Research Article

利用周氏五步法揭示双肾平肺散对特发性肺纤维化的活性成分及作用机理

卷 20, 期 3, 2020

页: [220 - 230] 页: 11

弟呕挨: 10.2174/1566524019666191011160543

价格: $65

摘要

背景:双肾平肺散(SPS)是经典配方仁深平肺散的衍生物,用于治疗特发性肺纤维化(IPF)。 方法:在这项研究中,执行了Chou的5个步骤的规则,以探讨SPS对IPF的潜在活性化合物和机理。建立并分析了复合物靶标网络,靶标通路网络,草药靶标网络和核心基因靶标相互作用网络。获得了总共296种化合物和69种SPS候选治疗靶标治疗IPF。网络分析表明,主要的活性化合物是类黄酮(如芹菜素,槲皮素,柚皮素,木犀草素),其他簇(如人参皂苷Rh2,薯os皂甙元,丹参酮IIa),它们也可能起重要作用。 SPS调节了多个IPF相对基因,这些基因影响纤维化(PTGS2,KDR,FGFR1,TGFB,VEGFA,MMP2 / 9)和炎症(PPARG,TNF,IL13,IL4,IL1B等)。 结论:总之,SPS的抗肺纤维化作用可能与炎症的调节和促纤维化信号通路有关。这些发现表明,SPS对IPF的潜在活性化合物和作用机理有待进一步研究。

关键词: 双神平肺散,特发性肺纤维化,周氏五步法则,活性成分,抗纤维化机制。

[1]
Lederer DJ, Martinez FJ. Idiopathic pulmonary fibrosis. N Engl J Med 2018; 378(19): 1811-23.
[http://dx.doi.org/10.1056/NEJMra1705751] [PMID: 29742380]
[2]
Kim HJ, Perlman D, Tomic R. Natural history of idiopathic pulmonary fibrosis. Respir Med 2015; 109(6): 661-70.
[http://dx.doi.org/10.1016/j.rmed.2015.02.002] [PMID: 25727856]
[3]
Raghu G, Chen SY, Yeh WS, et al. Idiopathic pulmonary fibrosis in US Medicare beneficiaries aged 65 years and older: incidence, prevalence, and survival, 2001-11. Lancet Respir Med 2014; 2(7): 566-72.
[http://dx.doi.org/10.1016/S2213-2600(14)70101-8] [PMID: 24875841]
[4]
Vancheri C, Failla M, Crimi N, Raghu G. Idiopathic pulmonary fibrosis: a disease with similarities and links to cancer biology. Eur Respir J 2010; 35(3): 496-504.
[http://dx.doi.org/10.1183/09031936.00077309] [PMID: 20190329]
[5]
Barratt SL, Creamer A, Hayton C, Chaudhuri N. Idiopathic Pulmonary Fibrosis (IPF): An Overview. J Clin Med 2018; 7(8): 201.
[http://dx.doi.org/10.3390/jcm7080201] [PMID: 30082599]
[6]
Lunardi F, Pezzuto F, Vuljan SE, Calabrese F. Idiopathic pulmonary fibrosis and antifibrotic treatments: focus on experimental studies. Arch Pathol Lab Med 2018; 142(9): 1090-7.
[http://dx.doi.org/10.5858/arpa.2018-0080-RA] [PMID: 30141997]
[7]
Mirzaei H, Sahebkar A, Sichani LS, et al. Therapeutic application of multipotent stem cells. J Cell Physiol 2018; 233(4): 2815-23.
[http://dx.doi.org/10.1002/jcp.25990] [PMID: 28475219]
[8]
Hu Y, Li M, Zhang M, Jin Y. Inhalation treatment of idiopathic pulmonary fibrosis with curcumin large porous microparticles. Int J Pharm 2018; 551(1-2): 212-22.
[http://dx.doi.org/10.1016/j.ijpharm.2018.09.031] [PMID: 30227240]
[9]
Smith MR, Gangireddy SR, Narala VR, et al. Curcumin inhibits fibrosis-related effects in IPF fibroblasts and in mice following bleomycin-induced lung injury. Am J Physiol Lung Cell Mol Physiol 2010; 298(5): L616-25.
[http://dx.doi.org/10.1152/ajplung.00002.2009] [PMID: 20061443]
[10]
Aliomrani M, Sepand MR, Mirzaei HR, Kazemi AR, Nekonam S, Sabzevari O. Effects of phloretin on oxidative and inflammatory reaction in rat model of cecal ligation and puncture induced sepsis. Daru 2016; 24(1): 15.
[http://dx.doi.org/10.1186/s40199-016-0154-9] [PMID: 27150961]
[11]
Richeldi L, du Bois RM, Raghu G, et al. INPULSIS Trial Investigators. Efficacy and safety of nintedanib in idiopathic pulmonary fibrosis. N Engl J Med 2014; 370(22): 2071-82.
[http://dx.doi.org/10.1056/NEJMoa1402584] [PMID: 24836310]
[12]
Noble PW, Albera C, Bradford WZ, et al. Pirfenidone for idiopathic pulmonary fibrosis: analysis of pooled data from three multinational phase 3 trials. Eur Respir J 2016; 47(1): 243-53.
[http://dx.doi.org/10.1183/13993003.00026-2015] [PMID: 26647432]
[13]
Hayton C, Chaudhuri N. Managing idiopathic pulmonary fibrosis: which drug for which patient? Drugs Aging 2017; 34(9): 647-53.
[http://dx.doi.org/10.1007/s40266-017-0488-0] [PMID: 28861727]
[14]
Chen F, Wang PL, Fan XS, Yu JH, Zhu Y, Zhu ZH. Effect of Renshen Pingfei Decoction, a traditional Chinese prescription, on IPF induced by Bleomycin in rats and regulation of TGF-β1/Smad3. J Ethnopharmacol 2016; 186: 289-97.
[http://dx.doi.org/10.1016/j.jep.2016.03.051] [PMID: 27013092]
[15]
Xu K, Xu HQ, Fan XS, et al. The effect and mechanism of renshen pingfei prescription in the pulmonary fibrosis model induced by silica in rats. Nanjing zhongyiyao daxue xuebao 2017; 33(01): 49-53.
[16]
Oxenoid K, Dong Y, Cao C, et al. Architecture of the mitochondrial calcium uniporter. Nature 2016; 533(7602): 269-73.
[http://dx.doi.org/10.1038/nature17656] [PMID: 27135929]
[17]
Dev J, Park D, Fu Q, et al. Structural basis for membrane anchoring of HIV-1 envelope spike. Science 2016; 353(6295): 172-5.
[http://dx.doi.org/10.1126/science.aaf7066] [PMID: 27338706]
[18]
Chou KC, Tomasselli AG, Heinrikson RL. Prediction of the tertiary structure of a caspase-9/inhibitor complex. FEBS Lett 2000; 470(3): 249-56.
[http://dx.doi.org/10.1016/S0014-5793(00)01333-8] [PMID: 10745077]
[19]
Chou KC, Howe WJ. Prediction of the tertiary structure of the beta-secretase zymogen. Biochem Biophys Res Commun 2002; 292(3): 702-8.
[http://dx.doi.org/10.1006/bbrc.2002.6686] [PMID: 11922623]
[20]
Ma Y, Wang SQ, Xu WR, Wang RL, Chou KC. Design novel dual agonists for treating type-2 diabetes by targeting peroxisome proliferator-activated receptors with core hopping approach. PLoS One 2012; 7(6): e38546
[http://dx.doi.org/10.1371/journal.pone.0038546] [PMID: 22685582]
[21]
Du X, Diao Y, Liu H, Li S. MsDBP: exploring DNA-binding proteins by integrating multiscale sequence information via chou’s five-step rule. J Proteome Res 2019; 18(8): 3119-32.
[http://dx.doi.org/10.1021/acs.jproteome.9b00226] [PMID: 31267738]
[22]
Ju Z, Wang SY. Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5- steps rule and general pseudo components. Genomics 2019; S0888-7543(19): 30219-8.
[23]
Le NQK, Yapp EKY, Ou YY, Yeh HY. iMotor-CNN: Identifying molecular functions of cytoskeleton motor proteins using 2D convolutional neural network via Chou’s 5-step rule. Anal Biochem 2019; 575: 17-26.
[http://dx.doi.org/10.1016/j.ab.2019.03.017] [PMID: 30930199]
[24]
Liang Y, Zhang S. Identifying DNase I hypersensitive sites using multi-features fusion and F-score features selection via Chou’s 5-steps rule. Biophys Chem 2019; 253: 106227
[http://dx.doi.org/10.1016/j.bpc.2019.106227] [PMID: 31325710]
[25]
Tahir M, Tayara H, Chong KT. iDNA6mA (5-step rule): Identification of DNA N6-methyladenine sites in the rice genome by intelligent computational model via Chou’s 5-step rule. CHEMOLAB 2019; 189: 96-101.
[http://dx.doi.org/10.1016/j.chemolab.2019.04.007]
[26]
Chou KC. Impacts of bioinformatics to medicinal chemistry. Med Chem 2015; 11(3): 218-34.
[http://dx.doi.org/10.2174/1573406411666141229162834] [PMID: 25548930]
[27]
Chou KC. Some remarks on protein attribute prediction and pseudo amino acid composition. J Theor Biol 2011; 273(1): 236-47.
[http://dx.doi.org/10.1016/j.jtbi.2010.12.024] [PMID: 21168420]
[28]
Ru J, Li P, Wang J, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 2014; 6: 13.
[http://dx.doi.org/10.1186/1758-2946-6-13] [PMID: 24735618]
[29]
Xue R, Fang Z, Zhang M, Yi Z, Wen C, Shi T. TCMID: Traditional Chinese Medicine integrative database for herb molecular mechanism analysis. Nucleic Acids Res 2013; 41(Database issue): D1089-95.
[PMID: 23203875]
[30]
Wishart DS, Feunang YD, Guo AC, et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 2018; 46(D1): D1074-82.
[http://dx.doi.org/10.1093/nar/gkx1037] [PMID: 29126136]
[31]
Gong J, Cai C, Liu X, et al. ChemMapper: a versatile web server for exploring pharmacology and chemical structure association based on molecular 3D similarity method. Bioinformatics 2013; 29(14): 1827-9.
[http://dx.doi.org/10.1093/bioinformatics/btt270] [PMID: 23712658]
[32]
Dunkel M, Günther S, Ahmed J, Wittig B, Preissner R. SuperPred: drug classification and target prediction. Nucleic Acids Res 2008; 36(Web Server issue): W55-9.
[PMID: 18499712]
[33]
Liu Z, Guo F, Wang Y, et al. BATMAN-TCM: a bioinformatics analysis tool for molecular mechanism of traditional chinese medicine. Sci Rep 2016; 6: 21146.
[http://dx.doi.org/10.1038/srep21146] [PMID: 26879404]
[34]
Wang X, Shen Y, Wang S, et al. PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database. Nucleic Acids Res 2017; 45(W1): W356-60
[http://dx.doi.org/10.1093/nar/gkx374] [PMID: 28472422]
[35]
Yang H, Qin C, Li YH, et al. Therapeutic target database update 2016: enriched resource for bench to clinical drug target and targeted pathway information. Nucleic Acids Res 2016; 44(D1): D1069-74.
[http://dx.doi.org/10.1093/nar/gkv1230] [PMID: 26578601]
[36]
Davis AP, Grondin CJ, Johnson RJ, et al. The comparative toxicogenomics database: update 2017. Nucleic Acids Res 2017; 45(D1): D972-8.
[http://dx.doi.org/10.1093/nar/gkw838] [PMID: 27651457]
[37]
UniProt Consortium T. UniProt. the universal protein knowledgebase. Nucleic Acids Res 2018; 46(5): 2699.
[http://dx.doi.org/10.1093/nar/gky092] [PMID: 29425356]
[38]
Xie C, Mao X, Huang J, et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res 2011; 39(Web Server issue): W316-22.
[http://dx.doi.org/10.1093/nar/gkr483] [PMID: 21715386]
[39]
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28(1): 27-30.
[http://dx.doi.org/10.1093/nar/28.1.27] [PMID: 10592173]
[40]
Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 2017; 45(D1): D362-8.
[http://dx.doi.org/10.1093/nar/gkw937] [PMID: 27924014]
[41]
Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 2011; 27(3): 431-2.
[http://dx.doi.org/10.1093/bioinformatics/btq675] [PMID: 21149340]
[42]
Nagini S. Carcinoma of the stomach: A review of epidemiology, pathogenesis, molecular genetics and chemoprevention. World J Gastrointest Oncol 2012; 4(7): 156-69.
[http://dx.doi.org/10.4251/wjgo.v4.i7.156] [PMID: 22844547]
[43]
Martinez FJ, Collard HR, Pardo A, et al. Idiopathic pulmonary fibrosis. Nat Rev Dis Primers 2017; 3: 17074.
[http://dx.doi.org/10.1038/nrdp.2017.74] [PMID: 29052582]
[44]
Selman M, Pardo A. Revealing the pathogenic and aging-related mechanisms of the enigmatic idiopathic pulmonary fibrosis. an integral model. Am J Respir Crit Care Med 2014; 189(10): 1161-72.
[http://dx.doi.org/10.1164/rccm.201312-2221PP] [PMID: 24641682]
[45]
Davoodvandi A, Sahebnasagh R, Mardanshah O, et al. Medicinal plants as natural polarizers of macrophages: phytochemicals and pharmacological effects. Curr Pharm Des 2019; 25: 3225-38.
[http://dx.doi.org/10.2174/1381612825666190829154934] [PMID: 31465276]
[46]
Trawinska MA, Rupesinghe RD, Hart SP. Patient considerations and drug selection in the treatment of idiopathic pulmonary fibrosis. Ther Clin Risk Manag 2016; 12: 563-74.
[PMID: 27114711]
[47]
King CS, Nathan SD. POINT: Should all patients with idiopathic pulmonary fibrosis, even those with more than moderate impairment, be treated with nintedanib or pirfenidone? Yes Chest 2016; 150(2): 273-5.
[http://dx.doi.org/10.1016/j.chest.2016.04.034] [PMID: 27292047]
[48]
Corte T, Bonella F, Crestani B, et al. Safety, tolerability and appropriate use of nintedanib in idiopathic pulmonary fibrosis. Respir Res 2015; 16: 116.
[http://dx.doi.org/10.1186/s12931-015-0276-5] [PMID: 26400368]
[49]
Zhang J, Chao L, Liu X, et al. The potential application of strategic released apigenin from polymeric carrier in pulmonary fibrosis. Exp Lung Res 2017; 43(9-10): 359-69.
[http://dx.doi.org/10.1080/01902148.2017.1380086] [PMID: 29206498]
[50]
Li LC, Kan LD. Traditional Chinese medicine for pulmonary fibrosis therapy: Progress and future prospects. J Ethnopharmacol 2017; 198: 45-63.
[http://dx.doi.org/10.1016/j.jep.2016.12.042] [PMID: 28038955]
[51]
Sellarés J, Rojas M. Quercetin in Idiopathic Pulmonary Fibrosis: Another Brick in the Senolytic Wall. Am J Respir Cell Mol Biol 2018. [Epub ahead of print
[PMID: 30211613]
[52]
Lin Y, Tan D, Kan Q, Xiao Z, Jiang Z. The Protective Effect of Naringenin on Airway Remodeling after Mycoplasma Pneumoniae Infection by Inhibiting Autophagy-Mediated Lung Inflammation and Fibrosis. Mediators Inflamm 2018; 2018 8753894
[http://dx.doi.org/10.1155/2018/8753894] [PMID: 29849498]
[53]
Du G, Jin L, Han X, Song Z, Zhang H, Liang W. Naringenin: a potential immunomodulator for inhibiting lung fibrosis and metastasis. Cancer Res 2009; 69(7): 3205-12.
[http://dx.doi.org/10.1158/0008-5472.CAN-08-3393] [PMID: 19318568]
[54]
Chen CY, Peng WH, Wu LC, Wu CC, Hsu SL. Luteolin ameliorates experimental lung fibrosis both in vivo and in vitro: implications for therapy of lung fibrosis. J Agric Food Chem 2010; 58(22): 11653-61.
[http://dx.doi.org/10.1021/jf1031668] [PMID: 20958047]
[55]
Zhou HT, Yu XF, Zhou GM. Diosgenin inhibits angiotensin II-induced extracellular matrix remodeling in cardiac fibroblasts through regulating the TGFβ1/Smad3 signaling pathway. Mol Med Rep 2017; 15(5): 2823-8.
[http://dx.doi.org/10.3892/mmr.2017.6280] [PMID: 28260007]
[56]
Lo SH, Hsu CT, Niu HS, Niu CS, Cheng JT, Chen ZC. Ginsenoside Rh2 improves cardiac fibrosis via PPARδ-STAT3 signaling in type 1-like diabetic rats. Int J Mol Sci 2017; 18(7)E1364
[http://dx.doi.org/10.3390/ijms18071364] [PMID: 28672855]
[57]
An L, Peng LY, Sun NY, et al. Tanshinone IIA activates nuclear factor-erythroid 2-related factor 2 to restrain pulmonary fibrosis via regulation of redox homeostasis and glutaminolysis. antioxid redox signal 2018. [J]. [Epub ahead of print].
[PMID: 30105924]
[58]
Tang H, He H, Ji H, et al. Tanshinone IIA ameliorates bleomycin-induced pulmonary fibrosis and inhibits transforming growth factor-beta-β-dependent epithelial to mesenchymal transition. J Surg Res 2015; 197(1): 167-75.
[http://dx.doi.org/10.1016/j.jss.2015.02.062] [PMID: 25911951]
[59]
Akgedik R, Akgedik S, Karamanlı H, et al. Effect of resveratrol on treatment of bleomycin-induced pulmonary fibrosis in rats. Inflammation 2012; 35(5): 1732-41.
[http://dx.doi.org/10.1007/s10753-012-9491-0] [PMID: 22707284]
[60]
Wang J, He F, Chen L, et al. Resveratrol inhibits pulmonary fibrosis by regulating miR-21 through MAPK/AP-1 pathways. Biomed Pharmacother 2018; 105: 37-44.
[http://dx.doi.org/10.1016/j.biopha.2018.05.104] [PMID: 29843043]
[61]
Huang SK, Chen CY, Shih HM, et al. Histone modifications are responsible for decreased Fas expression and apoptosis resistance in fibrotic lung fibroblasts. Cell Death Dis 2013; 4 e621
[http://dx.doi.org/10.1038/cddis.2013.146] [PMID: 23640463]
[62]
Chou KC, Forsen S, Zhou GQ. Three schematic rules for deriving apparent rate constants. Chem Scr 1980; 16: 109-13.
[63]
Chou KC, Carter RE, Forsen S. A new graphical method for deriving rate equations for complicated mechanisms. Chem Scr 1981; 18: 82-6.
[64]
Chou KC, Forsen S. Graphical rules of steady-state reaction systems. Can J Chem 1981; 59: 737-55.
[http://dx.doi.org/10.1139/v81-107]
[65]
Chou KC. Low-frequency vibrations of helical structures in protein molecules. Biochem J 1983; 209(3): 573-80.
[http://dx.doi.org/10.1042/bj2090573] [PMID: 6870784]
[66]
Chou KC. Low-frequency motions in protein molecules. Beta-sheet and beta-barrel. Biophys J 1985; 48(2): 289-97.
[http://dx.doi.org/10.1016/S0006-3495(85)83782-6] [PMID: 4052563]
[67]
Chou KC. Applications of graph theory to enzyme kinetics and protein folding kinetics. Steady and non-steady-state systems. Biophys Chem 1990; 35(1): 1-24.
[http://dx.doi.org/10.1016/0301-4622(90)80056-D] [PMID: 2183882]
[68]
Liu H, Wang M, Chou KC. Low-frequency Fourier spectrum for predicting membrane protein types. Biochem Biophys Res Commun 2005; 336(3): 737-9. [BBRC
[http://dx.doi.org/0.1016/j.bbrc.2005.08.160] [PMID: 16140260]
[69]
Chou KC. Graphic rule for drug metabolism systems. Curr Drug Metab 2010; 11(4): 369-78.
[http://dx.doi.org/10.2174/138920010791514261] [PMID: 20446902]
[70]
Li J, Wei DQ, Wang JF, Yu ZT, Chou KC. Molecular dynamics simulations of CYP2E1. Med Chem 2012; 8(2): 208-21.
[http://dx.doi.org/10.2174/157340612800493692] [PMID: 22385180]
[71]
Wang JF, Chou KC. Recent advances in computational studies on influenza a virus M2 proton channel. Mini Rev Med Chem 2012; 12(10): 971-8.
[http://dx.doi.org/10.2174/138955712802762275] [PMID: 22420575]
[72]
Jia J, Liu Z, Xiao X, Liu B, Chou KC. iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC. J Theor Biol 2015; 377: 47-56.
[http://dx.doi.org/10.1016/j.jtbi.2015.04.011] [PMID: 25908206]
[73]
Chou KC. Proposing pseudo amino acid components is an important milestone for proteome and genome analyses. Int J Pept Res Ther 2019.
[http://dx.doi.org/10.1007/s10989-019-09910-7]
[74]
Chou KC, Shen HB. Recent advances in developing web-servers for predicting protein attributes. Nat Sci 2009; 1: 63-92.
[http://dx.doi.org/10.4236/ns.2009.12011]
[75]
Cheng X, Xiao X, Chou KC. pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC. Mol Biosyst 2017; 13(9): 1722-7.
[http://dx.doi.org/10.1039/C7MB00267J] [PMID: 28702580]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy