Integrating UPLC–Q-TOF–MS and network pharmacology to analyze the components and mechanism of action of Compound Duzhong Zhuangyao Capsules on osteoporosis

Abstract

Although Compound Duzhong Zhuangyao Capsules (Co-DZZY Capsules) are used to treat lumbago and knee weakness caused by osteoporosis (OP), the underlying mechanisms involved remain unclear. Therefore, this study aimed to investigate the active components of Co-DZZY Capsules and the involved mechanisms for the treatment of OP. The components of the Co-DZZY Capsules were tentatively identified using ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry, and their targets were retrieved from the Swiss Target Prediction database. OP-related targets were obtained from the Gene Cards database. A protein–protein interaction network was constructed using the STRING data platform, and the compound-target-disease visualization network was established using Cytoscape software (Cytoscape Consortium, San Diego). Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were performed using the DAVID database. The AutoDock software (Molecular Graphics Laboratory at The Scripps Research Institute [TSRI], San Diego) was used to verify molecular docking between the selected components and core targets. In total, 92 compounds were identified, whose 101 predicted targets were associated with OP. The potential active ingredients included luteolin, allocryptopine, kaempferol, isobavachin, and albiflorin. The core targets identified were threonine-protein kinase, interleukin-6, tumor necrosis factor alpha, peroxisome proliferator-activated receptor gamma, signal transducer and activator of transcription 3, and tyrosine-protein kinase. Kyoto encyclopedia of genes and genomes analysis revealed that Co-DZZY Capsules activate the advanced glycation end product receptor for advanced glycation end products, hypoxia inducible factor-1, phosphatidylinositol 3-kinase-protein kinase B, tumor necrosis factor alpha, and ras-related protein 1 signaling pathways, and other signaling pathways via the core targets, and are involved in positive regulation of protein kinases, smooth muscle cell proliferation, cell migration, and other biological processes. Molecular docking revealed that the core targets were stably bound to the corresponding compounds. This study provides a scientific basis for analyzing the bioactive compounds in Co-DZZY Capsules and their pharmacological mechanisms of action.

1. Introduction

Osteoporosis (OP) is a systemic degenerative bone disease characterized by low bone mass and deterioration of bone microarchitecture, leading to reduced bone strength and increased fracture risk.^[1] Approximately >200 million people worldwide suffer from OP, and its incidence continues to increase, making it a serious public health concern.^[2] OP usually manifests as weakness, lower back discomfort, or soreness. Additionally, poor systemic treatment can easily lead to fracture, which seriously affects the quality of life of patients. Current strategies for treating OP include antiresorptive and osteogenic drugs.^[3] However, the side effects associated with long-term use of these drugs remain a substantial challenge. In this regard, natural medicinal ingredients, such as those used in traditional Chinese medicine (TCM), are a promising alternative.

TCM has a long history in the treatment of OP,^[4,5] and it is based on the synergistic effects of multiple components. For instance, Compound Duzhong Zhuangyao Capsules (Co-DZZY Capsules) is a TCM formula composed of 17 medicinal herbs namely, Eucommiae Cortex (Du Zhong), Codonopsis Radix (Dang Shen), Rehmanniae Radix Praeparata (Shu Di Huang), Artemisiae argyi Folium (Ai Ye), Paeoniae Radix Alba (Bai Shao), Psoralea Fructus (Bu Gu Zhi), Cibotii Rhizoma (Gou Ji), Lycii Fructus (Gou Qi Zi), Allii tuberosi Semen (Jiu Cai Zi), Ephedrae Herba (Ma Huang), Achyranthis Bidentatae Radix (Niu Xi), Corni Fructus (Shan Zhu Yu), Cuscutae Semen (Tu Si Zi), Asari Radix et Rhizoma (Xi Xin), Corydalis Rhizoma (Yan Hu Suo), Cervi Cornu (Lu Jiao), Capra Tibia (Yang Jing Gu). Co-DZZY Capsules are used for tonifying the kidney, strengthening waist and knee, treating lumbago and knee weakness caused by OP. Additionally, studies have shown that Eucommiae Cortex,^[6] Rehmanniae Radix Praeparata,^[7] Psoralea Fructus,^[8] Corni Fructus,^[9] Cibotii Rhizoma,^[10] and several other components in the Co-DZZY Capsules can inhibit osteoclast differentiation and bone resorption, and stimulate osteoblast differentiation and bone mineralization. Subsequently, clinical practice has confirmed that Co-DZZY Capsules are effective in treating OP. However, the underlying pharmacological mechanisms of Co-DZZY Capsules in treating OP remain unclear, making it is necessary to identify its components, targets and regulatory methods.

Ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC–Q-TOF–MS) technology can provide structural fragment information of compounds at different retention times, and has become prevalent among studies on active ingredients in TCM.^[11] Network pharmacology is a method of searching for drug molecules and disease targets through biological networks. This method can systematically exhibit the impact of drugs on diseases, and reveal the synergistic mechanism of multi-molecular drugs, using the “disease-target-drug” interaction network.^[12] Thus, the combination of UPLC–Q-TOF–MS and network pharmacology is a promising approach to further the research on identifying the components, their targets and the therapeutic mechanism of Co-DZZY Capsules.

Therefore, this study aimed to identify the main chemical components of Co-DZZY Capsules and elucidate the active components involved in the treatment of OP and their action mechanisms, providing a scientific basis for further drug development of Co-DZZY Capsules.

2. Materials and methods

The flow chart of the study design was shown in Figure 1.

Figure 1.

Network pharmacological study of Compound Duzhong Zhuangyao Capsules for the treatment of osteoporosis.

2.1. Instruments and materials

An Impact II High-resolution 4-pole time-of-flight mass spectrometer (Bruker, Billerica), ultra-high-performance liquid chromatograph (Thermo Fisher, Waltham), KQ-500DE ultrasonic cleaner (Kunshan Ultrasonic Instrument Co. Ltd., China), and Milli-Q integral water purification system (Millipore Corporation, Burlington) were used in this study.

Methanol, formic acid, and acetonitrile were obtained from Thermo Fisher Scientific (Waltham), and all chemicals and solvents were of chromatographic grade. Co-DZZY Capsules (Batch no: 231203) were provided by Guangxi Huatianbao Pharmaceutical Company Limited. (China). The reference standards psoralen (Batch no: 110739–202319), isopsoralen (Batch no: 110738–202317), pseudoephedrine hydrochloride (Batch no: 171237–201910), ephedrine hydrochloride (Batch no: 171241–201809), monoside (Batch no: 111998–201703), loganin (Batch no: 111640–201808), protocatechuic acid (Batch no: 110809–201906), paeonin (Batch no: 110736–202145), and pinoresinol diglucoside (Batch no: 111537–201706) were purchased from China National Institutes for Drug Control, Beijing, China. Albiflorin (Batch no: 0121-RG-0008) was purchased from CATO Reaearch Chemicals Inc., Guangzhou, China.

2.2. UPLC–Q-TOF–MS analysis

2.2.1. Preparation of sample and control solutions

The Co-DZZY Capsules (0.5 g) contents were ultrasonically (frequency 40 kHz, power 100 W) treated with 10 mL methanol for 40 minutes. Subsequently, the solution was filtered through a 0.45 μm syringe filter for UPLC–Q-TOF–MS analysis. Controls were dissolved in methanol to prepare a mixed solution of 100 μg/mL respectively.

2.2.2. Chromatographic parameters

Separation was performed using a chromatographic column APCELL PAK C18 MGⅡ (4.6 × 250 mm, 5 μm). A column temperature of 35 °C, an injection volume of 10 μL and a flow rate of 1 mL/min maintained for the mobile phase, which comprised 0.1% formic acid water (A) and acetonitrile (B). The gradient elution sequence was as follows: 0 to 5 minutes, 10% B; 5 to 45 minutes, 10 to 70% B; 45 to 50 minutes, 70 to 95% B; 50 to 55 minutes, 95% B; 55 to 60 minutes, 95 to 10% B; 60 to 70 minutes, 10% B. Thereafter, a shunt between the diode array detector and the mass spectrometry (MS) detector was conducted in parallel at a 1:1 ratio.

2.2.3. Mass spectrometry conditions

An electrospray ionization source was used for the positive and negative ion modes, with a scanning range of m/z 50 to 2500. Capillary voltage of 2500 V, atomizing gas pressure of 2 bar, dry gas flow rate of 8.0 L/min, dry temperature of 200 °C were used.

2.2.4. Structure analysis

DataAnalysis (Bruker, Billerica) was used to analyze the MS data. The compounds in the sample solution were identified based on the main chromatographic peaks, relative molecular weights of the compounds, ion fragment information, control products, and related literature.

2.3. Network pharmacology research

2.3.1. Acquisition of compound targets, disease targets, and intersecting targets

The components of the Co-DZZY Capsules were identified using UPLC–Q-TOF–MS. SMILES information of these compounds was obtained through PubChem (https://pubchem.ncbi.nlm.nih.gov) database and the SwissTargetPrediction (http://www.swissadme.ch) database was searched to predict the targets of the compounds in Co-DZZY Capsules; only the results with P > .1 were included.^[13] The GeneCards (https://www.genecards.org) database^[14] was used to seek targets related to the keyword “Osteoporosis,” and only results with relevance score > 2 were included. The compound targets of the Co-DZZY Capsules and OS-related targets were intersected using a Venn diagram to obtain intersection targets.

2.3.2. Construction of compound–target-disease network

The “compound–target–disease” network was constituted using the Cytoscape 3.10.2 software^[15] to visualize relationships as well as pathways targeted by the compounds in Co-DZZY Capsules, and to clarify the mechanism of action against OP.

2.3.3. Construction of protein–protein interaction network

The intersection of the Co-DZZY Capsules and OP targets was imported into the STRING database (https://string-db.org/)^[16] to construct a protein–protein interaction (PPI) network and subsequent data analysis. PPI data were input into Cytoscape 3.10.2 software for visualization and a PPI network was constructed. The network Analyzer function was used for topology analysis, and the top 6 target proteins were selected as key targets in accordance with the node degree value.

2.3.4. Enrichment of gene ontology (GO) term and Kyoto encyclopedia of genes and genomes (KEGG) pathway

Intersecting genes were further evaluated using GO and KEGG enrichment analyses using the DAVID database (https://davidbioinformatics.nih.gov/).^[17] The top 10 most significant GO terms and top 25 most significant KEGG pathways with P < .05 were selected for visualization using the Bioinformatics tool (https://www.bioinformatics.com.cn/).

2.3.5. Construction of component–target–pathway network

The top 20 components ranked by degree value in the compound-target-disease network, the top 20 intersection targets in the PPI network, and the top 20 KEGG pathways were imported into Cytoscape software to construct the active component-target-pathway network to explore the pharmacodynamic material basis and antiosteoporosis mechanisms.

2.3.6. Molecular docking verification

Based on the PPI network results, the top 6 targets were screened as receptors. The entry number of the target was obtained using the UniProt Database (https://www.uniprot.org/) and copied into the PDB online platform (https://www.rcsb.org/) to obtain the 3D protein structure.^[18] The 2 dimensional structures of the active ingredients corresponding to the key targets were downloaded from the PubChem database, and their minimum binding energies were optimized using ChemBio3D Ultra.^[19] Molecular docking was performed using AutoDock Tools 1.5.7, (Molecular Graphics Laboratory at The Scripps Research Institute [TSRI], San Diego) AutoDock Vina 1.1.2 (Molecular Graphics Laboratory at The Scripps Research Institute [TSRI], San Diego), and 3-dimensional visualization of the docking results was generated through PyMOL3.0.3 (Schrödinger, New York).^[20]

3. Results

3.1. Identification of chemical composition of Co-DZZY Capsules

The base peak ion chromatograms of the Co-DZZY Capsules were detected in positive and negative ion modes, as shown in Figure 2. The base peak ion chromatograms of the reference standards are shown in Figure 3. A total of 92 compounds (see Table S1, Supplemental Content, https://links.lww.com/MD/Q558 which illustrates the specific compound information) were tentatively identified based on retention time, relative molecular mass, secondary fragment ions, and relevant literature reports, including 24 flavonoids, 22 phenylpropanoids, 17 terpenes, 12 organic acids, 8 alkaloids, and 9 other chemical types.

Figure 2.

Base peak ion chromatogram of Compound Duzhong Zhuangyao Capsules. (A) Positive ion mode. (B) Negative ion mode.

Figure 3.

Base peak ion chromatogram of reference standards. (A) Co-DZZY Capsules in positive ion mode. (B) Reference standards in positive ion mode. (C) Co-DZZY Capsules in negative ion mode. (D) Reference standards in negative ion mode. (1) Ephedrine hydrochloride. (2) Pseudoephedrine hydrochloride. (3) Psoralen. (4) Isopsoralen. (5) Protocatechuic acid. (6) Monoside. (7) Loganin. (8) Pinoresinol diglucoside. (9) Albiflorin. (10) Aaeonin. Co-DZZY Capsules = Compound Duzhong Zhuangyao Capsules.

In addition to Cervi Cornu and Capra Tibia, chemical components of 15 medicinal herbs were identified. Among them, 12 were derived from Eucommiae Cortex, 10 from Codonopsis Radix, 9 from Rehmanniae Radix Praeparata, 7 from Artemisiae argyi Folium, 11 from Paeoniae Radix Alba, 22 from Psoralea Fructus, 12 from Cibotii Rhizoma, 9 from Lycii Fructus, 8 from Allii tuberosi Semen, 11 from Ephedrae Herba, 8 from Achyranthis Bidentatae Radix, 11 from Corni Fructus, 6 from Cuscutae Semen, 1 from Asari Radix et Rhizoma, and 5 from Corydalis Rhizoma.

3.1.1. Flavonoids

Flavonoids mainly originate from Psoralea Fructus, Artemisiae argyi Folium, Achyranthis Bidentatae Radix, Codonopsis Radix, and Ephedrae Herba. They are prone to retro Diels-Adel cleavage and loss of neutral fragments, such as CO, CO₂, which first occurred in the C ring, followed by the A ring. No loss of neutral fragments was observed in the B ring.^[21] The cleavage pattern of flavonoids is represented by compound 52, kaempferol, which had m/z 285.0416 [M-H]⁻ in the negative ion primary mass spectrum. The possible molecular formula based on comprehensive analysis of the elemental composition was C₁₅H₁₀O₆: the parent ion lost CO to form an m/z 257.0864 ion fragment in the high-energy collision of the mass spectrum, followed by loss of C₄H₂O₂ to form an m/z 175.0394 ion fragment, or the parent ion retro Diels-Adel cracked to produce an m/z 151.0032 and an m/z 133.0299 ion fragment. The molecular formula, cleavage rule, and fragment information of the compound were compared with those reported in literature^[22] to confirm that the compound was kaempferol. A possible cleavage pathway is shown in Figure 4.

Figure 4.

Cleavage pathway (A) and the fragment mass spectrometry (B) of kaempferol.

3.1.2. Phenylpropanoids

Phenylpropanoids, including phenylpropionic acid, coumarins, and lignans, are mainly found in the Eucommiae Cortex, Cibotii Rhizoma, Lycii Fructus, and Psoralea Fructus. Coumarins easily lost CO and CO₂ from the lactone ring resulting in fragment ions with mass losses of 28 and 44.^[23] Compound 60, psoralen was analyzed as an example phenylpropanoid. In the positive ion mode, the excimer ion peak at m/z 187.0387 [M+H]⁺ was predicted to be C₁₁H₆O₃ based on a comprehensive analysis of the elemental composition. The parent ion lost CO twice, resulting in fragments with m/z 159.0454 and 131.0488. Another pathway involved the loss of CO₂ and CO to produce m/z 143.0489 and 115.0539 fragments, respectively. Subsequently, combined with fragment information, reference substance and the literature,^[24] the compound was identified to be psoralen, and the cleavage pathway is shown in Figure 5.

Figure 5.

Cleavage pathway (A) and secondary fragment mass spectrometry (B) of psoralen.

3.1.3. Organic acids

Organic acids are the main components of Cibotii Rhizoma, Lycii Fructus, Allii tuberosi Semen, Cuscutae Semen. Small molecules, such as CO₂ and H₂O, are easily lost from organic acids in the mass spectrum, resulting in the fragmentation of ion peaks.^[25] Compound 11, protocatechuic acid was evaluated as an example. The excimer ion [M−H]⁻ was m/z 153.0195 in negative ion mode. The characteristic fragment ions m/z 109.0302 and m/z 91.0207 were generated by removing CO₂ and H₂O from the excimer ions. The compound was inferred to be protocatechuic acid based on comparison with the control product as well as the literature.^[26] The cleavage pathway is shown in Figure 6.

Figure 6.

Cleavage pathway (A) and secondary fragment mass spectrometry (B) of protocatechuic acid.

3.1.4. Alkaloids

Alkaloids are the active ingredients of Ephedrae Herba and Corydalis Rhizoma. Ephedrae Herba mainly contains organic amine alkaloids, while Corydalis Rhizoma mainly contains isoquinoline alkaloids. We evaluated organic amines in this study, after the stable conjugated structure was formed by dehydration, the methyl substituents were gradually lost along the side chain towards the benzene ring, and the compound was further deaminated.^[27] Compound 5, ephedrine, was assessed as an example. Ephedrine had an excimer ion peak of m/z 166.1226 in the positive ion mode, and lost H₂O to form a fragment ion m/z 148.1122. Consequently, m/z 133.0882 and m/z 115.0542 fragment ions were formed by removing methyl and methylamine respectively. The predicted cleavage pathways are shown in Figure 7. Compound 5 was identified as ephedrine in combination with the reference,^[28] control product, and debris information.

Figure 7.

C cleavage pathway (A) and secondary fragment mass spectrometry (B) of ephedrine.

3.1.5. Terpenoids and their glycosides

Terpenes and their glycosides mainly originate from Paeoniae Radix Alba, Eucommiae Cortex and Corni Fructus. Monoterpenes and their glycosides were analyzed, and benzoyl and glucosidating groups were found to be attached to the monoterpene parent nucleus. Benzoic acid is often broken and glucose is lost, or benzoic acid is broken after a molecule of CH₂O is lost.^[29] Compound 29 produced an m/z 525.1625 excimer ion peak in the negative ion mode, and its molecular formula was inferred to be C₂₃H₂₈O₁₁. However, the excimer ion lost CH₂O to become fragment ion m/z 449.1462 in the secondary mass spectrum. Subsequently, it lost the benzoic acid at m/z 121.0297 resulting in the fragment ion m/z 327.1097. Additionally, fragment ion m/z 165.0561 of the pinene skeleton structure was formed by the loss of glucose. Based on comparison with the literature^[30] and reference substances, compound 29 was inferred to be paeoniflorin; its cleavage pathway is shown in Figure 8.

Figure 8.

Cleavage pathway (A) and secondary fragment mass spectrometry (B) of paeoniflorin.

3.2. Network pharmacology analysis

3.2.1. Acquisition of intersecting targets

Based on the UPLC–TOF–MS identification results, 92 components of the Co-DZZY Capsules were obtained, corresponding to 633 targets filtered through the SwissTargetPrediction database. Meanwhile, 970 OP-related targets were obtained from the Gene Cards database. Among them, 101 intersection targets were associated with Co-DZZY Capsules and OP, as shown in Figure 9.

Figure 9.

Intersection targets of compounds and osteoporosis. OP = osteoporosis.

3.2.2. Compound-target–disease network

The cytoscape 3.10.2 software was used to construct a compound-target–disease network of the Co-DZZY Capsules, as shown in Figure 10. Co-DZZY Capsules exert an antiosteoporosis effect by influencing diverse targets, with each component acting on multiple targets, and each target corresponding to various components, reflecting the multi-component synergistic effect of TCM. The greater the number of edges of the active ingredients, the higher are the degree values.

Figure 10.

Construction of the “compound–target–disease” network. Rhomboids represent medicinal herbs, ellipsoids represented components, rectangles represented intersection targets, and triangle represented disease.

3.2.3. PPI network

The PPI of the drug and disease targets was constructed using the STRING database and Cytoscope software, as shown in Figure 11. The PPI network, with 99 nodes and 1155 edges, summarized the interactions with targets related to the therapeutic benefits of Co-DZZY Capsules for OP. Among the 101 intersection targets, glucose-6-phosphate translocase (SLC37A4) and alpha-l-fucosidase I (FUCA1) did not interact with other proteins. The results were ordered by degree using network topology analysis, with darker colors, larger figures, and more lines indicating higher degree values. Threonine-protein kinase (AKT1), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF), peroxisome proliferator-activated receptor gamma (PPARG), signal transducer and activator of transcription 3 (STAT3), and tyrosine-protein kinase (SRC) ranked high on the list and were deemed to be potential key targets.

Figure 11.

PPI network of intersection targets. (A) Important module of PPI created by the STRING database. (B) PPI ordered by degree value, the larger the degree value, the larger the figure and the darker the color. PPI = protein–protein interaction.

3.2.4. GO enrichment and KEGG pathway analysis

GO and KEGG enrichment pathways were analyzed using the DAVID database to further clarify the mechanism of action of Co-DZZY Capsules against OP at the molecular level. GO analysis of the top 10 common targets, including biological processes (BP), cellular components, and molecular functions, is shown in Figure 12. BP were mainly involved in the positive regulation of protein kinases, smooth muscle cell proliferation, cell migration, phosphorylation, extracellular matrix disassembly, and apoptotic processes, as well as in both positive and negative regulation of gene expression. Cellular components were mainly located in the plasma membrane, organelles, caveola, cell surface, and extracellular matrix. Molecular functions were mainly involved in enzyme binding, steroid binding, tyrosine kinase activity, nuclear receptor activity, and heme binding.

Figure 12.

Go enrichment analysis for targets. GO = gene ontology.

Subsequently, KEGG pathway analysis revealed 145 enriched pathways related to tumors, cardiovascular system, endocrine system, and diabetes. Figure 13 shows the 25 most significantly enriched KEGG pathways, which were concentrated in the advanced glycation end product receptor for advanced glycation end products (AGE-RAGE), hypoxia inducible factor-1 (HIF-1), phosphatidylinositol 3-kinase-protein kinase B, TNF, and ras-related protein 1 (Rap1) signaling pathways. The larger the figure, the more genes there are, and the redder the color, the more significant the enrichment.

Figure 13.

KEGG enrichment pathway analysis. KEGG = Kyoto encyclopedia of genes and genomes.

3.2.5. Component–target–pathway network

An interaction network of the top 20 components, targets, and pathways was constructed to directly visualize and explore the potential synergistic effects of the major compounds (Fig. 14). These components acted on targets that were enriched in the KEGG signaling pathways. Based on the degree values of the components in this network and the content analyzed by MS, luteolin, allocryptopine, kaempferol, isobavachin, and albiflorin were identified as potential core components.

Figure 14.

Network of component–target–pathway. Circles represent components, rectangles represented intersection targets, and triangles represented KEGG pathways. KEGG = Kyoto encyclopedia of genes and genomes.

3.2.6. Molecular docking analysis

Molecular docking of the top 6 core targets AKT1, IL6, TNF, PPARG, STAT3, and SRC in the PPI network and their corresponding components was performed using the PyMOL software (Table 1). The results revealed that the binding energy of the 6 core targets to most of the relevant ingredients was <−5 kcal/mol, indicating that the ligand and receptor could bind spontaneously and had good affinity. Among these components, quercetin, β-ecdysterone, astragalin, ursolic acid, and dehydrocorydaline showed the best binding with the key targets respectively; the docking complexes were displayed in Figure 15.

Table 1.

Results of molecular docking.

Key targets	Compounds	Binding energy (kcal/mol)	Key targets	Compounds	Binding energy (kcal/mol)
PPARG	Ursolic acid	−9.4	AKT1	Bavachalcone	−6.4
	Oleanolic acid	−8.6		Isobavachalcone	−6.4
	Bavachinin	−8.6		Luteolin	−6.3
	Isobavachin	−7.7		Kaempferol	−6.1
	Bavachin	−7.7		Quercetin	−6.1
	Linoleic acid	−6.3		Alternariol	−6.1
	Oleic acid	−5.7		Kaempferide	−5.9
	Stearic acid	−5.6		3-Hydroxybakuchiol	−5.5
	Linolenate	−0.7		Bakuchiol	−5.4
SRC	Quercetin	−8.5	IL6	β-Ecdysterone	−7.6
	Alternariol	−8.2		Linolenate	−4.5
	Luteolin	−8.1		Linoleic acid	−4.4
	Kaempferol	−8.0	TNF	Astragalin	−8.4
	Kaempferide	−7.4		β-Ecdysterone	−7.6
	Isobavachin	−7.1	STAT3	Dehydrocorydaline	−6.7
	Allocryptopine	−6.8		Palmatine	−6.7
	Albiflorin	−6.4
	Tetrahydropalmatine	−6.1

AKT1 = threonine-protein kinase, IL-6 = interleukin-6, PPARG = peroxisome proliferator-activated receptor gamma, SRC = tyrosine-protein kinase, STAT3 = signal transducer and activator of transcription 3, TNF = tumor necrosis factor alpha.

Figure 15.

Analysis of binding modes of key targets and active ingredients.

4. Discussion

A total of 92 compounds were identified in the Co-DZZY Capsules by UPLC–Q-TOF–MS, laying the foundation for network pharmacology research. Most flavonoids and alkaloids were detected in the positive ion mode, whereas phenylpropanes, organic acids, and terpenoids were detected in the negative ion mode. Psoralea Corylifolia Linn. had the largest variety of 24 components, which mainly included flavonoids and coumarins with a variety of pharmacological activities, such as anti-inflammatory, antioxidant, antitumor, antiosteoporosis, and immunomodulatory.^[31] Paeonia lactiflora Pall, Codonopsis Radix, Eucommiae Cortex, Cibotium Barometz, Lycii Fructus, Ephedra Herba, Cornus Officinalis all contained >10 ingredients. Kaempferol,^[32] luteolin,^[33] and quercetin^[34] are present in a variety of medicinal materials and exhibit a wide range of activities, including antiosteoporosis effects. The seed herbs, such as Allii Tuberosi Semen and Cuscutae Semen, were mainly composed of fatty acids, which showed low contents owing to their insolubility in water. Asari Radix Et Rhizoma is mainly composed of volatile oils; therefore, only a few species have been detected. Components of Cornu Cervi and Sheep Tibia were not detected, which may be related to their low contents.

The top 6 OP-related targets of Co-DZZY Capsules were AKT1, IL6, TNF, PPARG, STAT3, and SRC. AKT1 is one of the 3 isoforms of serine-threonine kinase AKT, which plays an important role in cell survival and apoptosis.^[35] IL-6 is produced by various cell types within the bone and studies involving knockout mice and human genetic mutations have demonstrated its critical role in maintaining skeletal integrity. Additionally, IL-6 is essential for proper bone formation, maturation, and the remodeling process, ensuring balanced bone metabolism and structural stability.^[36] Meanwhile, TNF disrupts the equilibrium of bone remodeling by enhancing osteoclast-mediated bone resorption, while simultaneously suppressing osteoblast-driven bone formation.^[37] Moreover, studies have demonstrated that genetically reduced low-density lipoprotein cholesterol levels, regulated by PPARG, were strongly linked to higher bone mineral density in both the femoral neck and lumbar spine. This finding highlights the potential role of lipid metabolism in bone health.^[38] Numerous in vivo studies utilizing cell-specific STAT3 transgenic mice have been conducted to explore its role in bone biology. These experiments revealed that STAT3 plays a critical and indispensable role in regulating bone formation and developmental processes.^[39] Consequently, tyrosine kinase SRC-knockout mice display osteopetrosis, demonstrating that SRC is crucial for bone resorption and formation.^[40]

GO enrichment analysis showed that Co-DZZY Capsules were mainly involved in the positive regulation of protein kinase, smooth muscle cell proliferation, cell migration, phosphorylation, and other BP in the disease process, including several BP involving the core targets AKT1, IL6, TNF, PPARG, STAT3, and SRC. The KEGG analysis revealed the involvement of the AGE-RAGE, HIF-1, PI3K-AKT, TNF, and Rap1 signaling pathways, indicating that the chemical components of Co-DZZY Capsules could regulate some of these pathways to treat OP. Wang et al^[41] found that another TCM formula containing Eucommiae Cortex and Psoralea Fructus enhanced osteogenesis by significantly downregulating the genes related to AGE-RAGE signaling pathway, such as RAGE, NOX4, NF-KB P65, AKT1, TNF-α, and IL-6. HIF-1 has 2 subunits, HIF-1α and HIF-1β, the protein level of HIF-1α is responsible for the activity of the HIF-1 signaling pathway. A recent study has shown that total flavonoids in Drynariae Rhizoma notably upregulated HIF-1α protein levels, and enhanced the osteogenic differentiation of bone marrow mesenchymal stem cells while suppressing adipogenic differentiation.^[42] The various flavonoid components of Co-DZZY Capsules may have a similar effect.

The PI3K–AKT signaling pathway plays a critical role in osteogenic and osteoclastic processes, controlling the survival and differentiation of osteoblasts and osteoclasts to ensure bone mass equilibrium and turnover. Ginsenoside Rg1 reportedly improves the protein expression levels of phosphorylated AKT by enhancing the expression levels of G protein-coupled estrogen receptor, subsequently promoting bone formation in zebrafish.^[43] Additionally, TNF is an inflammatory signaling pathway implicated in the development of endocrine system illnesses, particularly OS. Particularly, TNF-a promotes the transcription of inflammatory cytokine mRNA, leading to increased IL-6 production, which can enhance osteoclast formation. Wu et al, found that equol suppresses the TNF pathway by inhibiting the expression of TNF-a and IL-6, thereby reducing inflammation and generation of osteoclasts.^[44] One of the characteristics of OS is the imbalance in bone marrow mesenchymal stem cell differentiation, where adipogenesis is enhanced at the expense of osteogenesis. Suppression of vascular endothelial growth factor A and fibroblast growth factor 2 in adipogenic differentiation indicates that the Rap1 signaling pathway may be crucial for this process.^[45] Therefore, we speculated that relevant drugs may promote osteogenesis by activating the Rap1 pathway and increasing the expression of vascular endothelial growth factor A and fibroblast growth factor 2.

The results of the component–target–pathway network showed that luteolin, allocryptopine, kaempferol, isobavachin, and albiflorin were possible core ingredients of the Co-DZZY Capsules. Chai et al^[46] demonstrated that luteolin enhances mitochondrial function, reduces GSDME-mediated pyroptosis, and supports bone formation by activating the PI3K/AKT signaling pathway. Allocryptopine inhibits the LPS-induced upregulation of IL-6 and TNF-α protein expression levels in a dose-dependent manner;^[47] IL-6 and TNF were identified as targets in multiple signaling pathways of Co-DZZY Capsules. A previous study indicated kaempferol improved bone mineral density and enhanced trabecular microarchitecture in OVX rats, involving NF-κB, PI3K-AKT, and HIF-1 signaling pathways,^[48] Isobavachin significantly stimulating osteoblast proliferation and differentiation.^[49] Additionally, Suh et al investigated the cytoprotective effects of albiflorin in osteoblasts, demonstrating its ability to enhance mitochondrial function in MC3T3-E1 cells by reversing antimycin A-induced oxidative damage.^[50]

Subsequently, molecular docking reflected the interaction between the compounds and the targets to a certain extent, which showed that except for a few complexes, the binding energy of core targets AKT1, IL6, TNF, PPARG, STAT3, and SRC with their corresponding components was <−5.0 kcal/mol, suggesting that the potential active components of Co-DZZY Capsules had good binding activity with key targets. Fu et al^[51] conducted a 100 ns molecular dynamics simulation of AKT1-quercetin to validate the stability of the docking complexes. They reported that the root-mean-square deviation (RMSD) trajectory of the ligand and protein remained stable and within the range of 1.0 to 2.0 Å and 2.5 to 3.5 Å separately, indicating that the ligand could combine stably with the protein. Additionally, Zheng et al^[52] calculated the RMSD to assess the stability of PPARG-ursolic acid; the trajectory reached equilibrium after approximately 50 ns, and the system gradually maintained its stability. In addition, the PPARG-ursolic acid system had a low root-mean-square fluctuation value, suggesting stable backbone conformations and no significant structural disruption upon ligand binding. Moreover, Pan et al^[53] showed that RMSD of the SRC–quercetin complexes tended to be smooth throughout the dynamics. Accordingly, in this study, the binding free energy of SRC–quercetin was calculated to be −34 kcal/mol, by considering 60 to 100 ns trajectories, and the interaction between the ligand and protein was stabilized.

Currently, several network pharmacological studies on traditional Chinese formulas for OP are available. However, most of these studies infer the components through databases, which have certain limitations, and relatively only a few studies analyzed the components using instruments. Notably, in this study, the components of Co-DZZY Capsules were determined using UPLC–Q-TOF–MS, which improved the reliability. In addition, the key targets AKT1, IL-6, and TNF appeared more frequently in the research of similar traditional Chinese formulas; however, PPARG, STAT3, and SRC are less mentioned, which might be related to their components. Therefore, these 3 targets are the uniqueness of Co-DZZY Capsules in treating OP and deserve attention in future research.

Although network pharmacology provides a good basis for the study of traditional Chinese medicine, this study has some limitations. First, network pharmacology relies on a large amount of bioinformatics data and computational models, and the accuracy and reliability of these data directly affect the reliability of the research results. Second, the selection of disease targets is often subjective, and a large number of disease targets may lead to an unbalanced intersection ratio with the drug ingredients. Nevertheless, this study predicts the effects and mechanisms of a TCM through network pharmacology without in vitro and in vivo experimental validation. Although the results are predictive in nature, further studies involving cellular or animal experiments are warranted to verify them.

5. Conclusion

Based on UPLC–Q-TOF–MS, 92 chemical constituents were characterized in the Co-DZZY Capsules. The potential core targets of Co-DZZY Capsules involved in OP treatment were AKT1, IL6, TNF, PPARG, STAT3, and SRC. Additionally, the signaling pathways that may be involved were the AGE-RAGE, HIF-1, PI3K-AKT, TNF, and Rap1 signaling pathways. Moreover, luteolin, allocryptopine, kaempferol, isobavachin, and albiflorin were deemed to have therapeutic effects. These results provide a reference for further experimental research and clinical medication.

Author contributions

Conceptualization: Kaiting Wei, Jie Jiang, Youcheng Xu.

Data curation: Longyuanru Qiu.

Formal analysis: Jie Jiang, Youcheng Xu.

Funding acquisition: Kaiting Wei, Youcheng Xu.

Investigation: Longyuanru Qiu.

Methodology: Jie Jiang.

Project administration: Jianping Zhu.

Software: Longyuanru Qiu, Jie Jiang.

Supervision: Jianping Zhu.

Validation: Longyuanru Qiu.

Visualization: Kaiting Wei, Jianping Zhu.

Writing – original draft: Longyuanru Qiu, Kaiting Wei.

Writing – review & editing: Youcheng Xu, Kaiyuan Lao.