# Exploring the Molecular Mechanism of Qing Guang An Granule in Treating Glaucoma Using Network Pharmacology and Molecular Docking

Authors: Chen Ou; Houpan Song; Yasha Zhou; Jun Peng; Qinghua Peng
Journal: Evidence-Based Complementary and Alternative Medicine
 (2020)

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## Abstract

Background. Qing Guang An Granule (QGAG), a Chinese patent medicine, has been used clinically to treat glaucoma for more than 20 years. Objective. To explore the possible mechanism of treatment of QGAG in glaucoma by using network pharmacology and molecular docking in this study. Methods. Active compounds and targets of each herb in QGAG were retrieved via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Glaucoma-related targets were acquired from OMIM and DisGeNET database. Key targets of QGAG against glaucoma were acquired by overlapping the above targets via the Venn diagram. Using the DAVID, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the key targets were performed. The docking process was performed using the AutoDock 4.2.6 and AutoDock Vina 1.1.2. Results. The 55 active compounds and 173 targets were obtained and constructed a compound-target network. The 20 key targets of QGAG in treating glaucoma were acquired, and these targets are involved in the apoptotic process, cellular response to hypoxia, negative regulation of cell growth, and ovarian follicle development. The main pathways are p53, HIF-1, PI3K-Akt, and neurotrophin signaling pathway. Conclusion. QGAG may exert a protective effect by acting on the optic nerve at a molecular and systemic level. This study can provide a certain basis for future researches on exploring the QGAG in treating glaucoma and provide new ideas for developing new drugs.


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## Body

## 1. Introduction

Glaucoma is the second leading cause of blindness in the world characterized by optic atrophy and visual field defects [1]. It is estimated that there are more than 10 million patients with blindness worldwide due to glaucoma [2]. The primary treatment for glaucoma is to reduce intraocular pressure by pressure lowering eye drops, laser treatment, and surgery [3]. However, the pathophysiology of glaucoma is considered to be multifactorial and complex, single targeted therapies may not be sufficient enough and may induce inevitable side effects and toxicity. Therefore, the discovery of new multitarget drugs is necessary.Traditional Chinese medicine (TCM) has been used to treat glaucoma for thousands of years. Shennong’s Classic of Materia Medica (Shennong Bencao Jing), one of the four classics of TCM, has first recorded glaucoma. In TCM, glaucoma is considered as a “five wind cataract”, which is caused by emotional depression, qi movement stagnation, and liver fire flaming upward [4]. In recent years, the prevention and treatment of glaucoma using TCM has attracted increasing attention [5]. Oral administration is one of the main ways of Chinese medicine application, with unique advantages and broad prospects for development.Qing Guang An Granule (QGAG), a Chinese patent medicine, consists of eight medicine herbs, includingAstragalus membranaceus (Huangqi, HQ), Plantago (Cheqianzi, CQZ), Safflower (Honghua, HH), Poria cocos (Fuling, FL), Radix Paeoniae Rubra (Chishao, CS), Atractylodes macrocephala (Baizhu, BZ), Rehmannia glutinosa (Shengdihuang, SDH), and Earthworm (Dilong, DL). QGAG, first proposed by Professor Qinghua Peng, has been used clinically to treat glaucoma for more than 20 years. Huangqi (HQ) and Shengdihuang (SDH) benefit qi and nourish yin, Dilong (DL), Honghua (HH) and Chishao (CS) activate blood circulation, and Fuling (FL), Baizhu (BZ), and Cheqianzi (CQZ) remove dampness [6]. Previous experiments have indicated that QGAG can reduce intraocular pressure of glaucoma [7]. The mechanism of QGAG against glaucoma is related to the downregulated expression of TGF-β1 and Smad3 and reduced scar tissue hyperplasia [8]. However, each Chinese medicine contains complex chemical components, and its efficacy is not simply added up. Therefore, further study of the molecular mechanisms of QGAG in treating glaucoma has great clinical significance.Network pharmacology is an approach for exploring the potential pharmacological mechanism of TCM through constructing biological networks. TCM has the features of multi-ingredients and multitargets, while network pharmacology has the features of multipathways and multilevels. Therefore, the systematic evaluation method of network pharmacology has a good predictive effect in the study of TCM [9]. Molecular docking is a computational method that predicts the binding interaction of the small molecule ligands and the target proteins, and it can be applied to confirm and check the result of network pharmacology [10]. In this study, we aim to explore the relationships between QGAG and glaucoma through network pharmacology and molecular docking.


## 2. Methods

### 2.1. Collection of Active Compounds and Targets in QGAG

Active compounds of each herb in QGAG were retrieved via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP,http://tcmspw.com/tcmsp.php); duplicate compounds were removed. Oral bioavailability (OB) ≥ 30% and drug-likeness (DL) index ≥ 0.18 are considered as important pharmacokinetic parameters to filter active compounds [11]. Prediction of possible targets related to compounds of QGAG was performed by searching “Related Targets” of the TCMSP Database. The obtained targets were entered into STRING (https://string-db.org/) to transform gene symbols.


### 2.2. Collection of Known Glaucoma-Related Targets

Glaucoma-related targets were acquired from the OMIM database (https://omim.org) and DisGeNET database (http://www.disgenet.org/). The obtained targets were entered into STRING (https://string-db.org/) to build Protein-Protein Interaction (PPI) networks.


### 2.3. Key Targets of QGAG for Treating Glaucoma

The key targets of QGAG against glaucoma were acquired by overlapping the above targets via Venn diagram (http://bioinfogp.cnb.csic.es/ tools/venny/index.html).


### 2.4. Network Construction

Based on the key targets obtained from the Venn diagram, we constructed an interaction network of the herbs, compounds, disease, and key targets using Cytoscape 3.6.0.


### 2.5. Gene Ontology (GO) Enrichment Analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis

GO enrichment analysis is normally classified into cell component (CC), biological process (BP), and molecular functions (MF) categories [12]. Using the DAVID (https://david.ncifcrf.gov/), the GO enrichment analysis and KEGG pathway analysis of the key targets were performed to obtain the related functions and pathways.


### 2.6. Molecular Docking

The three-dimensional structures of active compounds were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/), and the receptor proteins of key targets were obtained from Protein Data Bank (http://www.rcsb.org/pdb). The receptor proteins removed ligands and water by using the protein visualization software PyMOL 2.3.4. The docking process was performed using the AutoDock 4.2.6 and AutoDock Vina 1.1.2. From the docking results, docked conformation with the best scoring was selected for further mapping analysis. PyMOL was performed to show the interactions between receptor protein and ligand.


## 2.1. Collection of Active Compounds and Targets in QGAG

Active compounds of each herb in QGAG were retrieved via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP,http://tcmspw.com/tcmsp.php); duplicate compounds were removed. Oral bioavailability (OB) ≥ 30% and drug-likeness (DL) index ≥ 0.18 are considered as important pharmacokinetic parameters to filter active compounds [11]. Prediction of possible targets related to compounds of QGAG was performed by searching “Related Targets” of the TCMSP Database. The obtained targets were entered into STRING (https://string-db.org/) to transform gene symbols.


## 2.2. Collection of Known Glaucoma-Related Targets

Glaucoma-related targets were acquired from the OMIM database (https://omim.org) and DisGeNET database (http://www.disgenet.org/). The obtained targets were entered into STRING (https://string-db.org/) to build Protein-Protein Interaction (PPI) networks.


## 2.3. Key Targets of QGAG for Treating Glaucoma

The key targets of QGAG against glaucoma were acquired by overlapping the above targets via Venn diagram (http://bioinfogp.cnb.csic.es/ tools/venny/index.html).


## 2.4. Network Construction

Based on the key targets obtained from the Venn diagram, we constructed an interaction network of the herbs, compounds, disease, and key targets using Cytoscape 3.6.0.


## 2.5. Gene Ontology (GO) Enrichment Analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis

GO enrichment analysis is normally classified into cell component (CC), biological process (BP), and molecular functions (MF) categories [12]. Using the DAVID (https://david.ncifcrf.gov/), the GO enrichment analysis and KEGG pathway analysis of the key targets were performed to obtain the related functions and pathways.


## 2.6. Molecular Docking

The three-dimensional structures of active compounds were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/), and the receptor proteins of key targets were obtained from Protein Data Bank (http://www.rcsb.org/pdb). The receptor proteins removed ligands and water by using the protein visualization software PyMOL 2.3.4. The docking process was performed using the AutoDock 4.2.6 and AutoDock Vina 1.1.2. From the docking results, docked conformation with the best scoring was selected for further mapping analysis. PyMOL was performed to show the interactions between receptor protein and ligand.


## 3. Results

### 3.1. The Active Compounds and Targets in QGAG

QGAG consists of HQ, CQZ, HH, FL, CS, BZ, SDH, and DL. The 17 components of HQ, 7 components of CQZ, 17 components of HH, 6 components of FL, 14 components of CS, 4 components of BZ, 3 components of SDH, and 2 components of DL were obtained from the TCMSP. All active components should satisfy the criteria of OB ≥ 30% and DL ≥ 0.18. The 55 active compounds were obtained after deleting duplicates. The obtained compounds from the eight medicine herbs are shown in Table1. The obtained compounds were linked to targets, and networks of compound-target interactions were plotted using Cytoscape 3.6.0 software. The resulting compound-target network is shown in Figure 1. The network contains 283 nodes and 1194 compound-target interactions. For all active compounds, quercetin, kaempferol, luteolin, 7-O-methylisomucronulatol, baicalein, beta-sitosterol, Stigmasterol, formononetin, and isorhamnetin have the highest degree distributions.Table 1
The active compounds from the eight medicine herbs.
CodeMolecule nameOB%DLHerb nameM1Mairin55.380.78HQM2Jaranol50.830.29HQM3Hederagenin36.910.75HQ/FLM4(3S, 8S, 9S, 10R, 13R, 14S, 17R)-10,13-dimethyl-17-[(2R, 5S)-5-propan-2-yloctan-2-yl]-2, 3, 4, 7, 8, 9, 11, 12, 14, 15, 16, 17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol36.230.78HQ/BZM5Isorhamnetin49.600.31HQM63,9-di-O-methylnissolin53.740.48HQM77-O-methylisomucronulatol74.690.30HQM89,10-Dimethoxypterocarpan-3-O-β-D-glucoside36.740.92HQM9(6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano [3,2-c]chromen-3-ol64.260.42HQ/DLM10Bifendate31.100.67HQM11Formononetin69.670.21HQM12Calycosin47.750.24HQM13Kaempferol41.880.24HQ/HH/SDHM14FA68.960.71HQM15Isomucronulatol-7, 2′-di-O-glucosiole49.280.62HQM161, 7-Dihydroxy-3, 9-dimethoxy pterocarpene39.050.48HQM17Quercetin46.430.28HQ/CQZ/HH/SDHM18Dinatin30.970.27CQZM19Sitosterol36.910.75CQZ/CSM20Daucostero_qt36.910.75CQZM21Dihydrotricetin58.120.28CQZM22Hypolaetin33.240.28CQZM23orobanchoside_qt55.990.82CQZM24Poriferast-5-en-3beta-ol36.910.75HHM254-[(E)-4-(3, 5-dimethoxy-4-oxo-1-cyclohexa-2, 5-dienylidene)but-2-enylidene]-2, 6-dimethoxycyclohexa-2, 5-dien-1-one48.470.36HHM26Lignan43.320.65HHM27Pyrethrin II48.360.35HHM286-Hydroxykaempferol62.130.27HHM29Baicalein33.520.21HH/CSM30qt_carthamone51.030.20HHM31Quercetagetin45.010.31HHM327, 8-Dimethyl-1H-pyrimido[5,6-g]quinoxaline-2, 4-dione45.750.19HHM33Beta-carotene37.180.58HHM34Baicalin40.120.75HH/CSM35Beta-sitosterol36.910.75HH/CSM36Stigmasterol43.830.76HH/CSM37Luteolin36.160.25HH/SDHM38CLR37.870.68HHM39(2R)-2-[(3S, 5R, 10S, 13R, 14R, 16R, 17R)-3,16-dihydroxy-4, 4, 10, 13, 14-pentamethyl-2, 3, 5, 6, 12, 15, 16, 17-octahydro-1H-cyclopenta[a]phenanthren-17-yl]-6-methylhept-5-enoic acid30.930.81FLM40Trametenolic acid38.710.80FLM41Cerevisterol37.960.77FLM42Ergosta-7, 22E-dien-3beta-ol43.510.72FLM43Ergosterol peroxide40.360.81FLM44Ellagic acid43.060.43CSM45Paeoniflorgenone87.590.37CSM46Paeoniflorin53.870.79CSM47Spinasterol42.980.76CSM48(+)-catechin54.830.24CSM49(2R,3R)-4-methoxyl-distylin59.980.30CSM50Stigmast-7-en-3-ol37.420.75CS/DLM51Ethyl oleate (NF)32.400.19CSM52Campest-5-en-3beta-ol37.580.71CSM5314-Acetyl-12-senecioyl-2E,8Z,10E-atractylentriol63.370.30BZM543β-acetoxyatractylone54.070.22BZM558β-ethoxy atractylenolide III35.950.21BZFigure 1
The compound-target network (red triangle represents active compounds; purple diamond represents targets).


### 3.2. PPI Network of Glaucoma-Related Targets

By researching the OMIM and DisGeNET database, 176 and 380 genes were acquired in these two databases, respectively. A total of 345 nodes and 2630 edges were involved in the PPI network, with an average of 15.2 edges per node. The resulting PPI network is shown in Figure2.Figure 2
The PPI network of glaucoma-related targets.


### 3.3. Key Targets of QGAG for Treating Glaucoma

The key targets of QGAG against glaucoma were obtained by overlapping the 228 targets of active compounds and 345 targets of related glaucoma with a Venn diagram. This analysis derived 20 targets, including ADRB2, RHO, MMP3, VEGFA, BCL2, CDKN1A, BAX, TP53, MMP1, GJA1, IL1B, SELE, PTGER3, NOS3, CYP1B1, GSTP1, COL3A1, GSTM1, TDRD7, and LYZ. The resulting Venn diagram is shown in Figure3.Figure 3
Overlapping the 228 targets of active compounds and 345 targets of related glaucoma.


### 3.4. Network between Medicine Herbs, Active Compounds, Key Targets, and Glaucoma

The resulting medicine herbs-active compounds-key targets-disease network is shown in Figure4. Thus, 20 key targets related to 16 active compounds of QGAG were selected against glaucoma. Among them, the key target with the most connections with active compounds is ADRB2.Figure 4
The herbs-active compounds-key targets-disease network (blue ellipse represents medicine herbs; red diamond represents active compounds; purple round rectangle represents key targets; yellow triangle represents disease).


### 3.5. GO Enrichment Analysis and KEGG Pathway Analysis

To further explore the multiple mechanisms of QGAG on glaucoma from a systematic level, GO enrichment analysis and KEGG pathway enrichment of the 20 key targets were performed. Among them, 9 items related to biological processes were found, including response to a toxic substance, positive regulation of intrinsic apoptotic signaling pathway, apoptotic process, cellular response to hypoxia, and ovarian follicle development. Meanwhile, 5 items were related to cell composition, including mitochondrion, mitochondrial outer membrane, endoplasmic reticulum, endoplasmic reticulum membrane, and membrane, and 4 items were related to molecular function, including identical protein binding, protein heterodimerization activity, ubiquitin-protein ligase binding, and protein homodimerization activity. The GO terms of each category are illustrated in Table2.Table 2
The GO enrichment analysis.
CategoryDescriptionCoutPop hitsP valueFold enrichmentBPResponse to toxic substance5852.2E − 649.39Response to gamma radiation3315.5E − 481.25Positive regulation of intrinsic apoptotic signaling pathway3336.3E − 476.33Negative regulation of the apoptotic process54551.5E − 39.23Apoptotic process55673.3E − 37.40Cellular response to hypoxia3965.2E − 326.24Negative regulation of cell growth41213.3E − 427.76Cellular response to DNA damage stimulus32082.3E − 212.11Ovarian follicle development3421.0E − 359.97CCMitochondrion613311.0E − 24.11Mitochondrial outer membrane31491.0E − 218.35Endoplasmic reticulum membrane48625.8E − 24.23Endoplasmic reticulum38282.1E − 13.30Membrane322006.9E − 11.24MFIdentical protein binding57498.7E − 35.63Protein heterodimerization activity44651.4E − 27.26Ubiquitin protein ligase binding32874.1E − 28.82Protein homodimerization activity57308.0E − 35.78The pathways of 20 key targets were analyzed via pathway enrichment, and 20 signaling pathways were obtained. The involved pathway was mainly composed of the p53 signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, Sphingolipid signaling pathway, apoptosis, and neurotrophin signaling pathway (Figure5).Figure 5
Bubble diagram of KEGG pathway analysis. TheY-axis label represents the pathway and the X-axis label represents the rich factor. The size and color of the bubble represent the number of genes enriched in pathway and enrichment significance, respectively.


### 3.6. Molecular Docking

The molecular docking between active compounds quercetin, kaempferol, luteolin, 7-O-methylisomucronulatol, baicalein, beta-sitosterol, Stigmasterol, formononetin, isorhamnetin, and key target ADRB2 (PDB ID: 2R4S) was performed. The binding energies of these 9 active compounds with ADRB2 are −7.8, −7.9, −8.0, −7.6, −7.9, −9.2, −9.5, −7.5, and −7.9 kcal/mol, respectively. The more negative the binding energy, the more stable the compound binds to the target. The Stigmasterol binding with the ADRB2 showed the highest binding energy (−9.5 kcal/mol). Figure6 shows the binding between Stigmasterol and ADRB2. The amino acid residues Leu145, Phe71, Val157, VAL160, Thr164, Ser207, Val206, Cys125, Val129, Phe133, Asp130, Val126, Glu122, and Thr118 participated in the hydrophobic interactions between Stigmasterol small molecule ligand.Figure 6
Molecular docking between Stigmasterol and ADRB2.


## 3.1. The Active Compounds and Targets in QGAG

QGAG consists of HQ, CQZ, HH, FL, CS, BZ, SDH, and DL. The 17 components of HQ, 7 components of CQZ, 17 components of HH, 6 components of FL, 14 components of CS, 4 components of BZ, 3 components of SDH, and 2 components of DL were obtained from the TCMSP. All active components should satisfy the criteria of OB ≥ 30% and DL ≥ 0.18. The 55 active compounds were obtained after deleting duplicates. The obtained compounds from the eight medicine herbs are shown in Table1. The obtained compounds were linked to targets, and networks of compound-target interactions were plotted using Cytoscape 3.6.0 software. The resulting compound-target network is shown in Figure 1. The network contains 283 nodes and 1194 compound-target interactions. For all active compounds, quercetin, kaempferol, luteolin, 7-O-methylisomucronulatol, baicalein, beta-sitosterol, Stigmasterol, formononetin, and isorhamnetin have the highest degree distributions.Table 1
The active compounds from the eight medicine herbs.
CodeMolecule nameOB%DLHerb nameM1Mairin55.380.78HQM2Jaranol50.830.29HQM3Hederagenin36.910.75HQ/FLM4(3S, 8S, 9S, 10R, 13R, 14S, 17R)-10,13-dimethyl-17-[(2R, 5S)-5-propan-2-yloctan-2-yl]-2, 3, 4, 7, 8, 9, 11, 12, 14, 15, 16, 17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol36.230.78HQ/BZM5Isorhamnetin49.600.31HQM63,9-di-O-methylnissolin53.740.48HQM77-O-methylisomucronulatol74.690.30HQM89,10-Dimethoxypterocarpan-3-O-β-D-glucoside36.740.92HQM9(6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano [3,2-c]chromen-3-ol64.260.42HQ/DLM10Bifendate31.100.67HQM11Formononetin69.670.21HQM12Calycosin47.750.24HQM13Kaempferol41.880.24HQ/HH/SDHM14FA68.960.71HQM15Isomucronulatol-7, 2′-di-O-glucosiole49.280.62HQM161, 7-Dihydroxy-3, 9-dimethoxy pterocarpene39.050.48HQM17Quercetin46.430.28HQ/CQZ/HH/SDHM18Dinatin30.970.27CQZM19Sitosterol36.910.75CQZ/CSM20Daucostero_qt36.910.75CQZM21Dihydrotricetin58.120.28CQZM22Hypolaetin33.240.28CQZM23orobanchoside_qt55.990.82CQZM24Poriferast-5-en-3beta-ol36.910.75HHM254-[(E)-4-(3, 5-dimethoxy-4-oxo-1-cyclohexa-2, 5-dienylidene)but-2-enylidene]-2, 6-dimethoxycyclohexa-2, 5-dien-1-one48.470.36HHM26Lignan43.320.65HHM27Pyrethrin II48.360.35HHM286-Hydroxykaempferol62.130.27HHM29Baicalein33.520.21HH/CSM30qt_carthamone51.030.20HHM31Quercetagetin45.010.31HHM327, 8-Dimethyl-1H-pyrimido[5,6-g]quinoxaline-2, 4-dione45.750.19HHM33Beta-carotene37.180.58HHM34Baicalin40.120.75HH/CSM35Beta-sitosterol36.910.75HH/CSM36Stigmasterol43.830.76HH/CSM37Luteolin36.160.25HH/SDHM38CLR37.870.68HHM39(2R)-2-[(3S, 5R, 10S, 13R, 14R, 16R, 17R)-3,16-dihydroxy-4, 4, 10, 13, 14-pentamethyl-2, 3, 5, 6, 12, 15, 16, 17-octahydro-1H-cyclopenta[a]phenanthren-17-yl]-6-methylhept-5-enoic acid30.930.81FLM40Trametenolic acid38.710.80FLM41Cerevisterol37.960.77FLM42Ergosta-7, 22E-dien-3beta-ol43.510.72FLM43Ergosterol peroxide40.360.81FLM44Ellagic acid43.060.43CSM45Paeoniflorgenone87.590.37CSM46Paeoniflorin53.870.79CSM47Spinasterol42.980.76CSM48(+)-catechin54.830.24CSM49(2R,3R)-4-methoxyl-distylin59.980.30CSM50Stigmast-7-en-3-ol37.420.75CS/DLM51Ethyl oleate (NF)32.400.19CSM52Campest-5-en-3beta-ol37.580.71CSM5314-Acetyl-12-senecioyl-2E,8Z,10E-atractylentriol63.370.30BZM543β-acetoxyatractylone54.070.22BZM558β-ethoxy atractylenolide III35.950.21BZFigure 1
The compound-target network (red triangle represents active compounds; purple diamond represents targets).


## 3.2. PPI Network of Glaucoma-Related Targets

By researching the OMIM and DisGeNET database, 176 and 380 genes were acquired in these two databases, respectively. A total of 345 nodes and 2630 edges were involved in the PPI network, with an average of 15.2 edges per node. The resulting PPI network is shown in Figure2.Figure 2
The PPI network of glaucoma-related targets.


## 3.3. Key Targets of QGAG for Treating Glaucoma

The key targets of QGAG against glaucoma were obtained by overlapping the 228 targets of active compounds and 345 targets of related glaucoma with a Venn diagram. This analysis derived 20 targets, including ADRB2, RHO, MMP3, VEGFA, BCL2, CDKN1A, BAX, TP53, MMP1, GJA1, IL1B, SELE, PTGER3, NOS3, CYP1B1, GSTP1, COL3A1, GSTM1, TDRD7, and LYZ. The resulting Venn diagram is shown in Figure3.Figure 3
Overlapping the 228 targets of active compounds and 345 targets of related glaucoma.


## 3.4. Network between Medicine Herbs, Active Compounds, Key Targets, and Glaucoma

The resulting medicine herbs-active compounds-key targets-disease network is shown in Figure4. Thus, 20 key targets related to 16 active compounds of QGAG were selected against glaucoma. Among them, the key target with the most connections with active compounds is ADRB2.Figure 4
The herbs-active compounds-key targets-disease network (blue ellipse represents medicine herbs; red diamond represents active compounds; purple round rectangle represents key targets; yellow triangle represents disease).


## 3.5. GO Enrichment Analysis and KEGG Pathway Analysis

To further explore the multiple mechanisms of QGAG on glaucoma from a systematic level, GO enrichment analysis and KEGG pathway enrichment of the 20 key targets were performed. Among them, 9 items related to biological processes were found, including response to a toxic substance, positive regulation of intrinsic apoptotic signaling pathway, apoptotic process, cellular response to hypoxia, and ovarian follicle development. Meanwhile, 5 items were related to cell composition, including mitochondrion, mitochondrial outer membrane, endoplasmic reticulum, endoplasmic reticulum membrane, and membrane, and 4 items were related to molecular function, including identical protein binding, protein heterodimerization activity, ubiquitin-protein ligase binding, and protein homodimerization activity. The GO terms of each category are illustrated in Table2.Table 2
The GO enrichment analysis.
CategoryDescriptionCoutPop hitsP valueFold enrichmentBPResponse to toxic substance5852.2E − 649.39Response to gamma radiation3315.5E − 481.25Positive regulation of intrinsic apoptotic signaling pathway3336.3E − 476.33Negative regulation of the apoptotic process54551.5E − 39.23Apoptotic process55673.3E − 37.40Cellular response to hypoxia3965.2E − 326.24Negative regulation of cell growth41213.3E − 427.76Cellular response to DNA damage stimulus32082.3E − 212.11Ovarian follicle development3421.0E − 359.97CCMitochondrion613311.0E − 24.11Mitochondrial outer membrane31491.0E − 218.35Endoplasmic reticulum membrane48625.8E − 24.23Endoplasmic reticulum38282.1E − 13.30Membrane322006.9E − 11.24MFIdentical protein binding57498.7E − 35.63Protein heterodimerization activity44651.4E − 27.26Ubiquitin protein ligase binding32874.1E − 28.82Protein homodimerization activity57308.0E − 35.78The pathways of 20 key targets were analyzed via pathway enrichment, and 20 signaling pathways were obtained. The involved pathway was mainly composed of the p53 signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, Sphingolipid signaling pathway, apoptosis, and neurotrophin signaling pathway (Figure5).Figure 5
Bubble diagram of KEGG pathway analysis. TheY-axis label represents the pathway and the X-axis label represents the rich factor. The size and color of the bubble represent the number of genes enriched in pathway and enrichment significance, respectively.


## 3.6. Molecular Docking

The molecular docking between active compounds quercetin, kaempferol, luteolin, 7-O-methylisomucronulatol, baicalein, beta-sitosterol, Stigmasterol, formononetin, isorhamnetin, and key target ADRB2 (PDB ID: 2R4S) was performed. The binding energies of these 9 active compounds with ADRB2 are −7.8, −7.9, −8.0, −7.6, −7.9, −9.2, −9.5, −7.5, and −7.9 kcal/mol, respectively. The more negative the binding energy, the more stable the compound binds to the target. The Stigmasterol binding with the ADRB2 showed the highest binding energy (−9.5 kcal/mol). Figure6 shows the binding between Stigmasterol and ADRB2. The amino acid residues Leu145, Phe71, Val157, VAL160, Thr164, Ser207, Val206, Cys125, Val129, Phe133, Asp130, Val126, Glu122, and Thr118 participated in the hydrophobic interactions between Stigmasterol small molecule ligand.Figure 6
Molecular docking between Stigmasterol and ADRB2.


## 4. Discussion

The efficacy of QGAG has been verified through more than 20 years of clinical application [13]. However, the pharmacological mechanism of QGAG in treating glaucoma still lacks deep understanding. In this study, we used the network pharmacology and molecular docking approach to illuminate the multiple underlying mechanisms of QGAG in glaucoma treatment from a systematic perspective. The active compounds, targets, PPI networks, GO enrichment analysis, and KEGG pathway analysis were used to reveal the relationships between QGAG and glaucoma.TCMSP database was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 herbal medicines registered in the Chinese pharmacopeia with 29,384 ingredients, 3,311 targets, and 837 related diseases [11]. The 55 active compounds and 228 targets were obtained via TCMSP databases and constructed a compound-target network. The key compounds of QGAG in the compound-target network included quercetin, kaempferol, luteolin, 7-O-methylisomucronulatol, baicalein, beta-sitosterol, Stigmasterol, formononetin, and isorhamnetin. Stigmasterol is a phytosterol and possesses anti-inflammatory, antioxidant, and anticancer activities [14]. Glaucomatous blindness is caused by the eventual apoptosis of retinal ganglion cells, and quercetin has been proven to protect retinal ganglion cells [15]. Some studies have shown that quercetin can inhibit the proliferation of human fibroblasts and thus reduce postoperative scarring of the filtration tract [16, 17]. In a recent study, it has been reported that baicalein can promote the growth of retinal ganglion axons and protect optic nerve activity, improving the microcirculation of the visual nipple [18].In our study, there are 20 key targets of QGAG in treating glaucoma. RHO has a close relationship with glaucoma, and the inhibition of RHO expression can lower intraocular pressure, change retinal vasculature perfusion, and promote regeneration of the optic nerve [19]. BCL and BAX are members of the BCL-2 family, which relieve optic nerve injury by preventing apoptosis of retinal ganglion cells [20]. Presently, TDRD7, CYP1B1, GJA1, IL1B, MMP1, and MMP3 have been considered as a causative gene for glaucoma [21–25]. ADRB2, a gene of β-adrenergic receptor family genes, is widely distributed in eye tissue [26]. Timolol maleate is a β-adrenergic receptor antagonist that has been widely used as eye drops for the treatment of high intraocular pressure in patients with glaucoma for many years. The result of molecular docking has shown that the binding energies of selected active compounds with ADRB2 lower than −7 kcal/mol indicate that these active compounds might act directly on ADRB2 to treat glaucoma.GO enrichment analysis and KEGG pathway mapping are efficient methods to analyze gene function. GO enrichment analysis found that the effects of QGAG in the treatment of glaucoma are mainly reflected in the apoptotic process, cellular response to hypoxia, negative regulation of cell growth, and ovarian follicle development. Enriched KEGG pathways were predominantly associated with some signaling pathways. The PI3K-Akt and P53 signaling pathway are related to apoptosis, and downregulating the expression of P53 can reduce ganglion cell apoptosis [27]. A study has indicated that HIF-1 expression in hypoxic conditions in glaucoma might be a crucial stage in damage to optic nerve axon and retinal ganglion cells [28]. Inflammation might be involved in the pathogenesis of glaucoma, and the sphingolipids signaling pathway plays an important signaling role in the pathophysiology of ocular inflammatory diseases [29]. Neurotrophins as a therapeutic drug for glaucoma and neurotrophin signaling pathway have been verified as vital signaling to protect the optic nerve [30]. Based on the results of this study, the abovementioned active compounds, targets, and pathways are associated with the pharmacological mechanisms of QGAG in glaucoma treatment.


## 5. Conclusion

In summary, we used the network pharmacology and molecular docking approach to illuminate the multiple underlying mechanisms of QGAG in glaucoma treatment. The results indicate that QGAG may exert a protective effect by acting on retinal ganglion cell and optic nerve at a molecular level. However, the results require further experimental verification. This study can provide a certain basis for future research on exploring the QGAG in treating glaucoma and provide new ideas for developing new drugs.



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*Source: 8824150-2020-11-23.xml*