Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Organic Chemistry
  4. Volume 28, Issue 20
  5. Article
Volume 28, Issue 20
  • ISSN: 1385-2728
  • E-ISSN: 1875-5348

Abstract

Joint degeneration is a possible outcome of rheumatoid arthritis, an inflammatory disorder that is chronic, systemic, and progressive. is known to contain many phytoconstituents that have demonstrated therapeutic effects in terms of inflammation. However, the therapeutic actions of are still not fully understood. The present study aims to better understand rheumatoid arthritis and its possible treatments through the identification of relevant targets and mechanisms. A total of 47 common targets were identified for andrographolide, while 38 common targets were found for neoandrographolide. Additionally, 53 common targets were discovered for 5-hydroxy-7-methoxy flavone. Furthermore, a screening process was carried out to identify 9 primary hubb targets for andrographolide, neoandrographolide, and 5-hydroxy-7-methoxy flavone. Twenty useful gene ontology (GO) terms and twenty important Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways were found through the study of gene ontology and pathways. Molecular-docking analysis revealed that andrographolide had the highest binding efficacy (-7.8) towards the Serine/threonine-protein kinase 2 (PIM2) target. On the other hand, neoandrographolide displayed the highest binding efficacy towards mitogen-activated protein kinase (MAPK1) and Interlukine-6 (IL-6), with docking scores of (-9.0) and (-7.2), respectively. Furthermore, 5-hydroxy-7-methoxy flavone showed the highest docking score (-6.6) with Arachidonate 12-lipoxygenase (ALOX-12). The identification of numerous targets linked with various pathways in the treatment of Rheumatoid arthritis proves to be a helpful resource for future investigation into the mechanism and clinical applications of AP, NP, and 5H-flavone.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/coc/10.2174/0113852728301440240620093751
2024-12-01
2025-01-10

  • From This Site

    /content/journals/coc/10.2174/0113852728301440240620093751
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. CoutantF. MiossecP. Evolving concepts of the pathogenesis of rheumatoid arthritis with focus on the early and late stages.Curr. Opin. Rheumatol.2020321576310.1097/BOR.0000000000000664 31644463
     [Google Scholar]
  2. ShenB. ChenH. YangD. YolandaO. YuanC. DuA. XuR. GengY. ChenX. LiH. XuG.Y. A structural equation model of health-related quality of life in chinese patients with rheumatoid arthritis.Front. Psychiatry20211271699610.3389/fpsyt.2021.716996 34421688
     [Google Scholar]
  3. BurmesterG.R. PopeJ.E. Novel treatment strategies in rheumatoid arthritis.Lancet2017389100862338234810.1016/S0140‑6736(17)31491‑5 28612748
     [Google Scholar]
  4. WangF. LiuJ. FangY. WenJ. HeM. LiX. HanQ. Effect of Siegesbeckiae Herba on immune-inflammation of rheumatoid arthritis: Data mining and network pharmacology.Eur. J. Integr. Med.20235910224210.1016/j.eujim.2023.102242
     [Google Scholar]
  5. van der WoudeD. van der Helm-van MilA.H.M. Update on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis.Best Pract. Res. Clin. Rheumatol.201832217418710.1016/j.berh.2018.10.005 30527425
     [Google Scholar]
  6. WangG. XuH. MuR. Management of rheumatoid arthritis in People’s Republic of China focus on tocilizumab and patient considerations.Int. J. Gen. Med.20158818719410.2147/IJGM.S81633 25999757
     [Google Scholar]
  7. De StefanoL. D’OnofrioB. ManzoA. MontecuccoC. BugattiS. The genetic, environmental, and immunopathological complexity of autoantibody-negative rheumatoid arthritis.Int. J. Mol. Sci.202122221238610.3390/ijms222212386 34830268
     [Google Scholar]
  8. PapT. DankbarB. WehmeyerC. Korb-PapA. SherwoodJ. Synovial fibroblasts and articular tissue remodelling: Role and mechanisms.Semin. Cell Dev. Biol.202010114014510.1016/j.semcdb.2019.12.006 31956018
     [Google Scholar]
  9. MuellerA.L. PayandehZ. MohammadkhaniN. MubarakS.M.H. ZakeriA. Alagheband BahramiA. BrockmuellerA. ShakibaeiM. Recent advances in understanding the pathogenesis of rheumatoid arthritis: New treatment strategies.Cells20211011301710.3390/cells10113017 34831240
     [Google Scholar]
  10. ShenP. LinW. DengX. BaX. HanL. ChenZ. QinK. HuangY. TuS. Potential implications of quercetin in autoimmune diseases.Front. Immunol.20211268904410.3389/fimmu.2021.689044 34248976
     [Google Scholar]
  11. FangY. LiuJ. XinL. SunY. WanL. HuangD. WenJ. ZhangY. WangB. Identifying compound effect of drugs on rheumatoid arthritis treatment based on the association rule and a random walking-based model.BioMed Res. Int.2020202011010.1155/2020/4031015 33204694
     [Google Scholar]
  12. TangM. XieX. YiP. KangJ. LiaoJ. LiW. LiF. Integrating network pharmacology with molecular docking to unravel the active compounds and potential mechanism of simiao pill treating rheumatoid arthritis.Evid. Based Complement. Alternat. Med.2020202011610.1155/2020/5786053 33204288
     [Google Scholar]
  13. KishoreV. YarlaN. BishayeeA. PuttaS. MallaR. NeelapuN. ChallaS. DasS. ShiralgiY. HegdeG. DhananjayaB. Multi-targeting andrographolide and its natural analogs as potential therapeutic agents.Curr. Top. Med. Chem.201717884585710.2174/1568026616666160927150452 27697058
     [Google Scholar]
  14. WangY. ChenL. ZhaoF. LiuZ. LiJ. QiuF. Microbial transformation of neoandrographolide by Mucor spinosus (AS 3.2450).J. Mol. Catal., B Enzym.2011681838810.1016/j.molcatb.2010.09.016
     [Google Scholar]
  15. LiZ. TanJ. WangL. LiQ. Andrographolide benefits rheumatoid arthritis via inhibiting MAPK pathways.Inflammation20174051599160510.1007/s10753‑017‑0600‑y 28584977
     [Google Scholar]
  16. LiG. QinY. DuP. Andrographolide inhibits the migration, invasion and matrix metalloproteinase expression of rheumatoid arthritis fibroblast-like synoviocytes via inhibition of HIF-1α signaling.Life Sci.2015136677210.1016/j.lfs.2015.06.019 26141990
     [Google Scholar]
  17. ZhangJ. SunY. ZhongL.Y. YuN.N. OuyangL. FangR.D. WangY. HeQ.Y. Structure-based discovery of neoandrographolide as a novel inhibitor of Rab5 to suppress cancer growth. Comput. Struct. Biotechnol. J.2020183936394610.1016/j.csbj.2020.11.033 33335690
     [Google Scholar]
  18. GongN. DuL. YangL. Neoandrographolide. In: Natural Small Molecule Drugs from Plants.Springer201842743110.1007/978‑981‑10‑8022‑7_71
     [Google Scholar]
  19. LiuJ. WangZ. Effect of neoandrographolide on activated mouse macrophages in vitro.Chin. J. Nat. Med.200535308311
     [Google Scholar]
  20. LiuJ. TangQ. WangZ. Effect of neoandrographolide on respiratory burst of macrophage RAW 264.7 and proliferation of lymphocytes in mice.Chin J New Drugs Clin Remedies2005243206209
     [Google Scholar]
  21. LiuJ. WangZ.T. JiL.L. GeB.X. Inhibitory effects of neoandrographolide on nitric oxide and prostaglandin E2 production in LPS-stimulated murine macrophage.Mol. Cell. Biochem.20072981-2495710.1007/s11010‑006‑9349‑6 17109078
     [Google Scholar]
  22. CushnieT.P.T. LambA.J. Antimicrobial activity of flavonoids.Int. J. Antimicrob. Agents200526534335610.1016/j.ijantimicag.2005.09.002 16323269
     [Google Scholar]
  23. HavsteenB. Flavonoids, a class of natural products of high pharmacological potency.Biochem. Pharmacol.19833271141114810.1016/0006‑2952(83)90262‑9 6342623
     [Google Scholar]
  24. MiddletonE.Jr KandaswamiC. TheoharidesT.C. The effects of plant flavonoids on mammalian cells: Implications for inflammation, heart disease, and cancer.Pharmacol. Rev.2000524673751 11121513
     [Google Scholar]
  25. PancheA.N. DiwanA.D. ChandraS.R. Flavonoids: An overview.J. Nutr. Sci.20165e47e4710.1017/jns.2016.41 28620474
     [Google Scholar]
  26. MalekiS.J. CrespoJ.F. CabanillasB. Anti-inflammatory effects of flavonoids.Food Chem.201929912512410.1016/j.foodchem.2019.125124 31288163
     [Google Scholar]
  27. LiS. ZhangB. Traditional Chinese medicine network pharmacology: Theory, methodology and application.Chin. J. Nat. Med.201311211012010.1016/S1875‑5364(13)60037‑0 23787177
     [Google Scholar]
  28. HopkinsA.L. Network pharmacology: The next paradigm in drug discovery.Nat. Chem. Biol.200841168269010.1038/nchembio.118 18936753
     [Google Scholar]
  29. LuoT. LuY. YanS. XiaoX. RongX. GuoJ. Network pharmacology in research of Chinese medicine formula: Methodology, application and prospective.Chin. J. Integr. Med.2020261728010.1007/s11655‑019‑3064‑0 30941682
     [Google Scholar]
  30. GuoQ. ZhengK. FanD. ZhaoY. LiL. BianY. QiuX. LiuX. ZhangG. MaC. HeX. LuA. Wu-Tou decoction in rheumatoid arthritis: integrating network pharmacology and in vivo pharmacological evaluation.Front. Pharmacol.2017823010.3389/fphar.2017.00230 28515692
     [Google Scholar]
  31. LeeA.Y. ParkW. KangT.W. ChaM.H. ChunJ.M. Network pharmacology-based prediction of active compounds and molecular targets in Yijin-Tang acting on hyperlipidaemia and atherosclerosis.J. Ethnopharmacol.201822115115910.1016/j.jep.2018.04.027 29698773
     [Google Scholar]
  32. XieG. PengW. LiP. XiaZ. ZhongY. HeF. TulakeY. FengD. WangY. XingZ. A network pharmacology analysis to explore the effect of Astragali radix-radix Angelica sinensis on traumatic brain injury.BioMed Res. Int.2018201811310.1155/2018/3951783 30596090
     [Google Scholar]
  33. LiP. ChenJ. ZhangW. LiH. WangW. ChenJ. Network pharmacology based investigation of the effects of herbal ingredients on the immune dysfunction in heart disease.Pharmacol. Res.201914110411310.1016/j.phrs.2018.12.016 30579974
     [Google Scholar]
  34. Zohoorian-AbootorabiT. SaneeH. IranfarH. SaberiM.R. ChamaniJ. Separate and simultaneous binding effects through a non-cooperative behavior between cyclophosphamide hydrochloride and fluoxymesterone upon interaction with human serum albumin: Multi-spectroscopic and molecular modeling approaches.Spectrochim. Acta A Mol. Biomol. Spectrosc.20128817719110.1016/j.saa.2011.12.026 22217702
     [Google Scholar]
  35. GirmeA. ParmarV. JagtapS. SasteG. ModiS.J. HingoraniL. Development and validation of UHPLC-ESI-MS/MS bioanalytical method, ADMET profiling, and pharmacokinetic study of bioactive phytoconstituents from Ayurvedic botanical Guduchi (Tinospora cordifolia). J. Pharmac. Biomed. Analy.Open2023210001810001810.1016/j.jpbao.2023.100018
     [Google Scholar]
  36. UgworE.I. JamesA.S. AmuzatA.I. EzenanduE.O. UgbajaV.C. UgbajaR.N. Network pharmacology-based elucidation of bioactive compounds in propolis and putative underlying mechanisms against type-2 diabetes mellitus.Pharmac. Res. Mod. Chin. Med.2022510018310018310.1016/j.prmcm.2022.100183
     [Google Scholar]
  37. HuQ. FengM. LaiL. PeiJ. Prediction of drug-likeness using deep autoencoder neural networks.Front. Genet.2018958510.3389/fgene.2018.00585 30538725
     [Google Scholar]
  38. ArnottJ.A. PlaneyS.L. The influence of lipophilicity in drug discovery and design.Expert Opin. Drug Discov.201271086387510.1517/17460441.2012.714363 22992175
     [Google Scholar]
  39. WaringM.J. Lipophilicity in drug discovery.Expert Opin. Drug Discov.20105323524810.1517/17460441003605098 22823020
     [Google Scholar]
  40. LipinskiC.A. LombardoF. DominyB.W. FeeneyP.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3-25. 1.Adv. Drug Deliv. Rev.2001461-332610.1016/S0169‑409X(00)00129‑0 11259830
     [Google Scholar]
  41. DainaA. MichielinO. ZoeteV. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.Sci. Rep.2017714271710.1038/srep42717 28256516
     [Google Scholar]
  42. SavjaniK.T. GajjarA.K. SavjaniJ.K. Drug solubility: Importance and enhancement techniques.ISRN Pharm.2012201211010.5402/2012/195727 22830056
     [Google Scholar]
  43. BaellJ.B. HollowayG.A. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays.J. Med. Chem.20105372719274010.1021/jm901137j 20131845
     [Google Scholar]
  44. SzklarczykD. GableA.L. LyonD. JungeA. WyderS. Huerta-CepasJ. SimonovicM. DonchevaN.T. MorrisJ.H. BorkP. JensenL.J. MeringC. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.Nucleic Acids Res.201947D1D607D61310.1093/nar/gky1131 30476243
     [Google Scholar]
  45. XieL. BourneP.E. Functional coverage of the human genome by existing structures, structural genomics targets, and homology models.PLOS Comput. Biol.200513e3110.1371/journal.pcbi.0010031 16118666
     [Google Scholar]
  46. UhlenM. OksvoldP. FagerbergL. LundbergE. JonassonK. ForsbergM. ZwahlenM. KampfC. WesterK. HoberS. WernerusH. BjörlingL. PontenF. Towards a knowledge-based human protein atlas.Nat. Biotechnol.201028121248125010.1038/nbt1210‑1248 21139605
     [Google Scholar]
  47. ApweilerR. BairochA. WuC.H. BarkerW.C. BoeckmannB. FerroS. GasteigerE. HuangH. LopezR. MagraneM. MartinM.J. NataleD.A. O’DonovanC. RedaschiN. YehL.S. UniProt: The universal protein knowledgebase.Nucleic Acids Res.20043290001115D11910.1093/nar/gkh131 14681372
     [Google Scholar]
  48. XiongL.L. TanY. MaH.Y. DaiP. QinY.X. YangR. XuY.Y. DengZ. ZhaoW. XiaQ.J. WangT.H. ZhangY.H. Administration of SB239063, a potent p38 MAPK inhibitor, alleviates acute lung injury induced by intestinal ischemia reperfusion in rats associated with AQP4 downregulation.Int. Immunopharmacol.201638546010.1016/j.intimp.2016.03.036 27236300
     [Google Scholar]
  49. MaL. ZhaoY. WangR. ChenT. LiW. NanY. LiuX. JinF. 3, 5, 4′-Tri-O-acetylresveratrol attenuates lipopolysaccharide-induced acute respiratory distress syndrome via MAPK/SIRT1 pathway.Mediators Inflamm.2015201511210.1155/2015/143074 26648661
     [Google Scholar]
  50. BodeJ.G. EhltingC. HäussingerD. The macrophage response towards LPS and its control through the p38MAPK-STAT3 axis.Cell. Signal.20122461185119410.1016/j.cellsig.2012.01.018 22330073
     [Google Scholar]
  51. LiuW. JiangH. CaiL. YanM. DongS. MaoB. Tanreqing injection attenuates lipopolysaccharide-induced airway inflammation through MAPK/NF-κB signaling pathways in rats model.Evid. Based Complement. Alternat. Med.2016201611510.1155/2016/5292346 27366191
     [Google Scholar]
  52. ChenC.C. LinM.W. LiangC.J. WangS.H. The anti-inflammatory effects and mechanisms of eupafolin in lipopolysaccharide-induced inflammatory responses in RAW264.7 macrophages.PLoS One2016117e015866210.1371/journal.pone.0158662 27414646
     [Google Scholar]
  53. MiossecP. KollsJ.K. Targeting IL-17 and TH17 cells in chronic inflammation.Nat. Rev. Drug Discov.2012111076377610.1038/nrd3794 23023676
     [Google Scholar]
  54. NiuM. ZhaoF. ChenR. LiP. BiL. The transient receptor potential channels in rheumatoid arthritis: Need to pay more attention.Front. Immunol.20231414112727710.3389/fimmu.2023.1127277 36926330
     [Google Scholar]
  55. LiX. XuT. WangY. HuangC. LiJ. Toll-like receptor-4 signaling: A new potential therapeutic pathway for rheumatoid arthritis.Rheumatol. Int.201434111613161410.1007/s00296‑013‑2890‑1 24553677
     [Google Scholar]
  56. NoackM. MiossecP. Selected cytokine pathways in rheumatoid arthritis.Semin. Immunopathol.201739436538310.1007/s00281‑017‑0619‑z 28213794
     [Google Scholar]
  57. ZelováH. HošekJ. TNF-α signalling and inflammation: Interactions between old acquaintances.Inflamm. Res.201362764165110.1007/s00011‑013‑0633‑0 23685857
     [Google Scholar]
  58. McConkeyB.J. SobolevV. EdelmanM. The performance of current methods in ligand-protein docking.Curr. Sci.20025845856Available from: https://www.jstor.org/stable/24107087
    [Google Scholar]
  59. OnonamaduC. IbrahimA. Molecular docking and prediction of ADME/drug-likeness properties of potentially active antidiabetic compounds isolated from aqueous-methanol extracts of Gymnema sylvestre and Combretum micranthum.BioTechnologia 20211021859910.5114/bta.2021.103765 36605715
     [Google Scholar]
  60. AroraM.K. GroverP. AsdaqS.M.B. MehtaL. TomarR. ImranM. PathakA. JangraA. SahooJ. AlamriA.S. AlsanieW.F. AlhomraniM. Potential role of nicotinamide analogues against SARS-COV-2 target proteins.Saudi J. Biol. Sci.202128127567757410.1016/j.sjbs.2021.09.072 34608370
     [Google Scholar]
  61. RoltaR. SalariaD. SharmaP. SharmaB. KumarV. RathiB. VermaM. SourirajanA. BaumlerD.J. DevK. Phytocompounds of Rheum emodi, Thymus serpyllum, and Artemisia annua inhibit spike protein of SARS-CoV-2 binding to ACE2 receptor: In silico approach.Curr. Pharmacol. Rep.20217413514910.1007/s40495‑021‑00259‑4 34306988
     [Google Scholar]
  62. JinD. ZhangJ. ZhangY. AnX. ZhaoS. DuanL. ZhangY. ZhenZ. LianF. TongX. Network pharmacology-based and molecular docking prediction of the active ingredients and mechanism of ZaoRenDiHuang capsules for application in insomnia treatment.Comput. Biol. Med.202113510456210456210.1016/j.compbiomed.2021.104562 34174759
     [Google Scholar]
  63. BardouP. MarietteJ. EscudiéF. DjemielC. KloppC. jvenn: An interactive Venn diagram viewer.BMC Bioinformat.201415117Available from: https://bioinfogp.cnb.csic.es/tools/venny/index.html
    [Google Scholar]
  64. ShannonP. MarkielA. OzierO. BaligaN.S. WangJ.T. RamageD. AminN. SchwikowskiB. IdekerT. Cytoscape: A software environment for integrated models of biomolecular interaction networks.Genome Res.200313112498250410.1101/gr.1239303 14597658
     [Google Scholar]
  65. TrottO. OlsonA.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.J. Comput. Chem.201031245546110.1002/jcc.21334 19499576
     [Google Scholar]
  66. AherR.B. RoyK. Computational approaches as rational decision support systems for discovering next-generation antitubercular agents: Mini-review.Curr. Computeraided Drug Des.201915536938310.2174/1573409915666190130153214 30706823
     [Google Scholar]
/content/journals/coc/10.2174/0113852728301440240620093751
Loading
Unraveling of Potential Targets for Andrographolide, Neoandrographolide and 5-hydroxy, 7-methoxy Flavone in the Treatment of Rheumatoid Arthritis using Network Pharmacology and Molecular Docking
Current Organic Chemistry 28, 1579 (2024); https://doi.org/10.2174/0113852728301440240620093751
/content/journals/coc/10.2174/0113852728301440240620093751
/content/journals/coc/10.2174/0113852728301440240620093751
Loading

Data & Media loading...

Supplements

file format download Download

  • Article Type:     Research Article
Keyword(s): Andrographis paniculata; hubb target; KEGG pathways; molecular-docking; network pharmacology; Rheumatoid arthritis

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test