Network Pharmacology Integrated with Molecular Docking Explores the Mechanisms of Naringin against Osteoporotic Fracture by Regulating Oxidative Stress

Yu, Xiang; Zhang, Peng; Tang, Kai; Shen, Gengyang; Chen, Honglin; Zhang, Zhida; Zhao, Wenhua; Shang, Qi; Zhu, Guangye; Tan, Riwei; Gan, Yanchi; Zhang, You; Liang, De; Ren, Hui; Jiang, Xiaobing; Zhou, Bengen

doi:https://doi.org/10.1155/2021/6421122

Evidence-Based Complementary and Alternative Medicine

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments Supplementary Materials References Copyright Related Articles

Special Issue

Molecular Approaches Evaluating the Antioxidant Activity of Flavonoids in Health and Disease

View this Special Issue

Research Article | Open Access

Volume 2021 | Article ID 6421122 | https://doi.org/10.1155/2021/6421122

Network Pharmacology Integrated with Molecular Docking Explores the Mechanisms of Naringin against Osteoporotic Fracture by Regulating Oxidative Stress

Xiang Yu,¹Peng Zhang,^2,3Kai Tang,^2,3Gengyang Shen,¹Honglin Chen,^1,2,3Zhida Zhang,^1,3Wenhua Zhao,^2,3Qi Shang,^2,3Guangye Zhu,²Riwei Tan,²Yanchi Gan,²and You Zhang² et al.

Academic Editor: Lucian Hritcu

Received27 Jul 2021

Accepted03 Sept 2021

Published20 Sept 2021

Abstract

Naringin (NG), as the most abundant component of Drynariae Rhizoma (Chinese name: Gusuibu), has been proved to be an antioxidant flavonoid on promoting osteoporotic fracture (OF) healing, but relevant research is scanty on the underlying mechanisms. We adopted target prediction, protein-protein interaction (PPI) analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and molecular docking to establish a system pharmacology database of NG against OF. Totally 105 targets of naringin were obtained, including 26 common targets with OF. A total of 415 entries were obtained through GO Biological Process enrichment analysis (), and 37 entries were obtained through KEGG pathway enrichment analysis with seven signaling pathways included (), which were primarily concerned with p53, IL-17, TNF, estrogen, and PPAR signaling pathways. According to the results of molecular docking, naringin is all bound in the active pockets of the core targets with 3–9 hydrogen bonds through some connections such as hydrophobic interactions, Pi-Pi stacked interactions, and salt bridge, demonstrating that naringin binds tightly to the core targets. In general, naringin may treat OF through multiple targets and multiple pathways via regulating oxidative stress, etc. Notably, it is first reported that NG may regulate osteoclast differentiation and oxidative stress through the expression of the core targets so as to treat OF.

1. Introduction

Osteoporosis (OP) is a bone disease that often results in severe consequences such as fracture [1, 2]. Osteoporotic fracture (OF) is one of the most serious outcomes and clinical endpoints of OP because the lifetime risk of any OF is very high, ranging from 40 to 50 percent for women and 13 to 22 percent for men [3]. In accordance with a Chinese report in 2015, there were about 2.69 million cases of OF happening mainly in the wrists, hips, and vertebral body. OF seriously endangers the life and health of the elderly and increases the burden on families and society. OF is mainly treated using drugs for inhibition of bone resorption in clinics, but the clinical application of these drugs is limited due to some complications for long-term use [4]. Recently, traditional Chinese medicine has been gradually proved to have a functional effect on treating OF, which has attracted increasing attention from more and more scholars [5].

Drynariae Rhizoma (Chinese name: Gusuibu) is widely used to prevent and treat OF and OF-related bone diseases, whose isolated active constituents are composed of flavonoids, phenolic acids, triterpenes, and their glycosides [6]. Among them, flavonoids are the hot spots of current research on the active constituents of Drynariae Rhizoma. It has been reported that total flavonoids of Drynariae Rhizoma can reduce the production of reactive oxygen species (ROS) to alleviate osteoporosis [7]. Naringin (PubChem CID: 442428), the main ingredient of the flavonoids from Drynariae Rhizoma, has the curative effect of treating osteoporosis and promoting fracture healing, so it has a good application prospect in clinics [6]. Current studies have revealed that NG can promote osteoblast proliferation [8]. Moreover, NG can promote osteogenic differentiation and fracture healing by inducing the expression of bone morphogenetic protein-2 (BMP-2) [9]. However, multiple targets and pathways are involved in the process of NG treating OF, and it is hard for traditional pharmacology to carry out systematic analysis about its complex underlying mechanism.

Oxidative stress (OS) is considered to be one of the most critical pathogenic factors of age-related bone loss, which is a primary factor in OF; oxidative stress and bone loss increase with aging, thus leading to OF [10]. Studies have reported that NG has a protective effect against bone loss through relieving oxidative stress [11, 12]. To our knowledge, data on NG treating OF through relieving oxidative stress are scanty, so the correlation between oxidative stress and NG in treating OF is worth further exploring.

For better understanding the potential mechanism of NG treatment on OF, we adopted an integrative strategy of network pharmacology and molecular docking [13], which would provide a profound theoretical basis for NG application in treating OF.

2. Materials and Methods

2.1. Network Pharmacological Data Screening

2.1.1. Naringin-Related Structure and Target Proteins

Naringin-related structure and targets were obtained in 3 steps. Step 1: Data retrieval was performed with the TCMSP database (https://tcmsp-e.com/) [14]. NG was retrieved from the “Chemical name” search box in the TCMSP database to obtain the structure and target information. The advantage of this approach is that the TCMSP database provides a comprehensive study for naringin. Step 2: The structure of naringin was exported as an “SDF” file by retrieving the PubChem database (https://pubchem.ncbi.nlm.nih.gov/), which was input into the SwissTargetPrediction database (http://new.swisstargetprediction.ch/) [15] to obtain the naringin-related targets. Step 3: The target proteins of naringin obtained from the two databases were imported into the UniProt database (http://www.uniprot.org/uniprot/), and the “popular organisms” search field was set to humans, so that target proteins of naringin were obtained, which were referred to as gene symbols.

2.1.2. OF-Related Genes and Corresponding Proteins

Genes of OF were obtained from 2 databases (GeneCards and Online Mendelian Inheritance in Man). GeneCards, a human gene database (https://www.genecards.org/) [16], includes more than 190 data sources about genes, diseases, pathways, and compounds. Online Mendelian Inheritance in Man (OMIM, https://omim.org/) [17] contains information on all known Mendelian disorders and over 15,000 genes. The same key word “Osteoporotic Fracture” was searched in the two databases, and the species was limited to “Homo sapiens.” The proteins corresponding to OF-related genes were standardized using the UniProt database for subsequent analysis.

2.1.3. Intersection Target Proteins (ITPs)

We used R (v3.6.1) software (Statistics Department of the University of Auckland, New Zealand) to take the intersection between OF-related proteins and the target proteins of NG to obtain ITPs.

2.2. Network Pharmacological Data Analysis

2.2.1. Protein-Protein Interaction (PPI) Analysis

To explore the interaction between ITPs, we adopted the STRING database (https://string-db.org/) [18] to obtain the PPI data, which was exported as a .tsv file for further analysis. Next, the PPI information of intersection target proteins was used for the following work by using Cytoscape (v3.7.2) software (Institute for Systems Biology, Seattle, Washington, USA; http://www.cytoscape.org/) [19]. Briefly, the NG-intersection target-OF network was generated. Afterward, we constructed the PPI network of ITPs and performed a network topology analysis by using the Cytoscape plugin NetworkAnalyzer to count the degrees. The target proteins, whose degrees were above average, were considered core target proteins.

2.2.2. GO Enrichment Analysis and KEGG Pathway Analysis

GO and KEGG analyses of the intersection targets were performed using clusterProfiler package (R3.6.1). The enrichment results with were extracted.

2.3. Molecular Docking between Core Targets and Naringin

AutoDock Vina (v1.1.2) software (Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA) [20] was utilized to conduct molecular docking simulations on naringin and its core targets to verify its interaction activity. The 3D structure of naringin was downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). AutoDockTools (v1.5.6; Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA) was used to combine nonpolar hydrogen and distribute charge for naringin, the results of which were converted into a PDBQT file. The crystal structures of proteins were obtained from the RCSB PDB website (http://www.rcsb.org/), and the selection of proteins should satisfy the following three principles: (i) it should be a human protein; (ii) the protein owns one or more eutectic ligands, and the eutectic ligand having higher structural similarity with naringin is preferred; and (iii) the crystal structure with smaller “resolution” value is selected. Molecular docking simulations were not conducted, when the eutectic ligand structure of the protein could not be found in the PDB database or its specific active sites could not be obtained through literature search. We used AutoDockTools to separate the target protein from its ligand, add polar hydrogen and distribute charge, and then output the results to a PDBQT file. AutoDockTools was also used to determine the size and center of the docking box. The specific process of docking is as follows: First, the eutectic ligand of target protein was used to obtain the affinity of the docked protein as the comparison of the docking results of naringin. Then, naringin was successively docked with the target proteins and every affinity was calculated. Finally, the docking results of naringin were plotted and analyzed using PyMOL software (DeLano Scientific Limited Liability Company, South San Francisco, USA).

3. Results

3.1. The Structure and Target Proteins of Naringin

Finally, 105 targets of naringin were obtained from TCMSP and SwissTargetPrediction databases. After input into the UniProt database, target proteins of naringin were obtained, which were referred to as gene symbols. The structure and target information of naringin are shown in Supplementary Tables S1 and S2.

3.2. OF-Related Target Proteins and ITPs

Totally 840 target proteins of OF were retrieved in GeneCards and OMIM databases. After they were mapped with the target proteins of naringin, ITPS were obtained including 26 intersection targets, which are shown in Figure 1(a) and Table 1.

(a)

(b)

(c)

3.3. PPI Network Plotting and Core Target Protein Identification

We input ITPs into the STRING database, hiding the targets with no interactive relationship with others. And then, the data of protein-protein interaction (PPI) were obtained, which was imported into Cytoscape (v 3.7.2) to plot the PPI network in Figure 1(b). There were 11 target proteins whose degrees were higher than the average degree (7.91), which were predicted as the core target proteins (Table 2).

3.4. NG-Intersection Target-OF Network Construction

Figure 1(c) shows the NG-intersection target-OF network, which involved 28 nodes and 52 edges, including one NG node, one OF node, and twenty-six target nodes. In Figure 1(c), the blue diamond nodes represent the intersection target proteins. The red polygon node represents “naringin.” The orange oval node represents “osteoporotic fracture.” The edges represent the corresponding relationship among naringin, osteoporotic fracture, and the intersection targets.

3.5. GO Enrichment Analysis

We obtained 415 items of biological process (BP). Figure 2(a) shows the top 20 items. Notably, we have screened 20 items mainly related to oxidative stress, osteoclast differentiation, and NF-кB signaling regulations, which are shown in Figure 2(b). In addition, 26 interaction targets were imported into Cytoscape (v3.7.2) for GO.BP enrichment analysis. The GO.BP results are mainly related to the following aspects shown in Figure 2(c): (i) inflammation-related activities, such as nuclear receptor activity and extracellular matrix disassembly, which are closely associated with oxidative stress; (ii) cell cycle, such as execution phase of apoptosis; (iii) hormone metabolism, such as estrogen metabolism process; and (iv) lipid metabolism, such as long-chain fatty acid transportation.

(a)

(b)

(c)

(d)

3.6. KEGG Pathway Analysis

The KEGG pathway analysis of 26 target genes was performed using R software. A total of 37 items were obtained, and Table 3 lists 7 key signaling pathways. Cytoscape (v3.7.2) was used for network visualization, as shown in Figure 2(d).

3.7. Molecular Docking Analysis

Among 11 core targets, a total of 8 proteins suitable for molecular docking were obtained after screening, including ESR1, CASP3, ACE, TNF, PPARG, SERPINE1, CYP19A1, and MMP1. To verify how naringin binds to core targets as previously referred, molecular docking using AutoDock Vina was developed in this section. We predicted whether naringin could enter the active pocket of target proteins successfully or not and calculated the affinities between them. The relevant information of the eight proteins and the docking results of eutectic ligands are shown in Supplementary Table S3, and the affinity and hydrogen bond information of naringin with each target protein are shown in Table 4.

As presented in Table 4 and Figure 3(a), the binding affinity of this combination is −7.1 kcal/mol. Naringin was bound with ESR1 by forming 2 hydrogen bonds with Thr-347, while one hydrogen bond with Leu-525. In addition, there are hydrophobic contacts between naringin and Ala-350 and Leu-525.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

As presented in Table 4 and Figure 3(b), the binding affinity of naringin upon CASP3 is −5.4 kcal/mol. The residues including Arg-179, Gln-283, Tyr-338, Arg-341, and Ser-343 interact with naringin by forming 9 hydrogen bonds, which provide a powerful electrostatic force for the combination of naringin and CASP3.

As presented in Table 4 and Figure 3(c), the binding affinity of naringin upon ACE was −9.4 kcal/mol. There were 8 hydrogen bonds provided by Glu-162, Gln-281, His-383, His-513, Lys-449, Lys-454, and Ala-354 residues in the interaction with naringin. Naringin was located in the hydrophobic pocket comprising Glu-376, Val-379, Val-380, and Phe-457 residues. Interestingly, naringin interacts with the His-353 residue by salt bridge.

As presented in Table 4 and Figure 3(d), the binding affinity of naringin upon TNF was −6.5 kcal/mol. There were hydrogen bonds provided by Gly-121, Gly-148, and Gln-149 residues in the interaction with naringin. Naringin was located in the hydrophobic pocket comprising Tyr-59, Gln-61, and Tyr-119 residues. Interestingly, naringin interacts with Tyr-59 and Tyr-151 residues by Pi-Pi stacked interactions.

As presented in Table 4 and Figure 3(e), the binding affinity of naringin upon PPARG was −9.1 kcal/mol. There were 6 hydrogen bonds provided by Ala-278, Ile-281, Gln-286, Ser-289, and Glu-343 residues in the interaction with naringin. Naringin was located in the hydrophobic pocket of PPARG. Interestingly, naringin interacts with the His-449 residue by salt bridge.

As presented in Table 4 and Figure 3(f), the binding affinity of naringin upon SERPINE1 was −7.2 kcal/mol. There were hydrogen bonds provided by Tyr-37, Arg-76, Tyr-79, Asp-95, and Arg-118 residues in the interaction with naringin. Tyr-79, Thr-93, and Arg-118 residues interact with naringin by hydrophobic interaction.

As presented in Table 4 and Figure 3(g), the binding affinity of naringin on CYP19A1 was −9.0 kcal/mol. There were 7 hydrogen bonds provided by Thr-310, Ser-314, Leu-372, Phe-430, Gly-439, and Arg-115 residues in the interaction with naringin. In addition, naringin interacts with the Phe-430 residue by T-type Pi-Pi stacked interaction.

As presented in Table 4 and Figure 3(h), the binding affinity of naringin upon MMP1 was −9.5 kcal/mol. The residues including Asn-180, Leu-181, Glu-219, and Ala-182 interact with naringin by forming 5 hydrogen bonds, which provide a powerful electrostatic force for the combination of naringin and MMP1. Interestingly, naringin interacts with the His-228 residue by salt bridge.

4. Discussion

Chinese traditional medicine Drynariae Rhizoma has been widely applied in treating osteoporosis and osteoporotic fracture clinically for many years. Naringin is one of the most abundant flavonoids in Drynariae Rhizoma, which is also found in citrus fruits and many other Chinese medicines [6]. Studies have revealed that flavonoids have the therapeutic effect on OF by regulating estrogen receptor, OPG/RANK/RANKL, enzyme inhibition, or signal transduction pathways [21, 22].

In this study, there were 26 common targets obtained between NG and OF, among which 11 core targets were identified, namely CASP3, TNF, ESR1, MMP2, MMP1, SERPINE1, IGFBP3, CYP19A1, PPARG, CDKN1A, and ACE. PPI network topology analysis suggested that the targets were mainly characterized by oxidative stress, inflammation, cell cycle, and lipid and hormone metabolism-related proteins. The top three targets in terms of degree are TNF, CASP3, and ESR1, indicating that they may be the key targets of NG in the treatment of OF.

TNF (tumor necrosis factor), known as TNF-α, which is the earliest inflammatory medium produced in oxidative stress response, can promote the generation of inflammatory mediators and induce macrophage colony-stimulating factor (M-CSF) expression [23]. TNF can increase bone absorption and thus influence the healing of OF through activating NF-кB and promoting RANKL-induced osteoclast differentiation [24]. TNF-α can promote oxidative stress and regulate bone homeostasis and bone reconstruction [25, 26]. Moreover, it has been reported that NG could decrease the TNF-α expression [27]. Therefore, we speculated that NG could reduce oxidative stress by downregulating TNF expression in OF patients, so as to anti-OF.

CASP3 (caspase-3) affects the apoptosis of osteoclasts [28]. Some studies have proved that the upregulation of CASP3 mRNA can promote OF healing [29]. Further studies have shown that the upregulation of CASP3 can activate the p53 signaling pathway, destroy the maturation of osteoblasts, and inhibit chondrocyte differentiation, thus promoting fracture healing [30].

ESR1 (estrogen receptor 1) has a close relationship with bone formation [31]. When ESR1 is combined with estrogen, it can up- or downregulate cytokines to affect relevant signaling pathways. ESR1 affects the proliferation, differentiation, and maturation of chondrocytes, regulates the process of endochondral osteogenesis, and maintains chondrocyte phenotype, which promotes the maintenance of cartilage thickness, bone growth balance, and fracture healing [32]. The lack of estrogen results in the acceleration of bone mass loss in postmenopausal women, which could easily give rise to OF [33]. Estrogen exerts physiological activities in cells through ESR1, which are mainly manifested in cell growth, differentiation, senescence, and apoptosis [34]. Guo et al. [35] reported that naringin from Drynariae Rhizoma revealed a double directional adjusting function of estrogenic and antiestrogenic activities. Pang et al. [6] also demonstrated that naringin might mediate ligand-independent activation of ESR1 in osteoblastic cells to protect against ovariectomy-induced bone loss in mice. However, studies are needed to determine whether naringin could prevent and treat OF via exerting estrogen-like protective actions in bone.

MMP2 (matrix metalloproteinase 2) and MMP1 (matrix metalloproteinase 1) are all members of the family of matrix metalloproteinases (MMPs). MMP2 is expressed in the cytoplasm of osteoblasts and some osteoclasts, which can regulate the dissolution of bone matrix, inhibit bone resorption, and contribute to bone reconstruction [36], which promotes fracture healing. MMP1 is closely related to the repair of cartilage tissue. It has been shown that the expression of MMP1 can inhibit the degradation of cartilage matrix and promote the repair of cartilage [37]. Nevertheless, there is no research revealing the regulatory function of NG on MMP2 or MMP1 in OF, which is needed to be further studied in the next step study.

PPARG (peroxisome proliferator-activated receptor gamma), which is related to the regulation of cell differentiation, inflammatory response, and oxidative stress, mainly affects the catabolism of lipids and plays a key role in the process of adipocyte differentiation [38]. It can promote lipid formation and inhibit osteogenesis through different regulatory pathways like PPARγ2 signaling pathway [39, 40]. A study [41] reported that naringin can protect against steroid-induced avascular necrosis of the femoral head (SANFH) through upregulation of PPARγ2 and activation of the Notch signaling pathway in a rabbit model.

CDKN1A (cyclin-dependent kinase inhibitor 1), also known as p21, is a negative regulator of cell cycle that regulates cell proliferation, differentiation, and senescence [42]. The number of osteoblasts is closely related to cell proliferation, and the process of cell proliferation cycle is mainly regulated by cycle-regulating proteins, of which the regulation of G1 phase is the most important [43]. In this process, the combination of cyclin D1 and CDK4 (cyclin-dependent kinase 4) forms the CDK4-cyclin complex to promote the G1 phase [44]. CDKN1A (p21), as a G1 phase regulatory protein, inactivates the CDK4-cyclin complex by binding to it, leading to cell cycle stagnation in the G1 phase [45]. An animal experiment [46] has proved that the expression of p21 in osteoblasts was significantly increased in rats after ovariectomy (). It is also reported that the downregulation of p21 protein expression can promote the proliferation of osteoblasts [45]. Thus, p21 plays a key role in the proliferation of osteoblasts and NG might treat OF by upregulating the p21 expression, which is expected to be demonstrated in the future research.

In addition, CASP2, CASP3, CASP7, and CASP8 in Table 3 are members of the cysteine protease family, which can promote osteoclast apoptosis and thus promote fracture healing [47, 48]. ESR2 is also a receptor of estrogen, which is associated with postmenopausal OF [33].

The results of GO enrichment analysis are similar to those of PPI network analysis. Notably, GO.BP enrichment analysis reveals that the regulation of oxidative stress and osteoclast differentiation play a critical role in NG treating OF, as shown in Figure 2(b). In recent years, relevant reports have confirmed that oxidative stress plays a key role in the pathogenesis of OF [49]. Studies have also revealed that oxidative stress (OS) is one of the important factors that trigger OF [50, 51]. OS is due to the generation of excess reactive oxygen species (ROS), which cannot be cleared by endogenous antioxidants, exceeding the normal physiological threshold and triggering a series of cell toxic reactions, thus further causing tissue damage [52]. Oxidative stress induced by ROS can cause changes in bone homeostasis, increase bone resorption, and decrease bone formation, leading to the occurrence of OF [53]. Some scholars have reported that miR-320a can increase the OS level, reduce osteoblast function, and result in the occurrence of OF [54]. Liu et al. [55] found that the reduction of ROS can increase bone mass and prevent ovariectomized osteoporosis. And some studies have revealed the protective effects of naringin against H2O2-induced inhibition of osteogenic differentiation, which suggests that naringin is a natural antioxidant [56]. Based on our study, naringin may be a promising antioxidant, which would help relieve oxidative stress and ameliorate OF. Moreover, numerous studies have demonstrated that the expression of core targets including TNF [57], CASP3 [58], ESR1 [59], MMP2 [60], MMP1 [61], PPARG [62], CDKN1A [63], ACE [64], etc., plays an important part in regulating oxidative stress. Therefore, we speculated that NG could regulate core targets’ expressions and osteoclast differentiation by oxidative stress in OF patients, so as to anti-OF.

KEGG pathway enrichment analysis demonstrated that p53, IL-17, TNF, estrogen, and PPAR signaling pathways may play a key role in naringin treating OF. Similarly, the results of KEGG analysis are consistent with those of PPI and GO analysis.

Some studies have verified that the activation of p53 signaling pathway can destroy the maturation of osteoblasts and inhibit chondrocyte differentiation [30]. Studies have shown that NG could inhibit inflammation and apoptosis mediated by p53, NF-кB, and TNF pathways [65, 66]. However, whether NG could regulate the p53 signaling pathway to treat OF is still unclear, which needs further identification in the future research.

The IL-17 signaling pathway can stimulate the synthesis of TNF-α, IL-6, and NF-кB, thus promoting osteoclast differentiation induced by RANKL [67]. Moreover, studies have shown that the TNF signaling pathway plays a critical role in the occurrence of postmenopausal OF through promoting the expression of RANKL and inducing osteoclast differentiation [23]. So, IL-17 [68] and TNF signaling pathways [69] have close connection with osteoclast differentiation.

The estrogen signaling pathway can regulate the proliferation, differentiation, and apoptosis of osteoblasts and osteoclasts [70]. It has also been proved that the PPAR pathway can inhibit the lipogenesis of bone marrow, promote the generation of osteoblasts, and improve bone formation and bone mass [40], which promotes fracture healing.

Collectively, the results in our study predicted some pathways and targets that may be potentially therapeutic targets and provide reference for future research on NG treating OF. Nevertheless, a limitation of this study is that further experiments are necessary to demonstrate our findings.

5. Conclusion

In summary, for the first time, our results revealed that naringin may treat OF possibly by regulating numerous signaling pathways and targets related to oxidative stress and osteoclast differentiation. These results will provide a theoretical basis for the treatment of OF. However, these predicted altered signaling pathways or target genes still need to be further verified in the future study.

Data Availability

The data used to support the study’s results came from the first author.

Conflicts of Interest

The authors declare no conflicts of interest.

Authors’ Contributions

All the authors have actively participated in the planning of the work, data gathering and analyzing, and writing the manuscript. All the authors have read and confirmed their participation in the manuscript. The authors Xiang Yu, Peng Zhang, and Kai Tang contributed equally to this work.

Acknowledgments

The project was generously supported by the grants from Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (GDUPS 2018), the National Natural Science Foundation of China (81674000, 81774338, and 81904225), the Medical Research Foundation of Guangdong Province (A2021320 and A2019167), and the Guangdong Provincial Department of Education Project (2018KTSCX041).

Supplementary Materials

Supplementary Table S1: the structure of naringin. Supplementary Table S2: targets of naringin. Supplementary Table S3: target protein information and original ligand docking results. (Supplementary Materials)

References

B. J. Gates and S. Das, “Management of osteoporosis in elderly men,” Maturitas, vol. 69, no. 2, pp. 113–119, 2011.
View at: Publisher Site | Google Scholar
J. E. Compston, M. R. McClung, and W. D. Leslie, “Osteoporosis,” The Lancet, vol. 393, no. 10169, pp. 364–376, 2019.
View at: Publisher Site | Google Scholar
O. Johnell and J. Kanis, “Epidemiology of osteoporotic fractures,” Osteoporosis International, vol. 16, no. Suppl 2, pp. S3–S7, 2005.
View at: Publisher Site | Google Scholar
M. Gambacciani and M. Levancini, “Management of postmenopausal osteoporosis and the prevention of fractures,” Panminerva Medica, vol. 56, no. 2, pp. 115–131, 2014.
View at: Google Scholar
Y.-C. Wang, J.-H. Chiang, H.-C. Hsu, and C.-H. Tsai, “Decreased fracture incidence with traditional Chinese medicine therapy in patients with osteoporosis: a nationwide population-based cohort study,” BMC Complementary and Alternative Medicine, vol. 19, no. 1, p. 42, 2019.
View at: Publisher Site | Google Scholar
W.-Y. Pang, X.-L. Wang, S.-K. Mok et al., “Naringin improves bone properties in ovariectomized mice and exerts oestrogen-like activities in rat osteoblast-like (UMR-106) cells,” British Journal of Pharmacology, vol. 159, no. 8, pp. 1693–1703, 2010.
View at: Publisher Site | Google Scholar
P. Mu, Y. Hu, X. Ma, J. Shi, Z. Zhong, and L. Huang, “Total flavonoids of Rhizoma Drynariae combined with calcium attenuate osteoporosis by reducing reactive oxygen species generation,” Experimental and Therapeutic Medicine, vol. 21, no. 6, p. 618, 2021.
View at: Publisher Site | Google Scholar
N. Li, Y. Jiang, P. H. Wooley, Z. Xu, and S. Y. Yang, “Naringin promotes osteoblast differentiation and effectively reverses ovariectomy-associated osteoporosis,” Journal of Orthopaedic Science: Official Journal of the Japanese Orthopaedic Association, vol. 18, no. 3, pp. 478–485, 2013.
View at: Publisher Site | Google Scholar
X. Zhou, P. Zhang, C. Zhang, and Z. A. Zhu, “Promotion of bone formation by naringin in a titanium particle-induced diabetic murine calvarial osteolysis model,” Journal of Orthopaedic Research, vol. 28, no. 4, pp. 451–456, 2010.
View at: Publisher Site | Google Scholar
Y.-B. Zhang, Z.-M. Zhong, G. Hou, H. Jiang, and J.-T. Chen, “Involvement of oxidative stress in age-related bone loss,” Journal of Surgical Research, vol. 169, no. 1, pp. e37–e42, 2011.
View at: Publisher Site | Google Scholar
O. A. Adebiyi, O. O. Adebiyi, and P. M. O. Owira, “Naringin reduces hyperglycemia-induced cardiac fibrosis by relieving oxidative stress,” PLoS One, vol. 11, no. 3, Article ID e0149890, 2016.
View at: Publisher Site | Google Scholar
C. Li, J. Zhang, F. Lv, X. Ge, and G. Li, “Naringin protects against bone loss in steroid-treated inflammatory bowel disease in a rat model,” Archives of Biochemistry and Biophysics, vol. 650, pp. 22–29, 2018.
View at: Publisher Site | Google Scholar
X. Qi, H. Xu, P. Zhang et al., “Investigating the mechanism of scutellariae barbata herba in the treatment of colorectal cancer by network pharmacology and molecular docking,” Evidence-Based Complementary and Alternative Medicine, vol. 2021, Article ID 3905367, 18 pages, 2021.
View at: Publisher Site | Google Scholar
J. Ru, P. Li, J. Wang et al., “TCMSP: a database of systems pharmacology for drug discovery from herbal medicines,” Journal of Cheminformatics, vol. 6, no. 1, p. 13, 2014.
View at: Publisher Site | Google Scholar
D. Gfeller, A. Grosdidier, M. Wirth, A. Daina, O. Michielin, and V. Zoete, “SwissTargetPrediction: a web server for target prediction of bioactive small molecules,” Nucleic Acids Research, vol. 42, no. W1, pp. W32–W38, 2014.
View at: Publisher Site | Google Scholar
G. Stelzer, N. Rosen, I. Plaschkes et al., “The GeneCards suite: from gene data mining to disease genome sequence analyses,” Current Protocols in Bioinformatics, vol. 54, no. 1, pp. 1–33, 2016.
View at: Publisher Site | Google Scholar
J. S. Amberger and A. Hamosh, “Searching online mendelian inheritance in man (OMIM): a knowledgebase of human genes and genetic phenotypes,” Current Protocols in Bioinformatics, vol. 58, no. 1, pp. 1–12, 2017.
View at: Publisher Site | Google Scholar
C. v. Mering, M. Huynen, D. Jaeggi, S. Schmidt, P. Bork, and B. Snel, “STRING: a database of predicted functional associations between proteins,” Nucleic Acids Research, vol. 31, no. 1, pp. 258–261, 2003.
View at: Publisher Site | Google Scholar
P. Shannon, A. Markiel, O. Ozier et al., “Cytoscape: a software environment for integrated models of biomolecular interaction networks,” Genome Research, vol. 13, no. 11, pp. 2498–2504, 2003.
View at: Publisher Site | Google Scholar
O. Trott and A. J. Olson, “AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading,” Journal of Computational Chemistry, vol. 31, no. 2, pp. 455–461, 2009.
View at: Publisher Site | Google Scholar
D. Choudhary, P. Kushwaha, J. Gautam et al., “Fast and long acting neoflavonoids dalbergin isolated from Dalbergia sissoo heartwood is osteoprotective in ovariectomized model of osteoporosis: osteoprotective effect of Dalbergin,” Biomedicine & Pharmacotherapy, vol. 83, pp. 942–957, 2016.
View at: Publisher Site | Google Scholar
M. Satué, M. d. M. Arriero, M. Monjo, and J. M. Ramis, “Quercitrin and taxifolin stimulate osteoblast differentiation in MC3T3-E1 cells and inhibit osteoclastogenesis in RAW 264.7 cells,” Biochemical Pharmacology, vol. 86, no. 10, pp. 1476–1486, 2013.
View at: Publisher Site | Google Scholar
H. Kitaura, P. Zhou, H. J. Kim, D. V. Novack, F. P. Ross, and S. L. Teitelbaum, “M-CSF mediates TNF-induced inflammatory osteolysis,” Journal of Clinical Investigation, vol. 115, no. 12, pp. 3418–3427, 2005.
View at: Publisher Site | Google Scholar
R. C. Schulman, A. J. Weiss, and J. I. Mechanick, “Nutrition, bone, and aging: an integrative physiology approach,” Current Osteoporosis Reports, vol. 9, no. 4, pp. 184–195, 2011.
View at: Publisher Site | Google Scholar
B. A. Abdel-Wahab and M. E. Metwally, “Clozapine-induced cardiotoxicity: role of oxidative stress, tumour necrosis factor Alpha and NF-κβ,” Cardiovascular Toxicology, vol. 15, no. 4, pp. 355–365, 2015.
View at: Publisher Site | Google Scholar
C. Sang, Y. Zhang, F. Chen et al., “Tumor necrosis factor alpha suppresses osteogenic differentiation of MSCs by inhibiting semaphorin 3B via Wnt/β-catenin signaling in estrogen-deficiency induced osteoporosis,” Bone, vol. 84, pp. 78–87, 2016.
View at: Publisher Site | Google Scholar
O. M. Oladapo, B. Ben-Azu, A. M. Ajayi et al., “Naringin confers protection against psychosocial defeat stress-induced neurobehavioral deficits in mice: involvement of glutamic acid decarboxylase isoform-67, oxido-nitrergic stress, and neuroinflammatory mechanisms,” Journal of Molecular Neuroscience, vol. 71, no. 3, pp. 431–445, 2021.
View at: Publisher Site | Google Scholar
S. A. Lakhani, A. Masud, K. Kuida et al., “Caspases 3 and 7: key mediators of mitochondrial events of apoptosis,” Science, vol. 311, no. 5762, pp. 847–851, 2006.
View at: Publisher Site | Google Scholar
W.-J. Liu, Z.-M. Jiang, Y. Chen et al., “Network pharmacology approach to elucidate possible action mechanisms of Sinomenii Caulis for treating osteoporosis,” Journal of Ethnopharmacology, vol. 257, Article ID 112871, 2020.
View at: Publisher Site | Google Scholar
J. Wu, Y. Yang, Y. He et al., “EFTUD2 gene deficiency disrupts osteoblast maturation and inhibits chondrocyte differentiation via activation of the p53 signaling pathway,” Human Genomics, vol. 13, no. 1, p. 63, 2019.
View at: Publisher Site | Google Scholar
C. Yang, J. Ren, B. Li et al., “Identification of gene biomarkers in patients with postmenopausal osteoporosis,” Molecular Medicine Reports, vol. 19, no. 2, pp. 1065–1073, 2018.
View at: Publisher Site | Google Scholar
M. Liu, W. Xie, W. Zheng, D. Yin, R. Luo, and F. Guo, “[Targeted binding of estradiol with ESR1 promotes proliferation of human chondrocytes in vitro by inhibiting activation of ERK signaling pathway],” Nan Fang Yi Ke Da Xue Xue Bao, vol. 39, no. 2, pp. 134–143, 2021.
View at: Google Scholar
T. Mitek, Ł. Nagraba, J. Deszczyński, M. Stolarczyk, E. Kuchar, and A. Stolarczyk, “Genetic predisposition for osteoporosis and fractures in postmenopausal women,” Advances in Experimental Medicine & Biology, vol. 1211, pp. 17–24, 2019.
View at: Publisher Site | Google Scholar
A. Basudan, N. Priedigkeit, R. J. Hartmaier et al., “Frequent ESR1 and CDK pathway copy-number alterations in metastatic breast cancer,” Molecular Cancer Research, vol. 17, no. 2, pp. 457–468, 2019.
View at: Publisher Site | Google Scholar
D. Guo, J. Wang, X. Wang et al., “Double directional adjusting estrogenic effect of naringin from Rhizoma drynariae (Gusuibu),” Journal of Ethnopharmacology, vol. 138, no. 2, pp. 451–457, 2011.
View at: Publisher Site | Google Scholar
V. Parikka, A. Väänänen, J. Risteli et al., “Human mesenchymal stem cell derived osteoblasts degrade organic bone matrix in vitro by matrix metalloproteinases,” Matrix Biology, vol. 24, no. 6, pp. 438–447, 2005.
View at: Publisher Site | Google Scholar
S.-Y. Sheu, W.-S. Chen, J.-S. Sun, F.-H. Lin, and T. Wu, “Biological characterization of oxidized hyaluronic acid/resveratrol hydrogel for cartilage tissue engineering,” Journal of Biomedical Materials Research Part A, vol. 101, no. 12, pp. 3457–3466, 2013.
View at: Publisher Site | Google Scholar
M. Folwaczny, V. Manolis, C. Markus, and J. Glas, “Variants of the human PPARG locus and the susceptibility to chronic periodontitis,” Innate Immunity, vol. 17, no. 6, pp. 541–547, 2011.
View at: Publisher Site | Google Scholar
M. Herlin, F. E. McGuigan, H. Luthman, and K. Åkesson, “Polymorphisms in inflammation associated genes ALOX15 and IL-6 are associated with bone properties in young women and fracture in elderly,” Bone, vol. 79, pp. 105–109, 2015.
View at: Publisher Site | Google Scholar
J.-H. Kim, D. Y. Jung, A. Nagappan, and M. H. Jung, “Histone H3K9 demethylase JMJD2B induces hepatic steatosis through upregulation of PPARγ2,” Scientific Reports, vol. 8, no. 1, Article ID 13734, 2018.
View at: Publisher Site | Google Scholar
D. Huang, Z. Li, B. Chen et al., “Naringin protects against steroidinduced avascular necrosis of the femoral head through upregulation of PPAR gamma and activation of the Notch signaling pathway,” Molecular Medicine Reports, vol. 17, no. 2, pp. 3328–3335, 2017.
View at: Google Scholar
A. Karimian, Y. Ahmadi, and B. Yousefi, “Multiple functions of p21 in cell cycle, apoptosis and transcriptional regulation after DNA damage,” DNA Repair, vol. 42, pp. 63–71, 2016.
View at: Publisher Site | Google Scholar
S. Dalton, “Linking the cell cycle to cell fate decisions,” Trends in Cell Biology, vol. 25, no. 10, pp. 592–600, 2015.
View at: Publisher Site | Google Scholar
H. Matsushime, M. F. Roussel, R. A. Ashmun, and C. J. Sherr, “Colony-stimulating factor 1 regulates novel cyclins during the G1 phase of the cell cycle,” Cell, vol. 65, no. 4, pp. 701–713, 1991.
View at: Publisher Site | Google Scholar
B. He, L. Dai, X. Zhang et al., “The HDAC inhibitor quisinostat (JNJ-26481585) supresses hepatocellular carcinoma alone and synergistically in combination with sorafenib by G0/G1 phase arrest and apoptosis induction,” International Journal of Biological Sciences, vol. 14, no. 13, pp. 1845–1858, 2018.
View at: Publisher Site | Google Scholar
K. Asano, T. Okawa, I. Matsuoka, Y. Suzuki, and A. Sato, “Effects of sex steroids on expression of adenylyl cyclase messenger RNA in rat uterus,” Journal of Endocrinological Investigation, vol. 28, no. 4, pp. 357–362, 2005.
View at: Publisher Site | Google Scholar
M. Reyes-Becerril, C. Angulo, V. Sanchez, A. Cuesta, and A. Cruz, “Methylmercury, cadmium and arsenic (III)-induced toxicity, oxidative stress and apoptosis in Pacific red snapper leukocytes,” Aquatic Toxicology, vol. 213, Article ID 105223, 2019.
View at: Publisher Site | Google Scholar
N. Tisch, A. Freire-Valls, R. Yerbes et al., “Caspase-8 modulates physiological and pathological angiogenesis during retina development,” Journal of Clinical Investigation, vol. 129, no. 12, pp. 5092–5107, 2019.
View at: Publisher Site | Google Scholar
S. Zhu, W. Wei, Z. Liu, Y. Yang, and H. Jia, “TanshinoneIIA attenuates the deleterious effects of oxidative stress in osteoporosis through the NFkappaB signaling pathway,” Molecular Medicine Reports, vol. 17, no. 5, pp. 6969–6976, 2018.
View at: Google Scholar
J. Kular, J. Tickner, S. M. Chim, and J. Xu, “An overview of the regulation of bone remodelling at the cellular level,” Clinical Biochemistry, vol. 45, no. 12, pp. 863–873, 2012.
View at: Publisher Site | Google Scholar
V. Domazetovic, G. Marcucci, T. Iantomasi, M. L. Brandi, and M. T. Vincenzini, “Oxidative stress in bone remodeling: role of antioxidants,” Clinical Cases in Mineral and Bone Metabolism, vol. 14, no. 2, pp. 209–216, 2017.
View at: Publisher Site | Google Scholar
R. Li, Z. Jia, and M. A. Trush, “Defining ROS in Biology and medicine,” Reactive Oxygen Species (Apex, N.C.), vol. 1, no. 1, pp. 9–21, 2016.
View at: Publisher Site | Google Scholar
Y. Zhang, Y. Jiang, Y. Luo, and Y. Zeng, “Interference of miR-212 and miR-384 promotes osteogenic differentiation via targeting RUNX2 in osteoporosis,” Experimental and Molecular Pathology, vol. 113, Article ID 104366, 2020.
View at: Publisher Site | Google Scholar
L. De-Ugarte, S. Balcells, X. Nogues, D. Grinberg, A. Diez-Perez, and N. Garcia-Giralt, “Pro-osteoporotic miR-320a impairs osteoblast function and induces oxidative stress,” PLoS One, vol. 13, no. 11, Article ID e0208131, 2018.
View at: Publisher Site | Google Scholar
Y. Liu, C. Wang, G. Wang et al., “Loureirin B suppresses RANKL-induced osteoclastogenesis and ovariectomized osteoporosis via attenuating NFATc1 and ROS activities,” Theranostics, vol. 9, no. 16, pp. 4648–4662, 2019.
View at: Publisher Site | Google Scholar
L. Wang, Y.-G. Zhang, X.-M. Wang, L.-F. Ma, and Y.-M. Zhang, “Naringin protects human adipose-derived mesenchymal stem cells against hydrogen peroxide-induced inhibition of osteogenic differentiation,” Chemico-Biological Interactions, vol. 242, pp. 255–261, 2015.
View at: Publisher Site | Google Scholar
T. H. Khan, M. A. Ganaie, K. M. Alharthy, H. Madkhali, B. L. Jan, and I. A. Sheikh, “Naringenin prevents doxorubicin-induced toxicity in kidney tissues by regulating the oxidative and inflammatory insult in Wistar rats,” Archives of Physiology and Biochemistry, vol. 126, no. 4, pp. 300–307, 2020.
View at: Publisher Site | Google Scholar
P. M. Costa, C. Miguel, S. Caeiro et al., “Transcriptomic analyses in a benthic fish exposed to contaminated estuarine sediments through laboratory and in situ bioassays,” Ecotoxicology, vol. 20, no. 8, pp. 1749–1764, 2011.
View at: Publisher Site | Google Scholar
P. Fan, O. L. Griffith, F. A. Agboke et al., “c-Src modulates estrogen-induced stress and apoptosis in estrogen-deprived breast cancer cells,” Cancer Research, vol. 73, no. 14, pp. 4510–4520, 2013.
View at: Publisher Site | Google Scholar
D. A. Siwik, P. J. Pagano, and W. S. Colucci, “Oxidative stress regulates collagen synthesis and matrix metalloproteinase activity in cardiac fibroblasts,” American Journal of Physiology-Cell Physiology, vol. 280, no. 1, pp. C53–C60, 2001.
View at: Publisher Site | Google Scholar
E. J. Nam, G. Yoo, J. Y. Lee et al., “Glycosyl flavones from Humulus japonicus suppress MMP-1 production via decreasing oxidative stress in UVB irradiated human dermal fibroblasts,” BMB Reports, vol. 53, no. 7, pp. 379–384, 2020.
View at: Publisher Site | Google Scholar
L. Liu, T. Zheng, F. Wang et al., “Pro12Ala polymorphism in the PPARG gene contributes to the development of diabetic nephropathy in Chinese type 2 diabetic patients,” Diabetes Care, vol. 33, no. 1, pp. 144–149, 2010.
View at: Publisher Site | Google Scholar
C. Giovannini, P. Chieco, A. Bertaccini, L. Gramantieri, M. Lacchini, and G. Martorana, “Checkpoint effectors CDKN1A and Gadd45 correlate with oxidative DNA damage in human prostate carcinoma,” Anticancer Research, vol. 24, no. 6, pp. 3955–3960, 2004.
View at: Google Scholar
S. Zahler, C. Kupatt, J. Möbert, B. F. Becker, and E. Gerlach, “Effects of ACE-inhibition on redox status and expression of P-selectin of endothelial cells subjected to oxidative stress,” Journal of Molecular and Cellular Cardiology, vol. 29, no. 11, pp. 2953–2960, 1997.
View at: Publisher Site | Google Scholar
Y. Chtourou, B. Aouey, S. Aroui, M. Kebieche, and H. Fetoui, “Anti-apoptotic and anti-inflammatory effects of naringin on cisplatin-induced renal injury in the rat,” Chemico-Biological Interactions, vol. 243, pp. 1–9, 2016.
View at: Publisher Site | Google Scholar
Y. Chtourou, B. Aouey, M. Kebieche, and H. Fetoui, “Protective role of naringin against cisplatin induced oxidative stress, inflammatory response and apoptosis in rat striatum via suppressing ROS-mediated NF-κB and P53 signaling pathways,” Chemico-Biological Interactions, vol. 239, pp. 76–86, 2015.
View at: Publisher Site | Google Scholar
Y. Wang, J. Xu, X. Zhang et al., “TNF-α-induced LRG1 promotes angiogenesis and mesenchymal stem cell migration in the subchondral bone during osteoarthritis,” Cell Death & Disease, vol. 8, no. 3, Article ID e2715, 2017.
View at: Publisher Site | Google Scholar
D. Daoussis, A. P. Andonopoulos, and S.-N. C. Liossis, “Wnt pathway and IL-17: novel regulators of joint remodeling in rheumatic diseases. Looking beyond the RANK-RANKL-OPG axis,” Seminars in Arthritis and Rheumatism, vol. 39, no. 5, pp. 369–383, 2010.
View at: Publisher Site | Google Scholar
M. P. Whyte, “Paget’s disease of bone and genetic disorders of RANKL/OPG/RANK/NF-B signaling,” Annals of the New York Academy of Sciences, vol. 1068, no. 1, pp. 143–164, 2006.
View at: Publisher Site | Google Scholar
R. Y. Kim, H. J. Yang, Y. M. Song, I. S. Kim, and S. J. Hwang, “Estrogen modulates bone morphogenetic protein-induced sclerostin expression through the wnt signaling pathway,” Tissue Engineering. Part A, vol. 21, no. 13-14, pp. 2076–2088, 2015.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2021 Xiang Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

791

Downloads

767

Citations