Dendrobium nobile extract for treating COPD (chronic obstructive pulmonary disease) as well as preparation method and application of dendrobium nobile extract

Abstract

The invention provides a dendrobium nobile extract for treating COPD (chronic obstructive pulmonary disease) as well as a preparation method and application of the dendrobium nobile extract. Animal experiments are adopted to evaluate the pharmacological activity of dendrobium nobile in resisting chronic obstructive pulmonary disease (COPD), the chemical substance basis of dendrobium nobile is systematically analyzed through a high-resolution liquid chromatography-mass spectrometry technology, and the key active components of dendrobium nobile in resisting COPD are further screened in combination with spectrum-activity correlation analysis and network pharmacology technologies. Experimental results show that dendrobium nobile can improve the lung function of a COPD mouse and reduce the level of inflammatory factors, and shows a good COPD treatment effect; 93 chemical components are identified from dendrobium nobile lindl, and the comprehensive spectrum-activity correlation analysis and the network pharmacology analysis show that N-trans-feruloyltyramine, Colonin and glyphoside can be core active components of the dendrobium nobile lindl for treating COPD (chronic obstructive pulmonary disease).

Description

Technical field:

[0001] The invention belongs to the technical field of traditional Chinese medicine quality evaluation, and particularly relates to a Dendrobium nobile extract for treating COPD, a preparation method and an application thereof. Background technology:

[0002] Dendrobium nobile Lindl. (Dendrobium nobile Lindl) is the fresh or dried stem of the Orchidaceae plant. Traditional Chinese Medicine considers Dendrobium nobile Lindl to be sweet, slightly cold, with a subtle aroma and bitter taste. It enters the stomach and kidney meridians. It promotes the production of body fluids and nourishes the stomach, clearing away heat and nourishing yin. It is used to treat symptoms such as fluid loss caused by febrile illnesses, dry mouth and thirst, insufficient stomach yin, stomach pain and retching, dry cough caused by lung dryness, and blurred vision due to yin damage. Dendrobium nobile Lindl. Its chemical composition is complex, primarily consisting of alkaloids, phenanthrenes, bibenzyls, sesquiterpenes, polysaccharides, and other compounds. Currently, research has focused on alkaloids and polysaccharides. Bibenzyls have also been a hot topic in recent years due to their promising antitumor activity. Modern pharmacological studies have shown that Dendrobium nobile Lindl. It has multiple pharmacological effects, including regulating glucose and lipid metabolism, protecting the nervous system, modulating immunity, anti-tumor, anti-inflammatory, and hepatoprotective activities. It also possesses other biological activities, including anti-inflammatory, hepatoprotective, and antioxidant activities.

[0003] Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease characterized by persistent respiratory symptoms and airflow limitation. Common symptoms include chronic cough, sputum production, and dyspnea. It is more common in middle-aged and elderly individuals and has become the third leading cause of death worldwide. Currently, COPD is primarily treated with glucocorticoids, bronchodilators, and expectorants. While these medications can alleviate symptoms, long-term use can lead to adverse reactions, drug resistance, and liver damage. Recent studies have revealed that traditional Chinese medicine (TCM) offers unique advantages in the treatment of COPD. Through multi-target and multi-pathway regulatory mechanisms, it inhibits airway inflammation, improves lung function, and slows airway remodeling, providing new clinical therapeutic strategies. While research on Dendrobium nobile has made some progress, further research is needed. The main pharmacological studies focus on its chemical constituents, alkaloids and polysaccharides, which have immunomodulatory, anti-tumor, and neuroprotective properties. Summary of the invention:

[0004] The present invention provides a Dendrobium nobile extract for treating COPD, as well as a preparation method and application thereof. The present invention uses animal experiments to evaluate the pharmacological activity of the Dendrobium nobile extract against chronic obstructive pulmonary disease (COPD), and systematically analyzes the chemical substance basis of the Dendrobium nobile through high-resolution liquid chromatography-mass spectrometry technology. Spectrum-effect correlation analysis and network pharmacology technology are further combined to screen key active ingredients of the Dendrobium nobile for treating COPD, thereby solving the problem of the lack of modern scientific evidence for the use of Dendrobium nobile in treating lung diseases in the prior art and providing a basis for the research and development of Dendrobium nobile and the development of new drugs for COPD.

[0005] The present invention is achieved through the following technical solutions:

[0006] The first object of the present invention is to provide a Dendrobium nobile extract for treating COPD, which is obtained by extracting Dendrobium nobile with water, alcohol or alcohol-water solution and concentrating the extract.

[0007] Preferably, the alcohol can be a polar solvent such as methanol, ethanol, propanol, etc., preferably methanol.

[0008] The second object of the present invention is to provide the use of the Dendrobium nobile extract in the preparation of a drug for treating COPD.

[0009] Preferably, the drug comprises pharmaceutically acceptable excipients.

[0010] Preferably, the drug can be prepared into various pharmaceutically acceptable dosage forms, such as liquid dosage forms or solid dosage forms. The liquid dosage forms are injections, solutions, suspensions, or emulsions. The solid dosage forms are tablets, capsules, pills, powder injections, or sustained-release preparations.

[0011] A third object of the present invention is to provide a method for screening anti-COPD active ingredients in Dendrobium nobile, comprising the following steps:

[0012] 1) Pharmacological activity evaluation: The pharmacological activity of Dendrobium nobile in treating COPD was evaluated using animal models;

[0013] 2) Chemical component identification: The chemical components of Dendrobium nobile were systematically identified using high-resolution liquid chromatography-mass spectrometry (HPLC-MS / MS).

[0014] 3) Spectrum-effect correlation analysis: Different polarity extracts from Dendrobium nobile were combined to prepare differentiated samples. HPLC fingerprint analysis and efficacy evaluation were performed to obtain quantitative chemical and efficacy characteristics. Grey correlation analysis, partial least squares regression analysis, and Spearman correlation analysis were used to screen for active ingredients closely associated with efficacy.

[0015] 4) Network pharmacology analysis: The Swiss Target Prediction Database and the CTD disease database were used to predict potential targets of chemical components of Dendrobium nobile for the treatment of COPD. Key active ingredients and targets were screened by constructing a component-target network, and molecular docking validation and drugability assessment were performed.

[0016] 5) Integrate the results of the spectrum-effect association analysis in step 3) and the network pharmacology analysis in step 4) to determine the key active ingredients of Dendrobium nobile in the treatment of COPD.

[0017] Preferably, in step 1), the evaluation indicators of the pharmacological activity include changes in body weight; changes in lung function parameters; changes in serum TNF-α, IL-1β, and IL-6 levels; and changes in SOD activity and MDA content in lung tissue.

[0018] Preferably, in the high-resolution liquid chromatography-mass spectrometry technique described in step 2), the chromatographic conditions are: using an Agilent EclipsePlus C18 (2.1mm×50mm, 1.8μm) chromatographic column; the mobile phase is 0.1% formic acid aqueous solution (A)-acetonitrile (B), gradient elution: 0-2min, 95%A→70%A, 2-8min, 70%A, 8-20min, 70%A→40%A, 20-25min, 40%A→0%A, 25-30min, 0%A; flow rate 0.2mL / min; column temperature 30°C; injection volume 1μL; mass spectrometry conditions are: using an electrospray ionization source (ESI), ion detection mode is full scan mode and dynamic data-dependent scanning, positive and negative modes are collected respectively; ion source temperature is 350°C; collision energy (CE) is 40V; mass scan range is m / z 100-1500.

[0019] Preferably, in the high-resolution liquid chromatography-mass spectrometry technology of step 2), a mixed reference solution is prepared using schaftoside, dendrobine, dendrobium phenol, N-trans-feruloyltyramine, vitexin, phloroglucin, and coelonin reference substances as raw materials.

[0020] Preferably, in step 3), the preparation step of the difference sample is: using the uniform design method, the ethyl acetate, n-butanol and water extraction parts of Dendrobium nobile are combined with three factors (A, B, C) and nine levels (0, 25%, 50%, 75%, 100%, 125%, 150%, 175%, 200%) to prepare 9 difference samples.

[0021] Preferably, in the HPLC fingerprint analysis in step 3), the chromatographic conditions are: using an InertSustain C18 (4.6 mm × 250 mm, 5 μm) chromatographic column, the mobile phase is water (A)-acetonitrile (B); elution gradient: 0-20 min, 0.5% B→24% B; 20-40 min, 24% B→24% B; 40-65 min, 24% B→100% B; 65-70 min, 100% B; the flow rate is 1 ml / min, the detection wavelength is 270 nm, and the injection volume is 20 μl.

[0022] Preferably, the efficacy evaluation in step 3) is performed by using a lipopolysaccharide (LPS)-induced RAW264.7 cell inflammation model to evaluate the anti-inflammatory activity of each differential sample.

[0023] Preferably, in step 3), the grey correlation analysis uses the efficacy index as the reference series, the peak area of ​​the common peak of the difference samples as the comparison series, the resolution coefficient is 0.5, and the correlation factors with a correlation degree ≥0.7 and the top 5 are retained; in the partial least squares regression analysis, the standardization method selects Autoscale, the model is cross-validated using the Venetian blinds method, and the variables are screened using the VIP value >1.0 as an indicator; in the Spearman correlation analysis, the peak area of ​​each common peak is subjected to bivariate correlation analysis with the efficacy index, and the Spearman correlation coefficient is calculated. The screening criteria are a correlation coefficient ≥0.3 and statistically significant (p <0.05).

[0024] Preferably, the active ingredients screened in step 3) are N-trans-feruloyltyramine, Coelonin, phloroglucosidol, and dendrobium phenol.

[0025] Preferably, in step 4), the specific steps of constructing a component-target network to screen key active ingredients and targets are: importing the chemical structures of the chemical components of Dendrobium nobile obtained by liquid chromatography-mass spectrometry analysis into the Swiss Target Prediction database, and screening the potential target proteins of each component based on the top 15 results with a Probably value > 0; importing the obtained targets into the CTD database, and screening the potential anti-COPD targets of each component based on the highest inference score ≥ 85; then, performing visualization processing to construct a component-target network, and analyzing the degree value of each data point to obtain the key active ingredients and targets of Dendrobium nobile for anti-COPD. Furthermore, the degree value is greater than or equal to 10.

[0026] Preferably, in step 4), the specific steps of the molecular docking verification are: saving the compound structure of the key active ingredient as an sdf format file, and obtaining the protein structure of each target from the PDB protein library, using the software in a flexible docking mode to perform molecular docking analysis on the key active ingredient and the target, with a docking score >5.0 as the evaluation standard.

[0027] Preferably, in step 4), the drugability is assessed by analyzing QED (drug-like properties) and bioavailability values. Further, the bioavailability is F20%, F30%, and QED>0.67.

[0028] Preferably, the active ingredients screened in step 4) are Coelonin, Ephemeranthol C, Ephedrine, Phrynoside, N-trans-feruloyltyramine, 10,12-Dihydroxypicrotoxane, Nobilenin H, and 3-hydroxy-5-methoxybibenzyl.

[0029] Preferably, in step 5), the key active ingredients of the Dendrobium nobile for anti-COPD are N-trans-feruloyltyramine, Coelonin, and phloroglucosidase.

[0030] Dendrobium nobile can improve lung function in COPD mice, reduce levels of the inflammatory factors IL-6, IL-1β, and TNF-α, enhance lung superoxide dismutase activity, and reduce MDA levels, demonstrating promising therapeutic effects. Ninety-three chemical components were identified from the herb. Spectrum-effect association analysis identified the key active ingredients as N-trans-feruloyltyramine, coelonin, phleuroside, and dendrobiumol. Network pharmacology analysis identified the key active ingredients as coelonin, ephemeranthol C, phleuroside, phleuroside, N-trans-feruloyltyramine, 10,12-dihydroxypicrotoxane, dendrobium nobile H, and 3-hydroxy-5-methoxybibenzyl. Comprehensive analysis suggests that N-trans-feruloyltyramine, coelonin, and phloroglucin may be the core active ingredients in the treatment of COPD in Dendrobium nobile. Dendrobium phenol, ephemeranthol C, malanphen, 10,12-dihydroxypicrotoxane, dendrobium nobile H, and 3-hydroxy-5-methoxybibenzyl may also play important roles. These findings provide a valuable reference for the development and utilization of Dendrobium nobile. Description of the drawings:

[0031] Figure 1 The figure shows the changes in body weight of mice in each group in Example 1.

[0032] Figure 2These are the lung function test results for each group of mice in Example 1; A: FRC; B: RI; C: Cchord; D: FEV0.1 / FVC. (##: compared with the blank group, p < 0.01; compared with the model group, *p < 0.05, **p < 0.01)

[0033] Figure 3 The results of the changes in the levels of proinflammatory cytokines in the serum of each group of mice in Example 1 are as follows: A: TNF-α; B: IL-6; C: IL-1β. (##: compared with the blank group, p < 0.01; **: compared with the model group, p < 0.01)

[0034] Figure 4 The following are the changes in the relevant markers in the lung tissues of the mice in each group in Example 1; A: SOD activity; B: MDA level. (##: compared with the blank group, p < 0.01; **: compared with the model group, p < 0.01)

[0035] Figure 5 1 is the total ion current diagram of Dendrobium nobile in Example 1; wherein, A: positive mode of Dendrobium nobile; B: negative mode of Dendrobium nobile.

[0036] Figure 6 This is a representative HPLC chromatogram (S5) of the differential samples of Dendrobium nobile in Example 1; wherein, 3: New Zealand vitexin, 4: schaftoside, 6: phloroglucin, 8: N-trans-feruloyltyramine, 10: Coelonin, 12: dendrobium phenol, 14: dendrobine.

[0037] Figure 7 This is the dendrogram of cluster analysis of the difference samples of Dendrobium nobile in Example 1.

[0038] Figure 8 This is the effect of the different samples of Dendrobium nobile on the NO level in Example 1; compared with the blank group: ##p<0.01; compared with the model group: *p<0.05, **p<0.01.

[0039] Figure 9 It is the VIP value of the common peak of Dendrobium nobile on the anti-inflammatory efficacy in Example 1.

[0040] Figure 10 is the Spearman correlation coefficient of the common peak of Dendrobium nobile on the anti-inflammatory efficacy in Example 1.

[0041] Figure 11 This is the Dendrobium nobile component-COPD target network diagram in Example 1; wherein A-alkaloids, B-phenanthrene, C-bibenzyl, D-sesquiterpenes, and E-others.

[0042] Figure 12It is the key active ingredient of Dendrobium nobile for treating COPD screened by component-target network analysis in Example 1; wherein A: Coelonin, B: Ephemeranthol C, C: Maolanfei, D: Phlecoside, E: N-trans-feruloyltyramine, F: 10,12-Dihydroxypicrotoxane, G: Dendrobium nobile H, H: 3-hydroxy-5-methoxybibenzyl. Specific implementation method:

[0043] The following examples are provided to further illustrate the present invention, but are not intended to limit the present invention.

[0044] Example 1

[0045] 1. Materials and Methods

[0046] 1.1 Experimental Materials and Instruments

[0047] 1.1.1 Instruments

[0048] Electronic analytical balance (Sartorius, Germany), pulmonary function measurement system (Buxco-PFT, DSI, USA), small desktop high-speed centrifuge (Eppendorf, Germany), Mithras2LB943 full-function microplate analyzer (Berthold, Germany); UltiMate 3000UHPLC ultra-high performance liquid phase system, Q-Exactive-Orbitrap high-resolution mass spectrometer (Thermo Scientific, USA); LC-20A high-performance liquid chromatograph (Shimadzu, Japan); ultrapure water machine (Millipore Simplicity); biological safety cabinet (Suzhou Purification Antai Technology Co., Ltd., model BSC-1304IIA2); biological microscope (SDPTOP ICX41); CO2 incubator (Thermo Scientific, model 3111); ultra-low temperature refrigerator (ThermoScientific, model 907).

[0049] 1.1.2 Drug testing

[0050] Dendrobium nobile Lindl was purchased from Chishui Xintian Human Pharmaceutical Co., Ltd. and identified as the dried stem of Dendrobium nobile Lindl (Orchidaceae) by Associate Professor Wang Sheng of Guangzhou Medical University. Dexamethasone was purchased from Sigma-Aldrich. Soft-packed Coconut Tree brand cigarettes (11 mg tar, 1.0 mg nicotine in smoke, and 13 mg carbon monoxide in smoke, supplied by Guangdong China Tobacco Industry Co., Ltd.) were also purchased. TNF-α, IL-1β, and IL-6 ELISA kits were purchased from Novus Pharmaceuticals, Inc., USA. =Biologicals Company); malondialdehyde (MDA) and total SOD activity detection kit (Shanghai Beyotime Biotechnology Co., Ltd.); methanol and acetonitrile (chromatographic grade, ThermoScientific, USA); schaftoside reference substance (Beijing Myrida Technology Co., Ltd.); dendrobine and dendrobium phenol reference substances (China Food and Drug Inspection Institute); N-trans-feruloyltyramide, vitexin, and phloroglucin reference substances (Shanghai Yuanye Biotechnology Co., Ltd.); coelonin (Shanghai MacLean Biochemical Technology Co., Ltd.); lipopolysaccharide (0111:B4, Sigma-Aldrich); CCK-8 reagent (Sigma-Aldrich); nitric oxide detection kit (Beyotime, batch number: Z938240812); DMEM complete medium (Servicebio); PBS buffer (Servicebio); fetal bovine serum (ExCell); DMSO (MPBiomedicals).

[0051] 1.1.3 Animals

[0052] Sixty SPF male Balb / c mice (weighing 17-19 g) were purchased from the Guangdong Provincial Laboratory Animal Center. All procedures adhered to the hygiene regulations established by the Ethics Committee of Guangzhou Medical University. They were housed in a clean environment with a constant temperature (25°C) and humidity (50%), maintaining a 12-h day / night cycle. After purchase, the animals were allowed to acclimate to their new environment for one week before beginning experiments. Appropriate measures were taken to minimize harm to the animals during the experiments.

[0053] 1.2 Methods

[0054] 1.2.1 Evaluation of the pharmacological activity of Dendrobium nobile in the treatment of COPD

[0055] (1) Preparation of Dendrobium nobile extract

[0056] After crushing the Dendrobium nobile, weigh an appropriate amount and soak it in 8 times its weight of methanol for three 7-day soaking cycles. Filter the mixture, combine the filtrates, and concentrate them under reduced pressure with rotary evaporation to a crude drug concentration of approximately 1 g / mL. This is the Dendrobium nobile extract and store it at -20°C until needed.

[0057] (2) Animal grouping, modeling, and drug administration

[0058] The mice were randomly divided into 6 groups, with 10 mice in each group, namely: blank group, model group, positive drug group (dexamethasone 2 mg·kg -1 ·d -1 ), low-dose group of Dendrobium nobile (raw drug dosage 0.5 g·kg -1 ·d -1 ), medium-dose group of Dendrobium nobile (raw drug dosage 2.0 g·kg -1 ·d -1 ), high-dose group of Dendrobium nobile (crude drug dosage 8.0 g·kg -1 ·d -1 ).

[0059] Except for the blank group, mice in each group were smoked twice a day, with an interval of 4 hours between each treatment, and 8 cigarettes were used for 1 hour each time. The animals were placed in a smoke box and exposed to the smoke environment. They were free to move during the treatment and were treated 6 days a week for 12 weeks. From week 9 to week 12, the mice were gavaged 1 hour before the first smoke fumigation every day, with a gavage volume of 0.1 mL per 10 g body weight. The blank group and the model group were given an equal amount of normal saline. At 8 pm every Saturday, the mice were fasted but not watered for about 12 hours. The body weight of the mice in each group was weighed the next morning and recorded once a week.

[0060] (3) Pulmonary function test

[0061] After modeling and drug administration, mice were anesthetized with an intraperitoneal injection of 1% sodium pentobarbital solution (50 mg / kg). The mice were fixed in a supine position, and the neck skin was cut open to expose the trachea. A small transverse incision was made with a tracheal ring scissor, and the trachea was inserted into the trachea and secured with surgical suture. The mice were placed in a mouse cage and pulmonary function parameters, including functional residual capacity (FRC), airway resistance (RI), static compliance (Cchord), and forced expiratory volume (FEV0.1 / FVC), were measured using a pulmonary function measurement system.

[0062] (4) Collection of serum and lung tissue samples

[0063] Whole blood was collected from the eyeball into EP tubes and centrifuged at 4000 rpm for 15 minutes at 4°C. The upper serum layer was separated and stored at -20°C until further use. After eyeball bleeding, mice were sacrificed by cervical dislocation, and lung tissue was collected and stored at -20°C until further use.

[0064] (5) Detection of IL-6, IL-1β, and TNF-α in serum

[0065] The ELISA method was used to determine the levels of IL-6, IL-1β and TNF-α in mouse serum according to the kit instructions.

[0066] (6) Detection of SOD and MDA in lung tissue

[0067] The expression levels of the two in mouse lungs were determined according to the instructions of the detection kit.

[0068] (7) Data processing

[0069] The experimental data were sorted and statistically analyzed using SPSS 19.0 software. Inter-group comparisons were performed using one-way analysis of variance and independent sample T-test. The results were expressed as mean ± standard deviation (Mean ± SD), and the significance level was set at p < 0.05.

[0070] 1.2.2 Basic research on chemical substances of Dendrobium nobile based on LC-MS

[0071] (1) Preparation of solution

[0072] Accurately weigh schaftoside, dendrobine, dendrobium phenol, N-trans-feruloyltyramine, vitexin, phloroglucin, and coelonin reference substances and place them in 10 mL volumetric flasks respectively. Add methanol to the mark and mix well to prepare a 100 μg / mL reference substance stock solution. Take 500 μL of each, mix well, and pass through a 0.22 μm filter membrane as the mixed reference substance solution.

[0073] Take 0.1 g of Dendrobium nobile extract, accurately add 1 ml of methanol, vortex mix, and pass through a 0.22 μm filter membrane to use as the test solution.

[0074] (2) Chromatographic mass spectrometry conditions

[0075] An Agilent Eclipse Plus C18 column (2.1 mm × 50 mm, 1.8 μm) was used; the mobile phase consisted of 0.1% formic acid in water (A)-acetonitrile (B) in a gradient elution scheme (see Table 1). The flow rate was 0.2 mL / min, the column temperature was 30°C, and the injection volume was 1 μL.

[0076] Table 1 Mobile phase gradient elution program

[0077]

[0078] The mass spectrometer used an electrospray ionization (ESI) source, and the ion detection modes were full scan mode and dynamic data-dependent scan, with acquisition in positive and negative modes respectively; the ion source temperature was 350°C; the collision energy (CE) was 40 V; and the mass scan range was m / z 100-1500.

[0079] (3) Data processing method

[0080] The ion peaks and secondary fragments of the total ion chromatogram (TIC) of each sample were extracted using Xcalibur software. According to the primary accurate molecular weight and secondary fragment cracking rule, combined with reference substances, databases and literature, each chromatographic peak was qualitatively analyzed.

[0081] 1.2.3 Study on Anti-inflammatory Active Components of Dendrobium candidum Based on Spectrum-effect Association Analysis

[0082] (1) Preparation of difference samples

[0083] The Dendrobium candidum extract prepared in "1.2.1" was suspended in an appropriate amount of water, and then extracted with ethyl acetate and n-butanol, respectively, to separate into ethyl acetate, n-butanol and water extraction parts. Each part of the extraction was concentrated under reduced pressure to recover the solvent to obtain the corresponding extract. Using uniform design method, the three parts of samples were combined with three factors (A, B, C) and nine levels (0, 25%, 50%, 75%, 100%, 125%, 150%, 175%, 200%) to prepare 9 difference samples S1-S9. The sample ratio is shown in Table 2, wherein S5 is equivalent to the Dendrobium candidum extract.

[0084] Table 2 Preparation of Dendrobium candidum difference samples

[0085]

[0086]

[0087] (2) HPLC fingerprint detection and analysis of difference samples

[0088] 0.1 g of each difference sample was precisely added with 1 ml of methanol, vortexed, and filtered through a 0.22 μm filter to obtain the test solution. An InertSustain C18 (4.6 mm x 250 mm, 5 μm) column was used with a mobile phase of water (A) - acetonitrile (B). The elution gradient was 0-20 min, 0.5% B→24% B; 20-40 min, 24% B→24% B; 40-65 min, 24% B→100% B; 65-70 min, 100% B. The flow rate was 1 ml / min, the detection wavelength was 270 nm, and the injection volume was 20 μl.

[0089] The chromatographic peaks with good separation and high content were selected as common characteristic peaks. The common peak areas of the 9 difference samples were introduced into SPSS 27.0 software for system clustering, using Ward method with square Euclidean distance as the measure, and Z-Score standardization was performed according to the variable.

[0090] (3) Anti-inflammatory activity determination of difference samples

[0091] The anti-inflammatory activity of each different sample was evaluated using the lipopolysaccharide (LPS)-induced RAW264.7 cell inflammation model.

[0092] LPS solution: Accurately weigh an appropriate amount of lipopolysaccharide (LPS) and prepare a 1 mg / mL stock solution with PBS buffer. Sterilize the solution by filtering through a 0.22 μm sterile microporous filter and aliquot. Dilute with DMEM complete medium before use.

[0093] Sample Preparation: Each differential sample was prepared in DMEM complete medium (containing 0.1% DMSO) to a final concentration of 320 μg / mL of the crude drug (this concentration did not affect normal cell growth as determined by the CCK-8 assay). Dexamethasone (DEX) was prepared in DMEM complete medium (containing 0.1% DMSO) to a final concentration of 10 μg / mL as a positive control.

[0094] Cell culture: Mouse RAW 264.7 mononuclear macrophage cell line was purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences and cultured in DMEM complete medium (containing 10% fetal bovine serum) in a 37°C, 5% CO2 incubator. Logarithmic phase cells were used for subsequent experiments.

[0095] Cell treatment and NO detection: The experiment set up blank control group, model group (LPS), positive control group (dexamethasone DEX + LPS) and experimental group (Dendrobium nobile different samples + LPS), with 3 replicates in each group, and the final concentration of LPS in each well was 1 μg / mL. Cells growing in the logarithmic phase were taken and 5×10 4 Cells were seeded in 96-well cell culture plates. After 24 hours of cell attachment, the culture medium was discarded from each well and DEX and the sample solution were added. The blank control group and the model group were given equal amounts of DMEM medium containing 0.1% DMSO. After incubation for 2 hours in a 5% CO2, 37°C incubator, LPS solution was added to each well except for the blank control group, which was given an equal amount of culture medium and incubated for another 24 hours. Finally, the cell supernatant was collected and the inflammatory factor NO content was measured using a nitric oxide (NO) detection kit.

[0096] Data analysis: SPSS 27.0 software was used. The results were expressed as mean ± standard deviation. The differences between the groups were analyzed using T test. A P value less than 0.05 indicated that the difference was statistically significant.

[0097] (4) Spectrum-effect correlation analysis

[0098] Grey correlation analysis: To eliminate the influence of different units between the dependent variable and each variable, the original data was dimensionlessly processed using the mean method; the reference sequence (parent sequence) and the comparison sequence (subsequence) were determined; the anti-inflammatory efficacy index was used as the parent sequence, and the peak area shared by each sample was used as the subsequence. The transformed parent sequence was recorded as y(k) (k is the 9 differential samples), and the subsequence was recorded as Xi(k) (i is the peak number); the correlation coefficient (ρ is the resolution coefficient, set to 0.5) and the correlation degree were calculated, and the correlation factors with a correlation degree ≥ 0.7 and ranked in the top 5 were retained. The calculation formula is as follows:

[0099]

[0100] Partial least squares regression (PLSR) analysis was performed using the peak area of ​​the common peak as the independent variable (X) and the anti-inflammatory efficacy index as the dependent variable (Y). Data were imported into MATLAB (R2024b) software and PLSR analysis was performed using the PLS Toolbox. Autoscale was selected as the normalization method, and the model was cross-validated using the Venetian blinds method. Variable importance projection (VIP) analysis was performed. The VIP value reflects the explanatory power of the independent variable on the dependent variable; larger values ​​indicate stronger explanatory power and greater contribution of the variable. In this study, variables were screened using a VIP value greater than 1.0.

[0101] Spearman correlation analysis: The peak area of ​​each common peak was correlated with the anti-inflammatory efficacy index. The Spearman correlation coefficient was calculated using bivariate correlation analysis in SPSS 27.0 software. The screening criteria were a correlation coefficient ≥ 0.3 and statistical significance (p < 0.05).

[0102] 1.2.4 Study on the anti-COPD active ingredients of Dendrobium nobile based on network pharmacology

[0103] (1) Screening and analysis of potential targets of Dendrobium nobile in the treatment of COPD

[0104] The chemical components of Dendrobium nobile obtained by liquid chromatography-mass spectrometry were mapped using ChemDraw software. The chemical structures of each component were then imported into the Swiss Target Prediction Database for target prediction analysis. The top 15 targets with a Probability value > 0 were used as the screening criteria to identify potential target proteins for each component. The resulting targets were then imported into the CTD database. Based on data such as target-related disease classifications, COPD-related targets were screened with a maximum inference score ≥ 85, ultimately identifying potential anti-COPD targets for each compound.

[0105] The Excel spreadsheet with the "component-target" mapping was imported into Cytoscape 3.9.1 software for visualization, constructing a component-target network. The degree of each data point was analyzed using the Network Analysis plug-in within the software to identify the key active ingredients and key targets of Dendrobium nobile in its anti-COPD activities.

[0106] (2) Molecular docking verification

[0107] Based on the key active ingredients and key targets identified through component-target network analysis, the compound structures were saved as SDF files, and the protein structures of each target were obtained from the PDB protein library. Molecular docking analysis was performed between each key active ingredient and key target using Sybyl-X 2.0 software in flexible docking mode. The docking results were evaluated using a scoring function (Total Score), with higher scores indicating better docking performance. A docking score >5.0 was considered the criterion for successful docking.

[0108] (3) Drugability assessment

[0109] The structures of the key active ingredients were converted into SMILES numbers and then imported into the ADMET lab2.0 database to analyze the QED (drug-like properties) and bioavailability (F20%, F30%) values ​​of each ingredient to examine its drugability.

[0110] 2. Experimental Results

[0111] 2.1 Evaluation of the pharmacological activity of Dendrobium nobile in the treatment of COPD

[0112] 2.1.1 Changes in mouse weight

[0113] The weight changes of mice in each group during the experiment were as follows Figure 1 As shown. The blank group of mice gradually gained weight; the other groups of mice exposed to cigarette smoke experienced slower weight gain from 1 to 8 weeks, with significant differences compared to the blank group (p < 0.01). Starting from the 9th week, all treatment groups were administered medication, and the weight of mice in all groups, except the model group, began to gradually increase. This suggests that smoke can cause damage to the mice, and that the positive drug dexamethasone and high, medium, and low doses of Dendrobium nobile all have a certain protective effect against smoke-induced damage.

[0114] 2.1.2 Effects of Dendrobium nobile on lung function in COPD mice

[0115] The results showed that ( Figure 2), compared with the model group, the FRC, RI, Cchord in the lung function indicators of the mice in the positive drug group were significantly reduced (p<0.01), and the FEV0.1 / FVC was increased (p<0.05). The FRC, RI, Cchord values of the mice in the high and medium dose groups of D. candidum were reduced to varying degrees, and the FEV0.1 / FVC was increased to varying degrees; among them, the changes of the indicators in the high dose group were statistically significant (p<0.05, p<0.01). The four lung function indicators of the mice in the low dose group had no obvious change (p>0.05). The above results show that high and medium doses of D. candidum have an improving effect on the lung function damage of mice caused by cigarette smoke.

[0116] 2.1.3 Changes in the contents of TNF-α, IL-1β and IL-6 in the serum of mice

[0117] The results show that Figure 3 ), compared with the model group, the levels of TNF-α, IL-6 and IL-1β in the serum of mice in the model group were significantly increased (p<0.01). Compared with the model group, the levels of TNF-α, IL-6 and IL-1β in the serum of mice in the positive drug group, the medium and high dose groups of D. candidum were significantly reduced (p<0.01); the levels of the three inflammatory factors in the serum of mice in the low dose group of D. candidum had no obvious change (p>0.05). The above results show that high and medium doses of D. candidum have an inhibitory effect on the increase of inflammatory level in mice caused by cigarette smoke.

[0118] 2.1.4 SOD activity and MDA level in the lung tissue of mice

[0119] Cigarette smoke can cause imbalance of oxidation-antioxidation ability and weaken the antioxidant stress ability in mice. SOD and MDA were selected as indicators to evaluate the antioxidant stress ability. The results show that Figure 4 ), compared with the model group, the SOD activity in the lung tissue of mice in the model group was significantly reduced (p<0.01), and the MDA content was significantly increased (p<0.01). Compared with the model group, the SOD activity in the lung tissue of mice in the positive drug group, the medium and high dose groups of D. candidum was significantly increased (p<0.01), and the MDA level was significantly reduced; the SOD and MDA in the lung tissue of mice in the low dose group had no obvious change (p>0.05). The above results show that high and medium doses of D. candidum can enhance the antioxidant activity in COPD mice and reduce the oxidative damage of lung tissue.

[0120] 2.1.5 Summary

[0121] This study used a cigarette smoke-induced COPD mouse model to evaluate the pharmacological effects of Dendrobium nobile. The results showed that the COPD mouse model was successfully established in this experiment; a medium dose of Dendrobium nobile (raw drug amount 2.0g·kg -1 ·d -1 ), high dose (crude drug amount 8.0g·kg -1 ·d -1 ) can significantly increase the body weight of COPD mice, improve the lung function of mice, reduce the levels of inflammatory factors IL-6, IL-1β and TNF-α, enhance SOD activity, and reduce MDA levels, showing a good anti-COPD effect overall.

[0122] 2.2 Basic research on chemical substances of Dendrobium nobile based on LC-MS

[0123] The total ion current of Dendrobium nobile is as follows Figure 5 Based on the precise molecular weight information obtained for each chromatographic peak from the total ion current chromatographic peaks, Xcalibur software was used to acquire all high-resolution primary and secondary mass spectrometric data. Peaks with intensities exceeding 10,000 were selected for identification, with mass tolerances within 5 ppm for both MS and MS2. A total of 93 chemical components were identified from Dendrobium nobile, primarily alkaloids, phenanthrenes, bibenzyls, and sesquiterpenes. Detailed results are shown in Table 3.

[0124] Table 3 Chemical constituents of Dendrobium nobile

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136] 2.3 Anti-inflammatory active components of D. nobile based on correlation analysis of spectrum-effect

[0137] 2.3.1 Identification and analysis of common peaks in differential samples

[0138] The differential samples S1-S9 of D. nobile were detected by HPLC, and the representative HPLC chromatogram (S5) is shown in Fig. 2.14 chromatographic peaks with good separation and high content were selected as common characteristic peaks (P1-14). Figure 6 The similarity and difference of common peaks in samples were analyzed and compared from the overall perspective by cluster analysis, and the cluster analysis dendrogram is shown in Fig. 3. Figure 7 The results showed that the common peak patterns of different samples had certain differences, which were suitable for carrying out subsequent spectrum-effect correlation analysis.

[0139] 2.3.2 Anti-inflammatory activity determination of differential samples

[0140] COPD belongs to chronic inflammatory diseases of the lung, so the inflammatory cell model was prepared by stimulating RAW264.7 cells with LPS, and the anti-inflammatory activity of differential samples S1-S9 of D. nobile was investigated by taking the secretion amount of nitric oxide (NO) as an index. The results are shown in Table 4, Figure 8 Compared with the normal group, the secretion amount of NO in the model group increased (p<0.01); compared with the model group, most samples could reduce the secretion amount of NO in RAW264.7 inflammatory cells to different extents. The inhibition of NO by different samples had certain differences, among which S3 and S8 had relatively good activity, and S1 and S4 had relatively poor activity.

[0141] Table 4 Effect of differential samples of D. nobile on the level of NO (x±s, n=3)

[0142]

[0143] Note: Compared with the blank group: ## p<0.01; compared with the model group: * p<0.05, ** p<0.01

[0144] 2.3.3 Spectrum-effect correlation analysis

[0145] (1) Grey correlation degree analysis

[0146] ​Gray correlation can characterize the degree of association between factors. By calculating the correlation, the factors are then sorted and analyzed based on their magnitude. A higher correlation value indicates a closer relationship, meaning a greater contribution to drug efficacy. Using the anti-inflammatory efficacy indicator (NO secretion by RAW264.7 inflammatory cells after treatment with each sample) as the reference series and the peak area of ​​the common peaks across the samples as the comparison series, the correlation between the chemical components represented by each common peak and the efficacy indicator was calculated. The results are shown in Table 5. The common peaks with a strong correlation with NO secretion in RAW264.7 cells were P13 > P7 > P8 > P10 > P6. The correlations for the more polar components P1, P2, P3, and P4 were all lower.

[0147] Table 5 Grey correlation between common peaks of Dendrobium nobile and anti-inflammatory efficacy

[0148]

[0149] (2) Partial least squares regression analysis (PLSR)

[0150] PLSR analysis is a data processing method with good model fitting and strong predictive ability. It integrates the advantages of cluster analysis, PCA, and multivariate linear regression. It has the characteristics of no need to exclude samples, high prediction accuracy, small amount of calculation, and easy qualitative interpretation. It has been widely used in the study of the spectrum efficacy of traditional Chinese medicine. The peak area of ​​the common peak is used as the independent variable (X) and the anti-inflammatory efficacy index is used as the dependent variable (Y). The PLSR model is established and the established model is subjected to 200 permutation tests. The test results show that the significance of the model is <0.05, indicating that the analysis results are relatively reliable. The VIP value of each common peak is calculated and shown in the following table. Figure 9 As shown in Table 6, the larger the VIP value (VIP>1), the greater the contribution of the common peak to the drug efficacy. There are seven common peaks with large contributions (VIP>1), namely P6>P5>P8>P10>P7>P12>P11.

[0151] Table 6 Common peaks of Dendrobium nobile and VIP values ​​of anti-inflammatory efficacy

[0152]

[0153]

[0154] (3) Spearman correlation analysis

[0155] Correlation analysis can be used to analyze two or more correlated variables. SPSS was used to perform a normality test on the common peak area data. Most of the peak area test results were significant less than 0.05, indicating that the data did not obey the normal distribution. Therefore, a non-parametric test was used to perform Spearman correlation analysis. The results are shown in Figure 10, Table 7. There are 4 common peaks significantly correlated with drug efficacy, namely P12>P10>P7>P11.

[0156] Table 7 Spearman correlation coefficients between common peaks of Dendrobium nobile and anti-inflammatory efficacy

[0157]

[0158] Note: ** p<0.001, * p<0.01

[0159] 2.3.4 Summary

[0160] A comprehensive analysis was conducted by combining grey correlation analysis, partial least squares regression analysis, and Spearman correlation analysis (Table 8). The components in D. nobile that were closely associated with anti-inflammatory activity included P7, P8 (N-trans-feruloyltyramide), P10 (Coelonin), P6 (Fleuroside), P12 (Dendrobium phenol), and P11.

[0161] Table 8 Summary of spectral-effect correlation analysis results

[0162]

[0163] 2.4 Study on the anti-COPD active ingredients of Dendrobium nobile based on network pharmacology

[0164] 2.4.1 Screening of potential targets

[0165] The 93 compounds analyzed in step 2.2 were imported into the Swiss Target Prediction database for target search, yielding target information for each compound. A total of 502 targets were obtained. These targets were then imported into the CTD database to screen for COPD-related targets. Target proteins with a maximum inference score of less than 85 were removed, ultimately resulting in 240 target proteins with a high association with COPD.

[0166] 2.4.2 Component-target network analysis

[0167] Each compound and its corresponding target protein were imported into cytoscape software to construct the "ingredient-COPD target" network diagram of Dendrobium nobile ( Figure 11) and analyzed the degree of each node. The larger the degree of the component and target, the greater the importance of the node. Sorted from high to low by degree, the top compounds (degree ≥ 10) are Coelonin (C2001, Degree = 12), Ephemeranthol C (C2002, Degree = 12), N-trans-feruloyltyramine (C1022, Degree = 12), phleboside (C5203, Degree = 12), 3-hydroxy-5-methoxybibenzyl (C3001, Degree = 11), 10,12-dihydroxypicrotoxane (C4018, Degree = 11), nobile dendrobium H (C4027, Degree = 10), and phytolamine (C2018, Degree = 10). They are mainly phenanthrenes, bibenzyls, and alkaloids, suggesting that these eight compounds may be the main active ingredients of Dendrobium nobile for the treatment of COPD ( Figure 12 The targets with the highest degree ranking (degree ≥ 10) included MMP9 (Degree = 17), MMP1 (Degree = 17), MMP2 (Degree = 13), EGFR (Degree = 13), ALOX5 (Degree = 13), ESR1 (Degree = 10), CA1 (Degree = 10), AR (Degree = 10), and SHBG (Degree = 10), suggesting that these targets may be the main action sites of the active ingredients of Dendrobium nobile.

[0168] 2.4.3 Molecular docking verification

[0169] Molecular docking was used to validate the binding abilities of eight key active ingredients (coelonin, ephemeranthol C, N-trans-feruloyltyramine, 3-hydroxy-5-methoxybibenzyl, phloroglucin, malanthroline, 10,12-dihydroxypicrotoxane, and nobilein H) identified from network analysis and nine key targets (MMP9, MMP1, MMP2, EGFR, ALOX5, ESR1, CA1, AR, and SHBG). Docking was not possible for MMP1, ALOX5, and SHBG, as their protein structures remain unknown. Docking scores are shown in Table 9; scores >5.0 (binding energy <-5 kcal / mol) indicate good binding activity. Results indicate that most compounds exhibited good binding activity with all six targets, with 91.7% achieving docking scores >5.0. Among them, N-trans-feruloyltyramine, Coelonin, and folate all had strong binding abilities to various targets, which was consistent with the results of spectrum efficacy experiments, further indicating that these three components may be the key active ingredients of Dendrobium nobile in the treatment of COPD.

[0170] Table 9 Docking scores of key components of Dendrobium nobile and targets

[0171]

[0172] 2.4.4 Drugability Assessment

[0173] The drugability of the above eight key active ingredients was predicted and analyzed using the ADMET lab2.0 database, with parameters including drug-likeness (QED) and bioavailability (F 20％ 、F 30％ ). QED is a scale parameter for measuring the drug-like properties of a compound. The larger the value, the better the drug-like properties. QED>0.67 indicates a high drug-like property. 20％ 、F 30％ These parameters represent the likelihood that the compound's bioavailability will be less than 20% or 30%, respectively. A larger parameter indicates a higher likelihood of a bioavailability of less than 20% or 30%, indicating poorer efficacy. The predicted results are shown in Table 10. The QEDs for all eight active ingredients are greater than 0.67, indicating good drug-like properties. Among these, coelonin, N-trans-feruloyltyramine, 10,12-dihydroxypicrotoxane, and nobile dendrobium H may exhibit good bioavailability.

[0174] Table 10 Results of investigation on the drugability of key active ingredients in Dendrobium nobile for anti-COPD

[0175]

[0176] *F 20％ 、F 30％ :0-0.1(---),0.1-0.3(--),0.3-0.5(-),0.5-0.7(+),0.7-0.9(++),0.9-1.0(+++).

[0177] 3. Summary

[0178] This study first evaluated the therapeutic effect of Dendrobium nobile on COPD using an animal model. The chemical basis of Dendrobium nobile was systematically analyzed using UHPLC Q-Exactive Orbitrap MS technology, and its key active ingredients for the treatment of COPD were screened using spectrum-effect association analysis and network pharmacology technology.

[0179] Results showed that Dendrobium nobile improved lung function in COPD mice, reduced levels of inflammatory factors such as IL-6, IL-1β, and TNF-α, enhanced lung SOD activity, and reduced MDA levels. Ninety-three chemical components were identified from Dendrobium nobile. Spectrum-effect association analysis identified the key active ingredients as N-trans-feruloyltyramine, coelonin, phleuroside, and dendrobiumol. Network pharmacology analysis identified the key active ingredients as coelonin, ephemeranthol C, phleuroside, phleuroside, N-trans-feruloyltyramine, 10,12-dihydroxypicrotoxane, dendrobium nobile H, and 3-hydroxy-5-methoxybibenzyl. Comprehensive analysis showed that N-trans-feruloyltyramide, coelonin, and pheloside may be the core active ingredients of Dendrobium nobile for the treatment of COPD, and dendrobium phenol, ephemeranthol C, magnolol, 10,12-dihydroxypicrotoxane, dendrobium nobile H, and 3-hydroxy-5-methoxybibenzyl may also make important contributions and play a synergistic therapeutic role.

Claims

1. A Dendrobium nobile extract for treating COPD, characterized in that: The Dendrobium nobile extract is obtained by extracting the Dendrobium nobile with water, alcohol or an alcohol-water solution and concentrating the extract.

2. The Dendrobium nobile extract according to claim 1, characterized in that The alcohol is selected from methanol, ethanol or propanol.

3. Use of the Dendrobium nobile extract according to claim 1 or 2 in preparing a medicament for treating COPD.

4. The use according to claim 3, characterized in that The medicine includes pharmaceutically usable excipients and is prepared into various usable dosage forms.

5. A method for screening anti-COPD active ingredients in Dendrobium nobile, characterized in that: The following steps are involved: 1) Pharmacological activity evaluation: The pharmacological activity of Dendrobium nobile in treating COPD was evaluated using animal models; 2) Chemical component identification: The chemical components of Dendrobium nobile were systematically identified using high-resolution liquid chromatography-mass spectrometry (HPLC-MS / MS). 3) Spectrum-effect correlation analysis: Different polarity extracts from Dendrobium nobile were combined to prepare differentiated samples. HPLC fingerprint analysis and efficacy evaluation were performed to obtain quantitative chemical and efficacy characteristics. Grey correlation analysis, partial least squares regression analysis, and Spearman correlation analysis were used to screen for active ingredients closely associated with efficacy. 4) Network pharmacology analysis: The Swiss Target Prediction Database and the CTD disease database were used to predict potential targets of chemical components of Dendrobium nobile for the treatment of COPD. Key active ingredients and targets were screened by constructing a component-target network, and molecular docking validation and drugability assessment were performed. 5) Integrate the results of the spectrum-effect association analysis in step 3) and the network pharmacology analysis in step 4) to determine the key active ingredients of Dendrobium nobile in the treatment of COPD.

6. The method according to claim 1, characterized in that In step 1), the evaluation indicators of the pharmacological activity include changes in body weight; changes in lung function parameters; changes in serum TNF-α, IL-1β, and IL-6 levels; and changes in SOD activity and MDA content in lung tissue.

7. The method according to claim 1, characterized in that In the high-resolution liquid chromatography-mass spectrometry technique of step 2), the chromatographic conditions are as follows: chromatographic column Agilent Eclipse Plus C18, 2.1 mm × 50 mm, 1.8 μm; mobile phase A is 0.1% formic acid in water, mobile phase B is acetonitrile, gradient elution: 0-2 min, 95% A→70% A, 2-8 min, 70% A, 8-20 min, 70% A→40% A, 20-25 min, 40% A→0% A, 25-30 min, 0% A; mass spectrometry conditions are as follows: an electrospray ion source is used, ion detection modes are full scan mode and dynamic data-dependent scan, and positive and negative modes are collected respectively; the ion source temperature is 350° C.; the collision energy is 40 V; and the mass scan range is m / z 100-1500.

8. The method according to claim 1, characterized in that In step 3), the preparation steps of the differential samples are as follows: using the uniform design method, the ethyl acetate, n-butanol and water extracts of Dendrobium nobile are combined with three factors A, B, and C and nine levels of 0, 25%, 50%, 75%, 100%, 125%, 150%, 175% and 200% to prepare 9 differential samples; in the HPLC fingerprint analysis of step 3), the chromatographic conditions are as follows: chromatographic column InertSustain C18, 4.6mm×250mm, 5μm; mobile phase A is water, mobile phase B is acetonitrile, elution gradient: 0-20min, 0.5%B→24%B; 20-40min, 24%B→24%B; 40-65min, 24%B→100%B; 65-70min, 100%B; step 3) the efficacy evaluation is to evaluate the anti-inflammatory activity of each differential sample using a lipopolysaccharide-induced RAW264.7 cell inflammation model; step 3) in the grey correlation analysis, the efficacy index is used as the reference series, the common peak area of ​​the differential samples is used as the comparison series, the resolution coefficient is 0.5, and the correlation factors with a correlation degree ≥0.7 and the top 5 are retained; in the partial least squares regression analysis, the standardization method is Autoscale, and the Venetian The model was cross-validated using the blinds method, and variables were screened using a VIP value > 1.0 as an indicator. In the Spearman correlation analysis, the peak area of ​​each common peak was subjected to bivariate correlation analysis with the efficacy index, and the Spearman correlation coefficient was calculated. The screening criteria were a correlation coefficient ≥ 0.3 and statistical significance (p < 0.05).

9. The method according to claim 1, characterized in that In step 4), the specific steps of constructing a component-target network to screen key active ingredients and targets are as follows: the chemical structures of the chemical components of Dendrobium nobile obtained by liquid chromatography-mass spectrometry analysis are imported into the Swiss Target Prdecition database, and the potential target proteins of each component are screened based on the top 15 results with a Probably value > 0. The obtained targets are imported into the CTD database, and the potential anti-COPD targets of each component are screened based on the highest inference score ≥ 85. Then, visualization processing is performed to construct a component-target network, and the degree value of each data point is analyzed to obtain the key active ingredients and targets of Dendrobium nobile for anti-COPD. The specific steps of the molecular docking verification in step 4) are as follows: the compound structure of the key active ingredient is saved as an SDF format file, and the protein structure of each target is obtained from the PDB protein library. The key active ingredient and the target are subjected to molecular docking analysis using software in a flexible docking mode, and the docking score > 5.0 is used as the evaluation standard. The drugability assessment in step 4) is assessed by analyzing drug-like properties and bioavailability.

10. The method according to claim 1, characterized in that The anti-COPD active ingredients screened were N-trans-feruloyltyramine, Coelonin, Phrynoside, Dendrobium phenol, Ephemeranthol C, Maurafenibine, 10,12-Dihydroxypicrotoxane, Nobile dendrobium H, and 3-hydroxy-5-methoxybibenzyl.

Images