and 4.8 g/kg) and Rof (5 mg/kg) intervention compared with those in model mice (p < 0.05 or p < 0.01) ([87]Figure [88]4 ). Moreover, these levels decreased in a dose-dependent manner after treatment with QLT. These findings indicated that QLT could alleviate COPD by decreasing the inflammatory response. Figure 4. [89]Figure 4 [90]Open in a new tab Effect of QLT on inflammatory cytokines levels. IL-1β (A) and IL-6 (B) levels in the lung homogenate and IL-1β (C) and IL-6 (D) levels in the serum. *p < 0.05 and **p < 0.01 vs the model; ^##p < 0.01 vs the control (n = 6). 2.5. UPLC-Q-TOF-MS/MS Analysis of Active Components of QLT To explore the pharmacodynamic material basis of QLT in treating COPD, UPLC-Q-TOF-MS/MS was used to analyze the QLT components in the serum of mice after oral administration of QLT. A total of 74 compounds were identified and inferred from QLT, including 14 flavonoids, 16 saponins and terpenoids, three phenylpropanoids, 11 organic acids, and other components ([91]Figure S1 and [92]Tables S2 and S3). A total of 21 original constituents migrating to blood were identified, consisting of six flavonoids, 11 saponins, and four other components ([93]Figure [94]5 and [95]Tables [96]1 and [97]S1). Figure 5. [98]Figure 5 [99]Open in a new tab UPLC-Q-TOF-MS/MS to determine the absorption of blood components in QLT. Total ion chromatogram in positive ionization (A) and negative ionization (B) modes. The mass spectrometry cleavage pathways of representative components in positive/negative ion modes, including Salidroside (C), Ginsenoside Rg[1] (D), and 7-hydroxycoumarin (E). Table 1. Identification of Original Constituents Migrating to Blood Based on UPLC-Q-TOF-MS/MS. no. RT (min) chemical formula selected ion mass-to-charge ratio (m/z) theoretical mass (Da) measured mass (Da) error (ppm) MS/MS compund source 1[100]^a 4.27 C[14]H[20]O[7] [M – H]^− 300.1209 299.1136 299.1146 3.2 137.0636, 119.0350, 101.0234, 89.0258 Salidroside HJT 2 5.11 C[11]H[20]O[6] [M + Na]^+ 248.126 271.1152 271.115 –0.7 203.0511, 165.0573, 97.1004 Crenulatin HJT 3 5.31 C[14]H[24]O[7] [M + Na]^+ 304.1522 327.1416 327.1412 –1.3 165.0859, 98.9852 Creoside I HJT 4 5.96 C[14]H[26]O[7] [M + COOH]^− 306.1679 351.165 351.1678 8.1 304.8562, 161.0030, 101.0247 Creoside II HJT 5 6.4 C[9]H[8]O[3] [M – H]^− 164.0473 163.0401 163.0395 –3.9 119.0520, 117.0347, 93.0353 p-coumaric acid HJT, SQ 6 7.43 C[16]H[30]O[8] [M – H]^− 350.1941 349.1868 349.1863 –1.3 161.0016, 141.0921 Rhodioloside D HJT 7 7.54 C[16]H[28]O[7] [M + COOH]^− 332.1835 377.1806 377.1819 3.3 149.0239, 103.4700 Rosiridin HJT 8 8.1 C[7]H[6]O[3] [M – H]^− 138.0317 137.0244 137.0254 6.9 108.0223, 93.0366 p-hydroxybenzoic acid HJT 9[101]^a 8.53 C[42]H[72]O[14] [M + COOH]^− 800.4922 845.4893 845.4901 0.9 799.4943, 637.4310, 475.3825 Ginsenoside Rg[1] SQ 10 8.66 C[42]H[72]O[14] [M + COOH]^− 800.4922 845.4893 845.4933 4.7 799.4904, 637.4341, 475.3849 Ginsenoside Rf SQ 11 9.65 C[19]H[36]O[10] [M – H]^− 424.2309 423.2236 423.2246 2.5 291.1802, 113.0247, 101.0261 Rhodiooctanoside HJT 12 9.65 C[22]H[38]O[12] [M – H]^− 494.2363 493.2291 493.2311 4.2 447.2233, 191.0564, 149.0462 Rhodioloside C HJT 13 9.66 C[21]H[36]O[10] [M – H]^− 448.2309 447.2236 447.2245 2.1 301.0381, 161.0008, 135.0460 Kenposide A HJT 14 9.67 C[21]H[34]O[10] [M + H]^+ 446.2152 447.2225 447.222 –1.1 343.0161, 315.1789, 207.0326, 147.0650 Sachaloside II HJT 15 10.03 C[9]H[6]O[3] [M + H]^+ 162.0317 163.039 163.0391 0.8 117.0567, 107.0498, 91.0541 7-hydroxycoumarin HJT 16 10.88 C[42]H[72]O[13] [M + COOH]^− 784.4973 829.4944 829.4977 4 783.4899, 475.3812 Ginsenoside Rg[2] SQ 17 10.98 C[36]H[62]O[9] [M + COOH]^− 638.4394 683.4365 683.4392 4 475.3805, 475.3805 Ginsenoside F1 SQ 18 10.93 C[21]H[20]O[11] [M + Na]^+ 448.1006 471.0898 471.0898 –7.3 409.0483, 383.0637, 339.0402, 131.0864 Rhodionin HJT 19 11.57 C[36]H[62]O[9] [M + COOH]^− 638.4394 683.4365 683.4384 2.8 637.4341, 475.3849, 161.0470, 113.0247 Ginsenoside Rh1 SQ 20 14.36 C[17]H[26]O[3] [M – H]^− 278.1882 277.1809 277.1827 6.6 233.1925, 205.1622, 175.7251 Panaxytriol SQ 21 15.68 C[16]H[28]O[8] [M – H]^− 348.1784 347.1711 347.1732 5.9 301.1694, 285.1367, 217.0746 Rhodioloside A HJT [102]Open in a new tab ^a Means the compositions identified by comparison with the reference substance. 2.6. Network Pharmacology Analysis of QLT in Treating COPD Forty-five differentially expressed genes (DEGs) were upregulated, and 46 DEGs were downregulated ([103]Figures [104]6 A and [105]6B) in the Gene Expression Omnibus (GEO) database. Based on the SwissTargetPrediction database search, 375 targets predicted by 21 constituents were absorbed in the blood. Combining GEO, DisGeNET, and Genecards databases, 675 targets associated with COPD were collected. The components–targets network was constructed to further reveal the key components of QLT in treating COPD. This network comprised 396 nodes and 944 edges ([106]Figure [107]6D), showing that multiple ingredients act on multiple targets; among them, Sachaloside II, Ginsenoside Rh1, Ginsenoside F1, Rosiridin, and Ginsenoside Rf were the top five nodes with higher betweenness centrality, closeness centrality, and degree and were thought to be the key compounds. Figure 6. [108]Figure 6 [109]Open in a new tab Network pharmacology analysis. (A) Volcano map of DEGs in the lungs between COPD patients and healthy controls. (B) Heatmap of DEGs between COPD patients and healthy controls. (C) Venn diagram. (D) Compounds–targets network. The blue rectangles represent targets; the pink arrows represent compounds. (E) PPI network. (F) GO enrichment. (G) KEGG enrichment. There were 57 overlapping targets between QLT and COPD that were acquired using the Venn diagram ([110]Figure [111]6 C). These targets were used to construct the protein–protein interaction (PPI) network ([112]Figure [113]6E). The larger nodes represent a higher degree of and greater contribution to the intersection. The result showed that TNF, IL6, EGFR, AKT1, IFNG, HIF1A, STAT3, IL1B, CASP3, and MTOR, which have the highest degree, might be the core targets. Besides, to reveal the possible signaling pathways of QLT to determine the therapeutic effect in COPD, Metascape was used to perform GO and KEGG analysis of the targets in the PPI network. It showed that the numbers of CC, MF, and BP were 58, 72, and 1257, respectively (p < 0.05, [114]Figure [115]6 F). According to the lowest p value, the top five BPs were positive regulation of MAP kinase activity, positive regulation of protein kinase B signaling, positive regulation of ERK1 and ERK2 cascades, positive regulation of gene expression, and negative regulation of the apoptotic process. The top five CCs were receptor complex, membrane raft, extracellular space, extracellular region, and plasma membrane. The top five MFs were endopeptidase activity, protein tyrosine kinase activity, cytokine activity, protein serine/threonine/tyrosine kinase activity, and protein kinase activity. After KEGG pathway analysis, a total of 167 signaling pathways were obtained (p < 0.05, [116]Figure [117]6G). The top five signaling pathways are the EGFR, MAPK, PI3K-AKT, HIF-1, and TNF signaling pathways. 2.7. Molecular Docking Based on network pharmacology results, compounds with the top five degree value in the components–targets network were screened, including Sachaloside II, Ginsenoside Rh1, Ginsenoside F1, Rosiridin, and Ginsenoside Rf. Thus, these compounds were docked with EGFR (PDB ID: [118]3G5X) and MAPK (PDB ID: [119]6ZWP) for further validation. The results revealed that the targets could spontaneously bind to the components to form a relatively stable conformation (the binding affinity was < −6 kcal/mol) ([120]Table [121]2 ), indicating that these key compounds demonstrated good biological activity, which was consistent with the above results. The visualization results are shown in [122]Figure [123]7. Table 2. Binding Affinity (kcal/mol) between Targets and Components. EGFR __________________________________________________________________ MAPK __________________________________________________________________ component binding affinity binding residues binding affinity binding residues Sachaloside II –8.1 Tyr –8.2 Arg, Lys, Asp, Ile, Phe Ginsenoside Rh1 –7.9 Gln, Asn, Asp, Ala –7.5 Thr, Val Ginsenoside F1 –7.9 Leu, Asn, Asp –7.7 Leu, Val Rosiridin –6.8 Glu, Ala –6.5 Met, His Ginsenoside Rf –8.3 Gln, Gly, Asn, Thr, Trp –7.9 Phe [124]Open in a new tab Figure 7. [125]Figure 7 [126]Open in a new tab Partial 3D digital model of molecular docking between compounds and proteins. 2.8. Experimental Validation of the Molecular Mechanism The MAPK signaling pathway may be a core pathway for the treatment of COPD based on KEGG enrichment analysis. The experimental results suggested that CSE/LPS significantly increased the phosphorylation levels of ERK, p38, and JNK compared with that in the control group (p < 0.01), but QLT treatment reversed this effect compared with that in the model group (p < 0.05) ([127]Figures [128]8 A–[129]8F). Meanwhile, compared with the control group, the mRNA expression of ERK, p38MAPK, and JNK in the lung tissue of the model group showed a significant increase trend (p < 0.01). After QLT treatment, the expression of mRNA was significantly downregulated (p < 0.05 or p < 0.01) ([130]Figures [131]8H–[132]8J). Figure 8. [133]Figure 8 [134]Open in a new tab Experimental validation of the molecular mechanism. (A–F) Western blotting of p-ERK, ERK, p-p38, p38, p-JNK, and JNK using the lung tissues of mice (n = 3). (G) Representative micrographs of EGFR in the immunohistochemical assay. (H–K) qRT-PCR to determine the relative mRNA expression of ERK, p38MAPK, JNK, and EGFR in the lung tissues of mice (n = 6). (L) EGFR staining areas were quantified using ImageJ software (n = 6). Immunohistochemistry images were taken at ×400 magnification (scale bar: 50 μm). *p < 0.05 and **p < 0.01 vs the model; ^##p < 0.01 vs the control. Immunohistochemistry results showed that the model group had significantly elevated levels of EGFR compared with those in the control group (p < 0.01). Interestingly, EGFR mRNA and protein expression were significantly inhibited in mice treated with QLT (p < 0.05 or p < 0.01) ([135]Figures [136]8 G, [137]8K, and [138]8L) compared with the observations in the model group. 3. Discussion QLT has been clinically proven to have favorable anti-COPD effects; however, its pharmacodynamic mechanism lacks in-depth studies. The pharmacological studies of QLT that have been reported so far usually use pulmonary hypertension models, which is not fully consistent with its clinical efficacy. Smoking is the most common risk factor for COPD, and CSE is the ideal stimulant to establish an animal model of COPD by using most of the ingredients in cigarette smoke. LPS is a cell wall component of Gram-negative bacteria; it can be used as a stressor to stimulate macrophages and epithelial cells, facilitate the release of inflammatory cytokines, and cause the acute exacerbation of COPD.^[139]32 Therefore, we chose intranasal administration of CSE and LPS to establish a mouse model of COPD in this study. The model group mice showed slow weight gain, thickening of bronchial walls and infiltration of inflammatory cells, irregular enlargement of alveolar cavities, thinning and rupture of alveolar walls, and significant pathological damage to lung tissue, indicating the successful establishment of the COPD model. Incomplete reversible airflow restriction is an essential physiological characteristic in the occurrence and development of COPD, and decreased pulmonary function can reflect the severity of airway obstruction.^[140]33 Moreover, cigarette smoke inhalation, bacterial infections, or harmful gases may induce the stimulation of inflammatory cells and the release of multiple inflammatory mediators (IL-6, IL-1β), which, in turn, cause a sustained cascade of the inflammatory response, mucus hypersecretion, small airway fibrosis, and lung tissue injury.^[141]34−[142]37 In addition, fibrosis observed predominantly around the small airways is associated with decreased lung function in patients with COPD.^[143]38 Interestingly, we found that QLT effectively increased the pulmonary function index EF50, MV, and PEF; relieved pulmonary inflammatory responses by suppressing the levels of IL-1β and IL-6 released in the serum and lung tissue; and reversed pathological changes and peribronchial collagen accumulation in the lung tissues of mice with CSE/LPS induced COPD. UPLC-Q-TOF-MS/MS identified a total of 21 prototype components, mainly saponins and flavonoids. Ginsenoside alleviates the cigarette smoke induced pulmonary epithelial–mesenchymal transition in both COPD rats and HBE cells via inhibition of the TGF-β1/Smad pathway.^[144]39,[145]40 Rhodiola glycoside inhibits the production of proinflammatory cytokines and M1 polarization of alveolar macrophages in mouse serum and lungs induced by cigarette smoke. In addition, the administration of Rhodiola glycoside significantly inhibits the protein levels of the MAPK/NF-κB pathway.^[146]41,[147]42 The KEGG results indicated that MAPK is a core signaling pathway for treating COPD with QLT, which was predicted using network pharmacology. The MAPK pathway can be activated when exposed to cigarette smoke, LPS, or cytokines.^[148]43 MAPK signaling is important in regulating COPD-associated phenotypes, including airway inflammation, mucus secretion, and airway remodeling.^[149]44,[150]45 It has been reported that phosphorylation of ERK1/2 and p38 MAPK in the MAPK pathway is a key step that mediates the expression of IL-1β and TNF-α.^[151]46 EGFR can be activated by cigarette smoke and is involved in airway remodeling, chemokine overexpression, pulmonary fibrosis, mucin hypersecretion, and goblet cell metaplasia.^[152]47−[153]49 Goblet cell hypertrophy and hyperplasia are features observed in cigarette smokers that lead to epithelial mucin hypersecretion. The results from experimental validation indicated that the phosphorylation of the EGFR/MAPK signaling pathway that increased in mice with COPD could be suppressed after the administration of QLT ([154]Figure [155]9 ). Furthermore, molecular docking revealed that the key compounds were relatively stable in combination with the core targets. Overall, these results contribute to further exploration of the molecular mechanism of QLT to provide further support for the use of QLT in treating COPD. However, the active ingredients of QLT in the treatment of COPD have not been experimentally verified. Further exploration is needed to provide evidence for the development of the QLT prescription. Figure 9. [156]Figure 9 [157]Open in a new tab Molecular mechanisms. CSE/LPS stimulation can promote the activation of the MAPK pathway, thereby promoting the development of COPD, while QLT can downregulate the expression of EGFR, thereby inhibiting MAPK pathway activity and hindering the development of COPD. 4. Conclusions QLT could alleviate airflow limitation, pulmonary histological damage, collagen deposition, and inflammatory responses in mice with CSE/LPS induced COPD. UPLC-Q-TOF-MS/MS and network pharmacology were used to predict the potential pharmacodynamic substances and molecular mechanisms of QLT in treating COPD. Sachaloside II, Ginsenoside Rh1, Ginsenoside F1, Rosiridin, and Ginsenoside Rf may be the key pharmacodynamic substances in this process. Verification of the prediction using in vivo experiments and molecular docking revealed that the mechanism of action may be closely related to the inhibition of the EGFR/MAPK signaling pathway. Therefore, QLT may be a promising therapeutic agent to treat COPD. Our study serves as an important reference to further elucidate the pharmacological mechanism and promote the clinical use of QLT. 5. Materials and Methods 5.1. Chemicals and Reagents Qilongtian capsules were provided by Kunming Municipal Hospital of Traditional Chinese Medicine. Enzyme-linked immunosorbent assay (ELISA) kits for interleukin (IL)-6 and IL-1β were obtained from YiFeiXue Biotechnology (Nanjing, China). TRIzol reagent was obtained from Invitrogen Life Technologies (Carlsbad, USA). The Hifair V one-step RT-gDNA digestion SuperMix for quantitative polymerase chain reaction (qPCR) kit, radio-immunoprecipitation assay (RIPA), and bicinchoninic acid (BCA) protein quantification kit were obtained from Yeasen Biotechnology Co., Ltd. (Shanghai, China). TOROGreen qPCR Master Mix kits were purchased from Toroivd Technology Co., Ltd. (Nantong, China). Anti-EGFR rabbit pAb was obtained from Servicebio Biotechnology Co., Ltd. (Wuhan, China). Antibodies of ERK1/2 rabbit pAb, phospho-ERK1/2 (Tyr204/Tyr187) rabbit pAb, p38 (5A1) mouse mAb, phospho-p38 (Thr180/Tyr182) rabbit pAb, JNK rabbit mAb, phospho-JNK (Thr183) rabbit pAb, and β-actin (8F10) mouse mAb were purchased from Zen Biotechnology Co., Ltd. (Chengdu, China). Polyvinylidene fluoride (PVDF) membranes were obtained from PALL Life Company (New York, USA). Ultrapure water was obtained using a Milli-Q water purification system (Millipore, Bedford, USA). Phosphate buffered saline was purchased from KeyGEN Biotechnology Co., Ltd. (Nanjing, China). Acetonitrile (MS-grade) was purchased from Merck (Darmstadt, Germany). LPS and formic acid (MS grade, 98% purity) was purchased from Sigma-Aldrich (Saint Louis, USA). Cigarettes were purchased from China Tobacco Hunan Industrial Co., Ltd. (Hunan, China). Other reagents and chemicals were all of analytical grade and purchased from commercial reagent companies. 5.2. Preparation and Quality Control of QLT QLT is composed of HJT, DL, and SQ in a 10:5:2 ratio and was provided by Kunming Municipal Hospital of Traditional Chinese Medicine. The raw medicinal materials were boiled with 10 times their volume of water (w/v) twice for 2 h each. The extracts were filtered, concentrated, and dried to obtain the QLT extract. Then, 70% ethanol was used as a wetting agent, followed by granulation, drying, and filling of capsules. 5.3. Preparation of CSE Each cigarette contained 10 mg of tar, 1 mg of nicotine, and 13 mg of carbon monoxide. While burning, the smoke from one cigarette was drawn into 1 mL of PBS using a vacuum pump, and the dissolved smoke was filtered through a 0.22 μm filter. The CSE was freshly prepared for each experiment. 5.4. Animal Studies A total of 36 male C57BL/6 mice at 6 weeks of age (18–22 g) were purchased from Jiangsu Huachuang Xinnuo Pharmaceutical Technology Co., Ltd. (Taizhou, China). The mice were reared in a standard environment of 22–25 °C and 60% humidity and subjected to a 12/12 h light/dark cycle with free access to food and water. After 1 week of adaptive feeding, the mice were randomly divided into the following six groups (n = 6 mice/group): (1) negative control group (control); (2) COPD model group (model); (3) positive control group with roflumilast (Rof, 5 mg/kg); (4) QLT low-dose group (QLT-L, 1.2 g/kg); (5) QLT middle-dose group (QLT-M, 2.4 g/kg); and (6) QLT high-dose group (QLT-H, 4.8 g/kg). According to the conversion formula, 1.2 g/kg for each mouse daily was equivalent to clinical usage in humans. Therefore, we chose 1.2, 2.4, and 4.8 g/kg as the low, middle, and high doses of the drug, respectively, for administration. We referred to the modeling method reported in the literature and adjusted the modeling dose according to our pretest. Except those in the negative control group, all other experimental mice with COPD were intranasally administered 25 μL of CSE once daily; 10 μL of LPS (1 mg/mL) was intranasally administered to each mouse twice a week. An equal volume of PBS was intranasally administered to the mice in the control group. After infection with CSE/LPS for 4 weeks, Rof and QLT dissolved in distilled water were gavaged intragastrically to mice in the Rof, QLT-L, QLT-M, and QLT-H groups once daily for 4 weeks. At this time, equal amounts of distilled water were administered orally to mice in the control and model groups. Specific pathogen-free-grade male Sprague–Dawley rats (200 ± 20 g) were purchased from the Hangzhou Medical College. The rats were allowed to acclimate for 1 week before the experiment. All rats were housed at ambient temperature (20 ± 2 °C), humidity (60 ± 5%), and light/dark cycle (12 h). Blank serum was taken as a backup before administration. The QLT aqueous solution was intragastrically administered to the rats (n = 6) at 4.1 g/kg/day for 3 consecutive days. Medicated serum was collected after the last oral administration at 1 h and then centrifuged (0.9 × g for 10 min at 4 °C) and stored at −80 °C. The animal protocols were approved and conducted by the Guide for the Care and Use of Laboratory Animal Center in Nanjing University of Chinese Medicine (approval number 202206A026). All procedures were in accordance with the Guide for the Care and Use of Laboratory Animals (National Institutes of Health). 5.5. Pulmonary Function Test The EF50, MV, and PEF were measured on the day before the end of the animal experiment using whole-body plethysmography (Buxco, America). 5.6. Sample Collection Before execution, blood was extracted from the eyeballs. Blood samples were allowed to stand for 120 min and centrifuged at 1.2 × g for 10 min to obtain the serum, which was stored at −20 °C until further analysis. After execution, lung tissues were removed and divided into three parts. One part was used for preparing the lung homogenate. The lung tissues were homogenized with precooled PBS (w/v = 1:9) and centrifuged at 2.4 × g for 10 min at 4 °C; the lung homogenate was collected and stored at −20 °C. The other part was fixed in 4% paraformaldehyde, and the remaining lung tissues were stored at −80 °C. 5.7. UPLC-Q-TOF-MS/MS Analysis First, 200 μL of serum was taken, and then 4 times the volume of acetonitrile was added and vortexed for 3 min. The solution was centrifuged at 4 °C and 18.8 × g for 10 min. The supernatant was blown into liquid nitrogen and dissolved again with 200 μL of acetonitrile. UPLC-Q-TOF-MS/MS analysis was conducted by using a Shimadzu ExionLC system and Sciex ZenoTOF 7600 mass spectrometer (AB SCIEX, USA). An ACQUITY UPLC BEH C[18] column (1.7 μm, 2.1 × 100 mm) was used; 3 μL was used as the injection volume, 40 °C was used as the chromatographic temperature, and 0.3 mL/min was used as the flow rate. The mobile phase consisted of (A) 0.1% formic acid in water and (B) methanol. The elution gradient was as follows: 0–2 min, 5% B; 2–12 min, 5∼50% B; 12–13 min, 50∼68% B; 13–18 min, 68∼95% B; 18–23 min, 95% B; 23–24 min, 95∼5% B; 24–28 min, 5% B. The mass spectrum operating parameters were set as follows: ion spray voltage, 5500 eV; source temperature, 550 °C; collision energy, 45/–45 V; declustering potential, 80/–80 V. Data acquisition was performed using an Analyst TF workstation (version 1.6, AB SCIEX). The TOF MS scan range was m/z 80–2000. 5.8. Identification of Compounds The compound database of QLT, including chemical name, molecular formula, molecular weight, and secondary fragments of the three herbal medicines, was established based on a literature search in PubMed and the Chinese National Knowledge Infrastructure. By comparing the mass spectrum data imported into Peakview 1.2 software with the compounds’ information in the compound database of QLT, the components with mass errors of <10 ppm were identified and further verified using the MOL file. 5.9. Network Pharmacological Analysis of QLT The compounds in QLT identified using UPLC-Q-TOF-MS/MS were imported into SwissTargetPrediction ([158]http://www.swisstargetprediction.ch/) databases for target prediction. Among them, the targets in SwissTargetPrediction with probabilities >0.1 were selected. The targets related to COPD were summarized using the GEO ([159]http://www.ncbi.nlm.nih.gov/geo), DisGeNET ([160]https://www.disgenet.org/), and Genecards ([161]https://www.genecards.org/) databases. The microarray data [162]GSE151052 from GEO was downloaded to analyze DEGs between lung samples of COPD patients and healthy controls, which were screened using the Bioconductor/R limma 3.4.2 software package with a p value of <0.05 and a |log[2] FC| of >1. Furthermore, the targets with a relevance score of >40 in the Genecards database and the targets with a score gda of >0.02 in the Genecards database were selected and combined with the targets gathered from GEO data sets. The components and disease overlap targets are considered candidate targets for QLT in treating COPD, as shown in the Venn diagram. A PPI network was constructed using STRING ([163]https://cn.string-db.org/) and Cytoscape 3.7.2 software with overlap targets. Next, the degree of the PPI network was analyzed to select the core targets. The compounds and overlap targets were input into Cytoscape 3.7.2 to establish a compound–targets network, and the key components were screened using network topology parameters. The overlap targets were submitted to the Metascape ([164]https://metascape.org/) database to conduct GO and KEGG pathway enrichment analysis. 5.10. Molecular Docking The 3D structure files of targets (receptors) were acquired from PDB ([165]https://www.rcsb.org/), and the SDF files of compounds (ligands) were obtained from PubChem. The organic elements and solvents of the receptors were removed by PyMOL, and the SDF files of ligands were transformed into MOL2 files by using ChemDraw 3D 20.0. The ligands and receptors were imported into AutoDockTools 1.5.7 and converted into PDBQT format files. AutoDock Vina was used for molecular docking, and PyMOL was used to visualize the docking results. 5.11. Measurement of Inflammatory Cytokines Using ELISA IL-6 and IL-1β levels in the lung homogenate and serum were measured using ELISA kits, and the manufacturer’s instructions and operation methods were strictly followed. 5.12. H&E and Masson’s Staining Lung tissues were removed from 4% paraformaldehyde after 24 h of fixing. They were dehydrated with alcohol, embedded in paraffin blocks, and cut into 5 μm thick slices. Staining was performed using H&E and Masson’s staining kits. Photographs were taken using a microscope (200×; PerkinElmer, America). The fibrotic area observed after Masson’s staining was quantified using ImageJ software. 5.13. Western Blotting RIPA lysis buffer was used to lyse the lung tissues, and a BCA protein assay kit was used to determine protein concentrations after centrifugation. SDS-PAGE and PVDF membranes were used for electro-transfer. After treatment with blocking fluid, the membranes were incubated with primary antibodies (1:1000) and secondary antibodies (1:2500). Lastly, the bands were visualized using the ECL reagent and quantified using ImageJ software. 5.14. Immunohistochemistry The lung tissues embedded in paraffin were cut, dewaxed, dehydrated, and incubated in a citrate antigen retrieval solution for antigen repair. After inhibiting endogenous peroxidase activity and blocking with serum albumin, the slices were incubated with rabbit EGFR primary antibodies and later incubated with a secondary antibody bound to HRP. The sections were stained with a DAB substrate kit, and the nuclei were counterstained with hematoxylin. Digital photos were captured using a microscope (400×; PerkinElmer, America). EGFR expression in tissues was analyzed using ImageJ software. 5.15. qRT-PCR Total RNA from lung tissues was extracted using a TRIzol reagent and reverse-transcribed into cDNA using Hifair V one-step RT-gDNA digestion SuperMix for qPCR kits. The samples were analyzed with TOROGreen qPCR Master Mix kits using LightCycler 96 (Roche, Indiana, USA). The operation methods of the kits were followed according to the manufacturer’s instructions. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was chosen as the control. The 2^–ΔΔCt method was used to determine the fold change difference between the experimental and calibration samples. The primer sequences are listed in [166]Table [167]3 . Table 3. Primer Sequences in qPCR. gene primer primer sequences (5′ → 3′) ERK forward AGTGTACAAGGGCCGATTGA ERK reverse GTACCCAGCTTTCAGGGTCT P38MAPK forward TCACTCCAGCTACGTTGTGT P38MAPK reverse GTTCAGGTGCTCTGTTCGTC JNK forward TCACCTGTGTCCCTCAGTTC JNK reverse CCTGTCCTGTCAGTGTCCTT EGFR forward AAAGGCAGCCACCAAATGAG EGFR reverse GGCTTGGCTTCTTTGGGAAA GAPDH forward ACCCCAGCAAGGACACTGAGCAAG GAPDH reverse GGCCCCTCCTGTTATTATGGGGGT [168]Open in a new tab 5.16. Statistical Analysis GraphPad Prism 9.0 was used for data analysis. Experimental data are expressed as the mean ± SEM and evaluated using ANOVA. p < 0.05 was considered statistically significant. Acknowledgments