Evidence-Based Complementary and Alternative Medicine

Evidence-Based Complementary and Alternative Medicine / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 5354215 | https://doi.org/10.1155/2020/5354215

Junmin Chen, Jianyong Chen, Jingrong Lu, "Systematic Elucidation of the Mechanism of Oroxylum indicum via Network Pharmacology", Evidence-Based Complementary and Alternative Medicine, vol. 2020, Article ID 5354215, 8 pages, 2020. https://doi.org/10.1155/2020/5354215

Systematic Elucidation of the Mechanism of Oroxylum indicum via Network Pharmacology

Academic Editor: Orazio Taglialatela-Scafati
Received01 Nov 2019
Accepted19 Jun 2020
Published14 Jul 2020

Abstract

Oroxylum indicum (O. indicum) is an important traditional Chinese medicine that exerts a wide spectrum of pharmacological activities. However, the pharmacological effect of O. indicum and its mechanism of action have not to be systematically elucidated yet. In this study, the druggability for active compounds of O. indicum was assessed via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the potential drug targets of O. indicum were identified using PharmMapper database. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed via WebGestalt. Drug-target-pathway networks were constructed using Cytoscape to give a visual view. Our findings revealed that O. indicum has extremely superb druggability with 41 putative identified target genes. GO, KEGG, and network analyses showed that these targets were associated with inflammatory immunoreactions, cancer, and other biological processes. In summary, O. indicum is predicted to target multiple genes/proteins and pathways that shape a network which can exert systematic pharmacological effects.

1. Introduction

Traditional Chinese medicine (TCM) is the most plentiful source of bioactive compounds or pharmaceutical components for drug development [1]. Oroxylum indicum (O. indicum), for instance, is an important herbal medicine that belongs to the Bignoniaceae family [2] and has been extensively used for centuries in many Asia countries [3]. It is known as Mu Hu Die [4] in China and also found throughout South and Southeast Asian countries such as Japan, Thailand, and India [5, 6]. Oroxylum indicum belongs to the Bignoniaceae family [2] and possesses a wide spectrum of pharmacological effects such as antioxidant [4], antimicrobial [7], antiallergic [8], anti-inflammatory [9], and anticancer [1012] properties.

Attentions have been closely paid to Oroxylum indicum owing to its underlying roles in the prevention and clinical therapy of a wide spectrum of diseases, for instance, cough, asthma, pertussis, pharyngitis, chronic or acute bronchitis, arthritic and rheumatic problems, and tumors [2, 3, 12]. These findings suggest that Oroxylum indicum could be used as a valuable TCM by reason of the incision of complicated pathophysiological processes, identification of therapeutic targets, and discovery of potential molecular functions and involved pathways. However, the possible molecular mechanisms that Oroxylum indicum induces are rarely investigated. Simultaneously, utilization of computational approaches to identify the drug target molecules and uncover the hidden mechanisms is becoming the main current for the sake of saving time, money, and effort. Especially important, computational target identification and the following molecular mechanisms could speed up the progress of drug development.

Therefore, we systematically investigated the pharmacological functions of Oroxylum indicum with the employment of computational approaches. Firstly, the active compounds of Oroxylum indicum were screened and evaluated using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) resource. Next, the potential target genes of those active compounds were predicted by the PharmMapper database. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted with the utilization of the predicted targets. Finally, the drug-targets and targets-pathways pharmacological data of Oroxylum indicum were integrated and further used to construct a three-layer network. An overview of the analytical procedures for Oroxylum indicum target gene identification and mechanism investigation is illustrated in Figure 1(a).

2. Materials and Methods

2.1. Evaluation of Oral Bioavailability and Druglikeness by TCMSP

TCMSP (http://lsp.nwu.edu.cn/tcmsp.php) is a systematic database of pharmacology for natural compounds or TCM [13]. It provides information on the absorption, distribution, metabolism, and excretion (ADME) activities of compounds or TCMs, such as druglikeness (DL), oral bioavailability (OB), and blood-brain barrier (BBB) [14, 15].

Of all the ADME-related properties, DL and OB are the most vital features of administered drugs, due to their roles in evaluating the efficacy of the drug distribution to the circulatory system, and how drug-like a compound is with respect to factors like bioavailability. In the TCMSP database, DL was calculated based on the Tanimoto coefficient and molecular descriptors, while OB was evaluated on OBioavail 1.1 based on an in-house model [13, 14].

In this study, “Oroxylum indicum” was input to TCMSP database, and its pharmacokinetics activities were assessed at the molecular level. Compounds with OB ≥ 40% and DL ≥ 0.2 were screened for further investigation.

2.2. Target Identification via PharmMapper Database

PharmMapper (http://www.lilab-ecust.cn/pharmmapper/) is an online reverse-docking database for potential target identification of small molecules [16]. Given a small molecule in Mol2 or SDF format, it provides the top 300 targets sorted by the normalized fit score in descending order. In the present study, the Mol2 format files of the active compounds identified were downloaded from TCMSP and uploaded individually to the PharmMapper. Only human protein targets were chosen and other arguments were set to default values. The top 10 targets identified of the individual compound were selected for further investigation.

2.3. GeneMANIA Analysis

GeneMANIA (http://www.genemania.org) is an online tool for generating hypotheses concerning gene function, analyzing gene sets, and prioritizing genes for functional assays [17].

Given a query gene list, GeneMANIA can discover functionally similar genes based on curated genomics and proteomics data. After selecting Homo sapiens from the organism option, the target gene list of interest was input to the search box, and the results were further collated.

2.4. Gene Function and Pathway Enrichment Analyses

We employed a Web-based gene set analysis toolkit (WebGestalt, http://www.webgestalt.org/option.php) to systematically investigate the functions and pathway enrichment information on the target genes we predicted [18]. The gene of interest was entered into WebGestalt web server utilizing overrepresentation enrichment analysis (ORA) approach with Gene Oncology [19] and KEGG databases [20, 21] and other default parameters. False discovery rate (FDR) adjusted value less than 0.05 was considered to be significant statistically.

2.5. Network Construction

For comprehensively understanding the complex association among the drug, target gene, and related pathways, we used Cytoscape (v 3.7.2) to build and analyze the drug-targets-pathways networks.

3. Results

3.1. Screening of Active Compounds from TCMSP

TCMSP provides detailed information on vital ADME-related activities such as human oral bioavailability (OB) and druglikeness (DL). The active compounds of Oroxylum indicum were identified based on the ADME-related properties from the TCMSP database, with the threshold OB ≥ 40% and DL ≥ 0.2. 10 active compounds were yielded and finally chosen for further investigation (Figure 1(b) and Table 1).


IDOB (%)DLMolecule name

MOL00100243.060.43Ellagic acid
MOL01210841.160.23Negletein
MOL01305841.520.282,5-Dihydroxy-6,7-dimethoxyflavone
MOL01305953.260.423,7,3′,5′-Tetramethoxy-2-hydrochroxyflavone
MOL00277640.120.75Baicalin
MOL00292841.370.23Oroxylin A
MOL00400446.930.286-OH-Luteolin
MOL00044943.830.76Stigmasterol
MOL00047183.380.24Aloe-emodin
MOL00009846.430.28Quercetin

3.2. Identification of Potential Drug Targets

Potential targets for the 10 active compounds of Oroxylum indicum were identified using PharmMapper [16] with selecting the top 10 targets of individual compound based on the normalized fit score. We obtained their official gene symbol and gene ID from PDB and UniProt and the Gene database of the National Center for Biotechnology Information (NCBI), yielding 41 targets after the removal of duplicates. After the removal of the duplicates, we finally identified 41 unique target genes of the 10 active compounds (Table 2). These 41 identified target genes were utilized for further investigation.


No.Gene IDGene symbolTarget name

15292PIM1Proto-oncogene serine/threonine-protein kinase Pim-1
23055HCKTyrosine-protein kinase HCK
32099ESR1Estrogen receptor
4590BCHECholinesterase
52147F2Prothrombin
65241PGRProgesterone receptor
71956EGFREpidermal growth factor receptor
87276TTRTransthyretin
9760CA2Carbonic anhydrase 2
102629GBAGlucosylceramidase
111646AKR1C2Aldo-keto reductase family 1 member C2
129261MAPKAPK2MAP kinase-activated protein kinase 2
13650BMP2Bone morphogenetic protein 2
14412STSSteryl-sulfatase
15213ALBSerum albumin
164129MAOBAmine oxidase [flavin-containing] B
17336APOA2Apolipoprotein A-II
187068THRBThyroid hormone receptor-beta
19840CASP7Caspase-7
204314MMP3Stromelysin-1
215599MAPK8Mitogen-activated protein kinase 8
225602MAPK10Mitogen-activated protein kinase 10
23759CA1Carbonic anhydrase 1
241017CDK2Cell division protein kinase 2
252950GSTP1Glutathione S-transferase P
265142PDE4BcAMP-specific 3,5-cyclic phosphodiesterase 4B
271675CFDComplement factor D
286256RXRAPeroxisome proliferator-activated receptor-gamma
297376NR1H2Oxysterols receptor LXR-beta
306626SNRPAU1 small nuclear ribonucleoprotein A
312159F10Coagulation factor X
3225824PRDX5Peroxiredoxin-5, mitochondrial
3323173METAP1Methionine aminopeptidase 1
345478PPIAPeptidyl-prolyl cis-trans isomerase A
35283ANGAngiogenin
362100ESR2Estrogen receptor-beta
3723621BACE1Beta-secretase 1
386678SPARCSPARC
397048TGFBR2TGF-beta receptor type-2
405836PYGLGlycogen phosphorylase, liver form
41629CFBComplement factor B

3.3. GeneMANIA Analysis

Among the 41 target genes and their interacting genes, it was uncovered that 40.32% displayed coexpression characteristics, 31.43% had physical interactions, and 12.96% engaged in colocalization. Other results, including shared protein domains, pathway, and genetic interactions, are illustrated in Figure 2.

3.4. GO and KEGG Pathway Analyses

To further understanding the 41 predicted targets, GO and KEGG enrichment analyses were performed via applying WebGestalt. As demonstrated in Figure 3, the top seven functions were metabolic process (40/41), biological regulation (38/41), protein binding (37/41), response to stimulus (33/41), cell communication (27/41), multicellular organismal process (25/41), and membrane-enclosed lumen (25/41). These GO terms were highly relevant to anti-inflammatory activities, particularly for pharyngitis, chronic or acute bronchitis, and other respiratory diseases, As for the pathway analysis, we found the 41 target genes participated in 10 KEGG pathways with significant FDR adjusted value including pathways in cancer, complement and coagulation cascades, and apoptosis (Figure 4).

3.5. Network Analysis

Based on target identification and pathway analysis, an entire drug, targets, and involved pathways network was built via Cytoscape (v 3.7.2). As demonstrated in Figure 5, this three-layer network had 52 nodes and 86 edges. The red oblong, green invert triangles, and blue circles represent drug, target genes, and related pathways, respectively.

4. Discussion

Traditional Chinese medicine (TCM) has been applied extensively to prevent and treat various kinds of diseases owing to its high efficiency, no drug resistance, and low toxicity [22, 23]. Thus, the development of active compounds derived from TCM on the drug design and discovery process should be prioritized urgently [2427]. In silico analyses can improve pharmacokinetic modeling, prediction, as much as toxicity, and metabolic endpoints; all of which streamline and speed up the drug development progress [28, 29].

Identification of target genes is the first step in drug discovery. It has been revealed that more and more active drugs or compounds interact with multiple genes or proteins to exert their pharmacological functions [3033]. Different kinds of in silico target identification approaches have been developed and are widely used towards this end. As shown in Table 2, 41 potential target genes of Oroxylum indicum were identified using computational approaches. GeneMANIA analysis, with information on coexpression, physical interactions, and colocalization, as well as pathway, shared protein domains, and genetic interactions, indicated that these target genes and their interacting genes may have identical or similar functions.

Accordingly, we identified an inflammatory role for Oroxylum indicum in pharyngitis and chronic or acute bronchitis. For example, the majority of the identified targets of Oroxylum indicum were enriched in biological regulation, response to stimulus, cell communication, and so on. These were all essential for Oroxylum indicum to exert its inflammatory role. Similarly, Begum et al. also found Oroxylum indicum plays a vital role in inhibiting inflammation, antiulcerative, enhancing immunity, and lowering blood glucose [6]. These findings coincide closely with our results via GO and KEGG analyses. Furthermore, we discovered that some of the predicted target genes of Oroxylum indicum were associated with cancer, such as EGFR, PIM1, ESR1/2, and MAPK8/10. These genes are closely related to cell proliferation, differentiation, or migration and participant in pathways in cancer, complement and coagulation cascades, apoptosis, signaling pathway, and so on. More importantly, some of these are transcription factors that coregulate several pathways simultaneously, like EGFR and ESR1/2. Consistently, Li et al. have also discovered that O. indicum induces apoptosis via PI3K/Akt/PTEN signaling pathway in liver cancer [12]. These interesting findings may elucidate the potential mechanism of antitumor role that Oroxylum indicum exerts.

The drug-targets network illustrated in Figure 5 also demonstrated that Oroxylum indicum has multiple targets to exert multiple pharmacological effects. Multiple target therapeutic drugs are more effective for the treatment of complex diseases, such as cough, asthma, pertussis, and cancers, and are less vulnerable to drug resistance. Therefore, Oroxylum indicum could be a promising resource that may be used as a lead compound, chemical moiety, or active ingredients for further drug development. Nevertheless, we have to acknowledge that there are some limits and bias in our analyses due to the databases we employed, for example, the release, update date, and resources they used.

5. Conclusion

In short, we would like to emphasize that Oroxylum indicum is a valuable TCM and contains quite promising compounds for the development of an effective and safe multitargeted anti-inflammatory and antitumor medicament. This study provides novel insight into the perspectives and challenges as for the Oroxylum indicum research and clinical application in future investigations.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflicts of interest in this work.

Authors’ Contributions

Junmin Chen and Jianyong Chen contributed equally to this work.

Acknowledgments

This work was financially supported by the grants from Shanghai Natural Science Foundation (no. 17ZR1418100).

References

  1. S. J. Chen and M. C. Cui, “Systematic understanding of the mechanism of salvianolic acid A via computational target fishing,” Molecules, vol. 22, no. 4, 2017. View at: Publisher Site | Google Scholar
  2. K. Lalrinzuali, M. Vabeiryureilai, and G. C. Jagetia, “Investigation of the anti-inflammatory and analgesic activities of ethanol extract of stem bark of sonapatha Oroxylum indicum in vivo,” International Journal of Inflammation, vol. 2016, Article ID 8247014, 8 pages, 2016. View at: Publisher Site | Google Scholar
  3. B. Dinda, I. SilSarma, M. Dinda, and P. Rudrapaul, “Oroxylum indicum (L.) Kurz, an important Asian traditional medicine: from traditional uses to scientific data for its commercial exploitation,” Journal of Ethnopharmacology, vol. 161, pp. 255–278, 2015. View at: Publisher Site | Google Scholar
  4. R.-y. Yan, Y.-y. Cao, C.-y. Chen et al., “Antioxidant flavonoids from the seed of Oroxylum indicum,” Fitoterapia, vol. 82, no. 6, pp. 841–848, 2011. View at: Publisher Site | Google Scholar
  5. P. Sithisarn, P. Nantateerapong, P. Rojsanga, and P. Sithisarn, “Screening for antibacterial and antioxidant activities and phytochemical analysis of Oroxylum indicum fruit extracts,” Molecules, vol. 21, no. 4, p. 446, 2016. View at: Publisher Site | Google Scholar
  6. M. M. Begum, A. Islam, R. Begum et al., “Ethnopharmacological inspections of organic extract of Oroxylum indicum in rat models: a promising natural gift,” Evidence-Based Complementary and Alternative Medicine, vol. 2019, Article ID 1562038, 13 pages, 2019. View at: Publisher Site | Google Scholar
  7. D. S. Moirangthem, N. C. Talukdar, U. Bora, N. Kasoju, and R. K. Das, “Differential effects of Oroxylum indicum bark extracts: antioxidant, antimicrobial, cytotoxic and apoptotic study,” Cytotechnology, vol. 65, no. 1, pp. 83–95, 2013. View at: Publisher Site | Google Scholar
  8. A.-Y. Lee, S. Kang, S.-J. Park, J. Huang, and D.-S. Im, “Anti-allergic effect of oroxylin A from Oroxylum indicum using in vivo and in vitro experiments,” Biomolecules & Therapeutics, vol. 24, no. 3, pp. 283–290, 2016. View at: Publisher Site | Google Scholar
  9. N. Siriwatanametanon, B. L. Fiebich, T. Efferth, J. M. Prieto, and M. Heinrich, “Traditionally used Thai medicinal plants: in vitro anti-inflammatory, anticancer and antioxidant activities,” Journal of Ethnopharmacology, vol. 130, no. 2, pp. 196–207, 2010. View at: Publisher Site | Google Scholar
  10. P. Yang, S. Fu, Z. Cao et al., “Oroxin B selectively induces tumor-suppressive ER stress and concurrently inhibits tumor-adaptive ER stress in B-lymphoma cells for effective anti-lymphoma therapy,” Toxicology and Applied Pharmacology, vol. 288, no. 2, pp. 269–279, 2015. View at: Publisher Site | Google Scholar
  11. M. K. Roy, K. Nakahara, T. V. Na et al., “Baicalein, a flavonoid extracted from a methanolic extract of Oroxylum indicum inhibits proliferation of a cancer cell line in vitro via induction of apoptosis,” Die Pharmazie, vol. 62, no. 2, pp. 149–153, 2007. View at: Google Scholar
  12. N. N. Li, X.-s. Meng, W.-x. Men, Y.-r. Bao, and S. Wang, “Total flavonoids from Oroxylum indicum induce apoptosis via PI3K/akt/PTEN signaling pathway in liver cancer,” Evidence-Based Complementary and Alternative Medicine, vol. 2018, Article ID 3021476, 9 pages, 2018. View at: Publisher Site | Google Scholar
  13. 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
  14. T. Pei, C. Zheng, C. Huang et al., “Systematic understanding the mechanisms of vitiligo pathogenesis and its treatment by Qubaibabuqi formula,” Journal of Ethnopharmacology, vol. 190, pp. 272–287, 2016. View at: Publisher Site | Google Scholar
  15. W. Zhang, Q. Tao, Z. Guo et al., “Systems pharmacology dissection of the integrated treatment for cardiovascular and gastrointestinal disorders by traditional Chinese medicine,” Scientific Reports, vol. 6, no. 1, Article ID 32400, 2016. View at: Publisher Site | Google Scholar
  16. X. Wang, Y. Shen, S. Wang et al., “PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database,” Nucleic Acids Research, vol. 45, no. W1, pp. W356–W360, 2017. View at: Publisher Site | Google Scholar
  17. D. Warde-Farley, S. L. Donaldson, O. Comes et al., “The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function,” Nucleic Acids Research, vol. 38, no. suppl_2, pp. W214–W220, 2010. View at: Publisher Site | Google Scholar
  18. J. Wang, D. Duncan, Z. Shi, and B. Zhang, “WEB-based GEne SeT AnaLysis toolkit (WebGestalt): update 2013,” Nucleic Acids Research, vol. 41, no. W1, pp. W77–W83, 2013. View at: Publisher Site | Google Scholar
  19. C. The Gene Ontology, “Expansion of the gene ontology knowledgebase and resources,” Nucleic Acids Research, vol. 45, no. D1, pp. D331–D338, 2017. View at: Publisher Site | Google Scholar
  20. M. Kanehisa, M. Furumichi, M. Tanabe, Y. Sato, and K. Morishima, “KEGG: new perspectives on genomes, pathways, diseases and drugs,” Nucleic Acids Research, vol. 45, no. D1, pp. D353–D361, 2017. View at: Publisher Site | Google Scholar
  21. M. Kanehisa and S. Goto, “KEGG: kyoto encyclopedia of genes and genomes,” Nucleic Acids Research, vol. 28, no. 1, pp. 27–30, 2000. View at: Publisher Site | Google Scholar
  22. W. Li, Y.-H. Tian, Y. Liu et al., “Platycodin D exerts anti-tumor efficacy in H22 tumor-bearing mice via improving immune function and inducing apoptosis,” The Journal of Toxicological Sciences, vol. 41, no. 3, pp. 417–428, 2016. View at: Publisher Site | Google Scholar
  23. M. J. Hossen, M.-Y. Kim, J.-H. Kim, and J. Y. Cho, “Codonopsis lanceolata: a review of its therapeutic potentials,” Phytotherapy Research, vol. 30, no. 3, pp. 347–356, 2016. View at: Publisher Site | Google Scholar
  24. H. van de Waterbeemd and E. Gifford, “ADMET in silico modelling: towards prediction paradise?” Nature Reviews Drug Discovery, vol. 2, no. 3, pp. 192–204, 2003. View at: Publisher Site | Google Scholar
  25. Y. Kou, Y. Cheun, M. C. Koag, and S. Lee, “Synthesis of 14,15-dehydro-ritterazine Y via reductive and oxidative functionalizations of hecogenin acetate,” Steroids, vol. 78, no. 2, pp. 304–311, 2013. View at: Publisher Site | Google Scholar
  26. Y. Kou, M. C. Koag, Y. Cheun, A. Shin, and S. Lee, “Application of hypoiodite-mediated aminyl radical cyclization to synthesis of solasodine acetate,” Steroids, vol. 77, no. 11, pp. 1069–1074, 2012. View at: Publisher Site | Google Scholar
  27. Y. Kou and S. Lee, “Unexpected opening of steroidal E-ring during hypoiodite-mediated oxidation,” Tetrahedron Letters, vol. 54, no. 31, pp. 4106–4109, 2013. View at: Publisher Site | Google Scholar
  28. Y.-H. Bi, L.-h. Zhang, S.-j. Chen, and Q.-z. Ling, “Antitumor mechanisms of curcumae rhizoma based on network pharmacology,” Evidence-Based Complementary and Alternative Medicine, vol. 2018, Article ID 4509892, 9 pages, 2018. View at: Publisher Site | Google Scholar
  29. Y. C. D. Hu, “Analysis of the action mechanism of Fang Ji Huang Qi decoction in treating rheumatoid arthritis by network pharmacology,” Modernization of Traditional Medicine, vol. 3, no. 6, pp. 286–294, 2018. View at: Google Scholar
  30. M. Schenone, V. Dančík, B. K. Wagner, and P. A. Clemons, “Target identification and mechanism of action in chemical biology and drug discovery,” Nature Chemical Biology, vol. 9, no. 4, pp. 232–240, 2013. View at: Publisher Site | Google Scholar
  31. L. Wang and X.-Q. Xie, “Computational target fishing: what should chemogenomics researchers expect for the future of in silicodrug design and discovery?” Future Medicinal Chemistry, vol. 6, no. 3, pp. 247–249, 2014. View at: Publisher Site | Google Scholar
  32. A. L. Hopkins, “Network pharmacology: the next paradigm in drug discovery,” Nature Chemical Biology, vol. 4, no. 11, pp. 682–690, 2008. View at: Publisher Site | Google Scholar
  33. J. Wang, L. Gao, Y. M. Lee et al., “Target identification of natural and traditional medicines with quantitative chemical proteomics approaches,” Pharmacology & Therapeutics, vol. 162, pp. 10–22, 2016. View at: Publisher Site | Google Scholar

Copyright © 2020 Junmin Chen 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.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views303
Downloads283
Citations

Related articles

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.