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Current Computer-Aided Drug Design

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ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

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Research Article

Network Pharmacology, Molecular Docking and Experimental Verification Revealing the Mechanism of Fule Cream against Childhood Atopic Dermatitis

Author(s): Chang Liu, Yuxin Liu, Yi Liu, Jing Guan, Ying Gao, Ling Ou, Yuenan Qi, Xiaoxi Lv* and Jianmin Zhang*

Volume 20, Issue 6, 2024

Published on: 02 October, 2023

Page: [860 - 875] Pages: 16

DOI: 10.2174/0115734099257922230925074407

Price: $65

Abstract

Background: The Fule Cream (FLC) is an herbal formula widely used for the treatment of pediatric atopic dermatitis (AD), however, the main active components and functional mechanisms of FLC remain unclear. This study performed an initial exploration of the potential acting mechanisms of FLC in childhood AD treatment through analyses of an AD mouse model using network pharmacology, molecular docking technology, and RNA-seq analysis.

Materials and Methods: The main bioactive ingredients and potential targets of FLC were collected from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and SwissTargetPrediction databases. An herb-compound-target network was built using Cytoscape 3.7.2. The disease targets of pediatric AD were searched in the DisGeNET, Therapeutic Target Database (TTD), OMIM, DrugBank and GeneCards databases. The overlapping targets between the active compounds and the disease were imported into the STRING database for the construction of the protein-protein interaction (PPI) network. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the intersection targets were performed, and molecular docking verification of the core compounds and targets was then performed using AutoDock Vina 1.1.2. The AD mouse model for experimental verification was induced by MC903.

Results: The herb-compound-target network included 415 nodes and 1990 edges. Quercetin, luteolin, beta-sitosterol, wogonin, ursolic acid, apigenin, stigmasterol, kaempferol, sitogluside and myricetin were key nodes. The targets with higher degree values were IL-4, IL-10, IL-1α, IL-1β, TNFα, CXCL8, CCL2, CXCL10, CSF2, and IL-6. GO enrichment and KEGG analyses illustrated that important biological functions involved response to extracellular stimulus, regulation of cell adhesion and migration, inflammatory response, cellular response to cytokine stimulus, and cytokine receptor binding. The signaling pathways in the FLC treatment of pediatric AD mainly involve the PI3K-Akt signaling pathway, cytokine‒cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and NF-κB signaling pathway. The binding energy scores of the compounds and targets indicate a good binding activity. Luteolin, quercetin, and kaempferol showed a strong binding activity with TNFα and IL-4.

Conclusion: This study illustrates the main bioactive components and potential mechanisms of FLC in the treatment of childhood AD, and provides a basis and reference for subsequent exploration.

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Graphical Abstract

[1]
Langan, S.M.; Irvine, A.D.; Weidinger, S. Atopic dermatitis. Lancet, 2020, 396(10247), 345-360.
[http://dx.doi.org/10.1016/S0140-6736(20)31286-1] [PMID: 32738956]
[2]
Weidinger, S.; Beck, L.A.; Bieber, T.; Kabashima, K.; Irvine, A.D. Atopic dermatitis. Nat. Rev. Dis. Primers, 2018, 4(1), 1.
[http://dx.doi.org/10.1038/s41572-018-0001-z] [PMID: 29930242]
[3]
Bieber, T. Atopic dermatitis: An expanding therapeutic pipeline for a complex disease. Nat. Rev. Drug Discov., 2022, 21(1), 21-40.
[http://dx.doi.org/10.1038/s41573-021-00266-6] [PMID: 34417579]
[4]
Silverberg, J.I. Public health burden and epidemiology of atopic dermatitis. Dermatol. Clin., 2017, 35(3), 283-289.
[http://dx.doi.org/10.1016/j.det.2017.02.002] [PMID: 28577797]
[5]
Ariëns, L.; Nimwegen, K.; Shams, M.; Bruin, D.; Schaft, J.; Os-Medendorp, H.; Bruin-Weller, M. Economic burden of adult patients with moderate to severe atopic dermatitis indicated for systemic treatment. Acta Derm. Venereol., 2019, 99(9), 762-768.
[http://dx.doi.org/10.2340/00015555-3212] [PMID: 31073619]
[6]
Tsoi, L.C.; Rodriguez, E.; Stölzl, D.; Wehkamp, U.; Sun, J.; Gerdes, S.; Sarkar, M.K.; Hübenthal, M.; Zeng, C.; Uppala, R.; Xing, X.; Thielking, F.; Billi, A.C.; Swindell, W.R.; Shefler, A.; Chen, J.; Patrick, M.T.; Harms, P.W.; Kahlenberg, J.M.; Perez White, B.E.; Maverakis, E.; Gudjonsson, J.E.; Weidinger, S. Progression of acute-to-chronic atopic dermatitis is associated with quantitative rather than qualitative changes in cytokine responses. J. Allergy Clin. Immunol., 2020, 145(5), 1406-1415.
[http://dx.doi.org/10.1016/j.jaci.2019.11.047] [PMID: 31891686]
[7]
Tsoi, L.C.; Rodriguez, E.; Degenhardt, F.; Baurecht, H.; Wehkamp, U.; Volks, N.; Szymczak, S.; Swindell, W.R.; Sarkar, M.K.; Raja, K.; Shao, S.; Patrick, M.; Gao, Y.; Uppala, R.; Perez White, B.E.; Getsios, S.; Harms, P.W.; Maverakis, E.; Elder, J.T.; Franke, A.; Gudjonsson, J.E.; Weidinger, S. Atopic dermatitis is an IL-13–dominant disease with greater molecular heterogeneity compared to psoriasis. J. Invest. Dermatol., 2019, 139(7), 1480-1489.
[http://dx.doi.org/10.1016/j.jid.2018.12.018] [PMID: 30641038]
[8]
Gittler, J.K.; Shemer, A.; Suárez-Fariñas, M.; Fuentes-Duculan, J.; Gulewicz, K.J.; Wang, C.Q.F.; Mitsui, H.; Cardinale, I.; de Guzman Strong, C.; Krueger, J.G.; Guttman-Yassky, E. Progressive activation of TH2/TH22 cytokines and selective epidermal proteins characterizes acute and chronic atopic dermatitis. J. Allergy Clin. Immunol., 2012, 130(6), 1344-1354.
[http://dx.doi.org/10.1016/j.jaci.2012.07.012] [PMID: 22951056]
[9]
Renert-Yuval, Y.; Del Duca, E.; Pavel, A.B.; Fang, M.; Lefferdink, R.; Wu, J.; Diaz, A.; Estrada, Y.D.; Canter, T.; Zhang, N.; Wagner, A.; Chamlin, S.; Krueger, J.G.; Guttman-Yassky, E.; Paller, A.S. The molecular features of normal and atopic dermatitis skin in infants, children, adolescents, and adults. J. Allergy Clin. Immunol., 2021, 148(1), 148-163.
[http://dx.doi.org/10.1016/j.jaci.2021.01.001] [PMID: 33453290]
[10]
Mancuso, J.B.; Lee, S.S.; Paller, A.S.; Ohya, Y.; Eichenfield, L.F. Management of severe atopic dermatitis in pediatric patients. J. Allergy Clin. Immunol. Pract., 2021, 9(4), 1462-1471.
[http://dx.doi.org/10.1016/j.jaip.2021.02.017] [PMID: 33838839]
[11]
Mandlik, D.S.; Mandlik, S.K. Atopic dermatitis: New insight into the etiology, pathogenesis, diagnosis and novel treatment strategies. Immunopharmacol. Immunotoxicol., 2021, 43(2), 105-125.
[http://dx.doi.org/10.1080/08923973.2021.1889583] [PMID: 33645388]
[12]
Wang, Z.; Xia, Q.; Liu, X.; Liu, W.; Huang, W.; Mei, X.; Luo, J.; Shan, M.; Lin, R.; Zou, D.; Ma, Z. Phytochemistry, pharmacology, quality control and future research of Forsythia suspensa (Thunb.) Vahl: A review. J. Ethnopharmacol., 2018, 210, 318-339.
[http://dx.doi.org/10.1016/j.jep.2017.08.040] [PMID: 28887216]
[13]
Hao, Y.; Li, D.; Piao, X.; Piao, X. Forsythia suspensa extract alleviates hypersensitivity induced by soybean β-conglycinin in weaned piglets. J. Ethnopharmacol., 2010, 128(2), 412-418.
[http://dx.doi.org/10.1016/j.jep.2010.01.035] [PMID: 20083183]
[14]
Sung, Y.Y.; Lee, A.Y.; Kim, H.K. Forsythia suspensa fruit extracts and the constituent matairesinol confer anti-allergic effects in an allergic dermatitis mouse model. J. Ethnopharmacol., 2016, 187, 49-56.
[http://dx.doi.org/10.1016/j.jep.2016.04.015] [PMID: 27085937]
[15]
Sung, Y.Y.; Yoon, T.; Jang, S.; Kim, H.K. Forsythia suspensa suppresses house dust mite extract-induced atopic dermatitis in NC/Nga mice. PLoS One, 2016, 11(12), e0167687.
[http://dx.doi.org/10.1371/journal.pone.0167687] [PMID: 27936051]
[16]
Zhang, H.; Sun, X.; Qi, H.; Ma, Q.; Zhou, Q.; Wang, W.; Wang, K. Pharmacological inhibition of the temperature-sensitive and Ca 2+ -Permeable transient receptor potential vanilloid trpv3 channel by natural forsythoside b attenuates pruritus and cytotoxicity of keratinocytes. J. Pharmacol. Exp. Ther., 2019, 368(1), 21-31.
[http://dx.doi.org/10.1124/jpet.118.254045] [PMID: 30377214]
[17]
Kim, H.; Yang, B.; Lee, H-B.; Kim, S.; Park, Y.C.; Kim, K. Decoction of Dictamnus Dasycarpus Turcz. Root bark ameliorates skin lesions and inhibits inflammatory reactions in mice with contact dermatitis. Pharmacogn. Mag., 2017, 13(51), 483-487.
[http://dx.doi.org/10.4103/0973-1296.211034] [PMID: 28839376]
[18]
Gao, P.; Wang, L.; Zhao, L.; Zhang, Q.; Zeng, K.; Zhao, M.; Jiang, Y.; Tu, P.; Guo, X. Anti-inflammatory quinoline alkaloids from the root bark of Dictamnus dasycarpus. Phytochemistry, 2020, 172, 112260.
[http://dx.doi.org/10.1016/j.phytochem.2020.112260] [PMID: 31982646]
[19]
Kim, H.; Kim, M.; Kim, H.; San Lee, G.; Gun An, W.; In Cho, S. Anti-inflammatory activities of Dictamnus dasycarpus Turcz., root bark on allergic contact dermatitis induced by dinitrofluorobenzene in mice. J. Ethnopharmacol., 2013, 149(2), 471-477.
[http://dx.doi.org/10.1016/j.jep.2013.06.055] [PMID: 23850712]
[20]
Chu, X.; Wei, M.; Yang, X.; Cao, Q.; Xie, X.; Guan, M.; Wang, D.; Deng, X. Effects of an anthraquinone derivative from Rheum officinale Baill, emodin, on airway responses in a murine model of asthma. Food Chem. Toxicol., 2012, 50(7), 2368-2375.
[http://dx.doi.org/10.1016/j.fct.2012.03.076] [PMID: 22484343]
[21]
Lin, Y.C.; Yang, C.C.; Lin, C.H.; Hsia, T.C.; Chao, W.C.; Lin, C.C. Atractylodin ameliorates ovalbumin induced asthma in a mouse model and exerts immunomodulatory effects on Th2 immunity and dendritic cell function. Mol. Med. Rep., 2020, 22(6), 4909-4918.
[http://dx.doi.org/10.3892/mmr.2020.11569] [PMID: 33174031]
[22]
Hopkins, A.L. Network pharmacology: The next paradigm in drug discovery. Nat. Chem. Biol., 2008, 4(11), 682-690.
[http://dx.doi.org/10.1038/nchembio.118] [PMID: 18936753]
[23]
Wang, Y.; Yuan, Y.; Wang, W.; He, Y.; Zhong, H.; Zhou, X.; Chen, Y.; Cai, X.J.; Liu, L. Mechanisms underlying the therapeutic effects of Qingfeiyin in treating acute lung injury based on GEO datasets, network pharmacology and molecular docking. Comput. Biol. Med., 2022, 145, 105454.
[http://dx.doi.org/10.1016/j.compbiomed.2022.105454] [PMID: 35367781]
[24]
Li, X.; Wei, S.; Niu, S.; Ma, X.; Li, H.; Jing, M.; Zhao, Y. Network pharmacology prediction and molecular docking-based strategy to explore the potential mechanism of Huanglian Jiedu Decoction against sepsis. Comput. Biol. Med., 2022, 144, 105389.
[http://dx.doi.org/10.1016/j.compbiomed.2022.105389] [PMID: 35303581]
[25]
Ru, J.; Li, P.; Wang, J.; Zhou, W.; Li, B.; Huang, C.; Li, P.; Guo, Z.; Tao, W.; Yang, Y.; Xu, X.; Li, Y.; Wang, Y.; Yang, L. TCMSP: A database of systems pharmacology for drug discovery from herbal medicines. J. Cheminform., 2014, 6(1), 13.
[http://dx.doi.org/10.1186/1758-2946-6-13] [PMID: 24735618]
[26]
Daina, A.; Michielin, O.; Zoete, V. SwissTargetPrediction: Updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res., 2019, 47(W1), W357-W364.
[http://dx.doi.org/10.1093/nar/gkz382] [PMID: 31106366]
[27]
Tao, W.; Xu, X.; Wang, X.; Li, B.; Wang, Y.; Li, Y.; Yang, L. Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease. J. Ethnopharmacol., 2013, 145(1), 1-10.
[http://dx.doi.org/10.1016/j.jep.2012.09.051] [PMID: 23142198]
[28]
Kim, S.; Chen, J.; Cheng, T.; Gindulyte, A.; He, J.; He, S.; Li, Q.; Shoemaker, B.A.; Thiessen, P.A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E.E. PubChem 2023 update. Nucleic Acids Res., 2023, 51(D1), D1373-D1380.
[http://dx.doi.org/10.1093/nar/gkac956] [PMID: 36305812]
[29]
Piñero, J.; Ramírez-Anguita, J.M.; Saüch-Pitarch, J.; Ronzano, F.; Centeno, E.; Sanz, F.; Furlong, L.I. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Res., 2020, 48(D1), D845-D855.
[PMID: 31680165]
[30]
Zhou, Y.; Zhang, Y.; Lian, X.; Li, F.; Wang, C.; Zhu, F.; Qiu, Y.; Chen, Y. Therapeutic target database update 2022: Facilitating drug discovery with enriched comparative data of targeted agents. Nucleic Acids Res., 2022, 50(D1), D1398-D1407.
[http://dx.doi.org/10.1093/nar/gkab953] [PMID: 34718717]
[31]
Amberger, J.S.; Bocchini, C.A.; Schiettecatte, F.; Scott, A.F.; Hamosh, A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res., 2015, 43(D1), D789-D798.
[http://dx.doi.org/10.1093/nar/gku1205] [PMID: 25428349]
[32]
Wishart, D.S.; Feunang, Y.D.; Guo, A.C.; Lo, E.J.; Marcu, A.; Grant, J.R.; Sajed, T.; Johnson, D.; Li, C.; Sayeeda, Z.; Assempour, N.; Iynkkaran, I.; Liu, Y.; Maciejewski, A.; Gale, N.; Wilson, A.; Chin, L.; Cummings, R.; Le, D.; Pon, A.; Knox, C.; Wilson, M. DrugBank 5.0: A major update to the DrugBank database for 2018. Nucleic Acids Res., 2018, 46(D1), D1074-D1082.
[http://dx.doi.org/10.1093/nar/gkx1037] [PMID: 29126136]
[33]
Stelzer, G.; Rosen, N.; Plaschkes, I.; Zimmerman, S.; Twik, M.; Fishilevich, S.; Stein, T. I.; Nudel, R.; Lieder, I.; Mazor, Y.; Kaplan, S.; Dahary, D.; Warshawsky, D.; Guan-Golan, Y.; Kohn, A.; Rappaport, N.; Safran, M.; Lancet, D. The genecards suite: From gene data mining to disease genome sequence analyses. Curr. Protoc. Bioinformatics, 2016, 54, 1.30.1-1.30.33.
[34]
Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res., 2003, 13(11), 2498-2504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[35]
Tang, Y.; Li, M.; Wang, J.; Pan, Y.; Wu, F.X. CytoNCA: A cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems, 2015, 127, 67-72.
[http://dx.doi.org/10.1016/j.biosystems.2014.11.005] [PMID: 25451770]
[36]
Raman, K.; Damaraju, N.; Joshi, G.K. The organisational structure of protein networks: Revisiting the centrality–lethality hypothesis. Syst. Synth. Biol., 2014, 8(1), 73-81.
[http://dx.doi.org/10.1007/s11693-013-9123-5] [PMID: 24592293]
[37]
Missiuro, P.V.; Liu, K.; Zou, L.; Ross, B.C.; Zhao, G.; Liu, J.S.; Ge, H. Information flow analysis of interactome networks. PLOS Comput. Biol., 2009, 5(4), e1000350.
[http://dx.doi.org/10.1371/journal.pcbi.1000350] [PMID: 19503817]
[38]
R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2021. Available from: https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006
[39]
Chen, H. R package VennDiagram: Generate High-Resolution Venn and Euler Plots. 2021. Available from: https://rdrr.io/cran/VennDiagram/#:~:text=A%20set%20of%20functions%20to,of%20plot%20shape%20and%20structure.
[40]
Szklarczyk, D.; Gable, A.L.; Lyon, D.; Junge, A.; Wyder, S.; Huerta-Cepas, J.; Simonovic, M.; Doncheva, N.T.; Morris, J.H.; Bork, P.; Jensen, L.J.; Mering, C. STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res., 2019, 47(D1), D607-D613.
[http://dx.doi.org/10.1093/nar/gky1131] [PMID: 30476243]
[41]
Chin, C.H.; Chen, S.H.; Wu, H.H.; Ho, C.W.; Ko, M.T.; Lin, C.Y. cytoHubba: Identifying hub objects and sub-networks from complex interactome. BMC Syst. Biol., 2014, 8(S4), S11.
[http://dx.doi.org/10.1186/1752-0509-8-S4-S11] [PMID: 25521941]
[42]
Zhou, Y.; Zhou, B.; Pache, L.; Chang, M.; Khodabakhshi, A.H.; Tanaseichuk, O.; Benner, C.; Chanda, S.K. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun., 2019, 10(1), 1523.
[http://dx.doi.org/10.1038/s41467-019-09234-6] [PMID: 30944313]
[43]
Wickham, H. ggplot2: Elegant Graphics for Data Analysis; Springer, 2016.
[44]
Neuwirth, E. RColorBrewer: ColorBrewer Palettes(Version 1.1-2). 2014. Available from: http://cran.nexr.com/web/packages/RColorBrewer/index.html
[45]
Csardi, G. The igraph software package for complex network research. InterJ. Complex Syst., 2006, 1695(5), 1-9.
[46]
Wu, T.; Hu, E.; Xu, S.; Chen, M.; Guo, P.; Dai, Z.; Feng, T.; Zhou, L.; Tang, W.; Zhan, L.; Fu, X.; Liu, S.; Bo, X.; Yu, G. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation, 2021, 2(3), 100141.
[http://dx.doi.org/10.1016/j.xinn.2021.100141] [PMID: 34557778]
[47]
Walter, W.; Sánchez-Cabo, F.; Ricote, M. GOplot: An R package for visually combining expression data with functional analysis. Bioinformatics, 2015, 31(17), 2912-2914.
[http://dx.doi.org/10.1093/bioinformatics/btv300] [PMID: 25964631]
[48]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[PMID: 19499576]
[49]
Kim, S.; Chen, J.; Cheng, T.; Gindulyte, A.; He, J.; He, S.; Li, Q.; Shoemaker, B.A.; Thiessen, P.A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E.E. PubChem 2019 update: Improved access to chemical data. Nucleic Acids Res., 2019, 47(D1), D1102-D1109.
[http://dx.doi.org/10.1093/nar/gky1033] [PMID: 30371825]
[50]
O’Boyle, N.M.; Banck, M.; James, C.A.; Morley, C.; Vandermeersch, T.; Hutchison, G.R. Open Babel: An open chemical toolbox. J. Cheminform., 2011, 3(1), 33.
[http://dx.doi.org/10.1186/1758-2946-3-33] [PMID: 21982300]
[51]
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30(16), 2785-2791.
[http://dx.doi.org/10.1002/jcc.21256] [PMID: 19399780]
[52]
Seeliger, D.; de Groot, B.L. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J. Comput. Aided Mol. Des., 2010, 24(5), 417-422.
[http://dx.doi.org/10.1007/s10822-010-9352-6] [PMID: 20401516]
[53]
Burley, S.K.; Bhikadiya, C.; Bi, C.; Bittrich, S.; Chen, L.; Crichlow, G.V.; Christie, C.H.; Dalenberg, K.; Di Costanzo, L.; Duarte, J.M.; Dutta, S.; Feng, Z.; Ganesan, S.; Goodsell, D.S.; Ghosh, S.; Green, R.K.; Guranović, V.; Guzenko, D.; Hudson, B.P.; Lawson, C.L.; Liang, Y.; Lowe, R.; Namkoong, H.; Peisach, E.; Persikova, I.; Randle, C.; Rose, A.; Rose, Y.; Sali, A.; Segura, J.; Sekharan, M.; Shao, C.; Tao, Y.P.; Voigt, M.; Westbrook, J.D.; Young, J.Y.; Zardecki, C.; Zhuravleva, M. RCSB Protein Data Bank: Powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. Nucleic Acids Res., 2021, 49(D1), D437-D451.
[http://dx.doi.org/10.1093/nar/gkaa1038] [PMID: 33211854]
[54]
DeLano, W.L. The PyMOL Molecular Graphics System (Version 2.5.0). 2021. Available from: https://mybiosoftware.com/pymol-molecular-visualization-system.html
[55]
Laskowski, R.A.; Swindells, M.B. LigPlot+: Multiple ligand-protein interaction diagrams for drug discovery. J. Chem. Inf. Model., 2011, 51(10), 2778-2786.
[http://dx.doi.org/10.1021/ci200227u] [PMID: 21919503]
[56]
Dai, J.; Choo, M.K.; Park, J.M.; Fisher, D.E. Topical ror inverse agonists suppress inflammation in mouse models of atopic dermatitis and acute irritant dermatitis. J. Invest. Dermatol., 2017, 137(12), 2523-2531.
[http://dx.doi.org/10.1016/j.jid.2017.07.819] [PMID: 28774591]
[57]
Hou, D.D.; Zhang, W.; Gao, Y.L.; Sun, Y.; Wang, H.X.; Qi, R.Q.; Chen, H.D.; Gao, X.H. Anti-inflammatory effects of quercetin in a mouse model of MC903-induced atopic dermatitis. Int. Immunopharmacol., 2019, 74, 105676.
[http://dx.doi.org/10.1016/j.intimp.2019.105676] [PMID: 31181406]
[58]
Karuppagounder, V.; Arumugam, S.; Thandavarayan, R.A.; Sreedhar, R.; Giridharan, V.V.; Watanabe, K. Molecular targets of quercetin with anti-inflammatory properties in atopic dermatitis. Drug Discov. Today, 2016, 21(4), 632-639.
[http://dx.doi.org/10.1016/j.drudis.2016.02.011] [PMID: 26905599]
[59]
Karuppagounder, V.; Arumugam, S.; Thandavarayan, R.A.; Pitchaimani, V.; Sreedhar, R.; Afrin, R.; Harima, M.; Suzuki, H.; Nomoto, M.; Miyashita, S.; Suzuki, K.; Nakamura, M.; Watanabe, K. Modulation of HMGB1 translocation and RAGE/NF κ B cascade by quercetin treatment mitigates atopic dermatitis in NC/Nga transgenic mice. Exp. Dermatol., 2015, 24(6), 418-423.
[http://dx.doi.org/10.1111/exd.12685] [PMID: 25739980]
[60]
Lee, H.N.; Shin, S.A.; Choo, G.S.; Kim, H.J.; Park, Y.S.; Kim, B.S.; Kim, S.K.; Cho, S.D.; Nam, J.S.; Choi, C.S.; Che, J.H.; Park, B.K.; Jung, J.Y. Anti inflammatory effect of quercetin and galangin in LPS stimulated RAW264.7 macrophages and DNCB induced atopic dermatitis animal models. Int. J. Mol. Med., 2018, 41(2), 888-898.
[PMID: 29207037]
[61]
Beken, B.; Serttas, R.; Yazicioglu, M.; Turkekul, K.; Erdogan, S. Quercetin improves inflammation, oxidative stress, and impaired wound healing in atopic dermatitis model of human keratinocytes. Pediatr. Allergy Immunol. Pulmonol., 2020, 33(2), 69-79.
[http://dx.doi.org/10.1089/ped.2019.1137] [PMID: 34678092]
[62]
Gendrisch, F.; Esser, P.R.; Schempp, C.M.; Wölfle, U. Luteolin as a modulator of skin aging and inflammation. Biofactors, 2021, 47(2), 170-180.
[http://dx.doi.org/10.1002/biof.1699] [PMID: 33368702]
[63]
Gugliandolo, E.; Palma, E.; Cordaro, M.; D’Amico, R.; Peritore, A.F.; Licata, P.; Crupi, R. Canine atopic dermatitis: Role of luteolin as new natural treatment. Vet. Med. Sci., 2020, 6(4), 926-932.
[http://dx.doi.org/10.1002/vms3.325] [PMID: 32741111]
[64]
Han, N.R.; Kim, H.M.; Jeong, H.J. The β-sitosterol attenuates atopic dermatitis-like skin lesions through down-regulation of TSLP. Exp. Biol. Med., 2014, 239(4), 454-464.
[http://dx.doi.org/10.1177/1535370213520111] [PMID: 24510054]
[65]
Moon, P.D.; Han, N.R.; Lee, J.; Kim, H.M.; Jeong, H.J. Ursolic acid downregulates thymic stromal lymphopoietin through the blockade of intracellular calcium/caspase 1/NF κB signaling cascade in HMC 1 cells. Int. J. Mol. Med., 2019, 43(5), 2252-2258.
[http://dx.doi.org/10.3892/ijmm.2019.4144] [PMID: 30976816]
[66]
Yano, S.; Umeda, D.; Yamashita, S.; Yamada, K.; Tachibana, H. Dietary apigenin attenuates the development of atopic dermatitis-like skin lesions in NC/Nga mice. J. Nutr. Biochem., 2009, 20(11), 876-881.
[http://dx.doi.org/10.1016/j.jnutbio.2008.08.002] [PMID: 18993046]
[67]
Che, D.N.; Cho, B.O.; Shin, J.Y.; Kang, H.J.; Kim, J.S.; Oh, H.; Kim, Y.S.; Jang, S.I. Apigenin inhibits IL-31 cytokine in human mast cell and mouse skin tissues. Molecules, 2019, 24(7), 1290.
[http://dx.doi.org/10.3390/molecules24071290] [PMID: 30987029]
[68]
Lee, H.S.; Jeong, G.S. Therapeutic effect of kaempferol on atopic dermatitis by attenuation of T cell activity via interaction with multidrug resistance‐associated protein 1. Br. J. Pharmacol., 2021, 178(8), 1772-1788.
[http://dx.doi.org/10.1111/bph.15396] [PMID: 33555623]
[69]
Hou, D.D.; Gu, Y.J.; Wang, D.C.; Niu, Y.; Xu, Z.R.; Jin, Z.Q.; Wang, X.X.; Li, S.J. Therapeutic effects of myricetin on atopic dermatitis in vivo and in vitro. Phytomedicine, 2022, 102, 154200.
[http://dx.doi.org/10.1016/j.phymed.2022.154200] [PMID: 35671605]
[70]
Behniafard, N.; Gharagozlou, M.; Farhadi, E.; Khaledi, M.; Sotoudeh, S.; Darabi, B.; Fathi, S.M.; Gholizadeh Moghaddam, Z.; Mahmoudi, M.; Aghamohammadi, A.; Amirzargar, A.A.; Rezaei, N. TNF-alpha single nucleotide polymorphisms in atopic dermatitis. Eur. Cytokine Netw., 2012, 23(4), 163-165.
[http://dx.doi.org/10.1684/ecn.2012.0323] [PMID: 23328497]
[71]
Gharagozlou, M.; Farhadi, E.; Khaledi, M.; Behniafard, N.; Sotoudeh, S.; Salari, R.; Darabi, B.; Fathi, S.M.; Mahmoudi, M.; Aghamohammadi, A.; Amirzargar, A.A.; Rezaei, N. Association between the interleukin 6 genotype at position -174 and atopic dermatitis. J. Investig. Allergol. Clin. Immunol., 2013, 23(2), 89-93.
[PMID: 23654074]
[72]
Stavric, K.; Peova, S.; Trajkov, D.; Spiroski, M. Gene polymorphisms of 22 cytokines in Macedonian children with atopic dermatitis. Iran. J. Allergy Asthma Immunol., 2012, 11(1), 37-50.
[PMID: 22427475]
[73]
Kayserova, J.; Sismova, K.; Zentsova-Jaresova, I.; Katina, S.; Vernerova, E.; Polouckova, A.; Capkova, S.; Malinova, V.; Striz, I.; Sediva, A. A prospective study in children with a severe form of atopic dermatitis: Clinical outcome in relation to cytokine gene polymorphisms. J. Investig. Allergol. Clin. Immunol., 2012, 22(2), 92-101.
[PMID: 22533231]
[74]
Hulshof, L.; Hack, D.P.; Hasnoe, Q.C.J.; Dontje, B.; Jakasa, I.; Riethmüller, C.; McLean, W.H.I.; Aalderen, W.M.C.; van’t Land, B.; Kezic, S.; Sprikkelman, A.B.; Middelkamp-Hup, M.A. A minimally invasive tool to study immune response and skin barrier in children with atopic dermatitis. Br. J. Dermatol., 2019, 180(3), 621-630.
[http://dx.doi.org/10.1111/bjd.16994] [PMID: 29989151]
[75]
Lyubchenko, T.; Collins, H.K.; Goleva, E.; Leung, D.Y.M. Skin tape sampling technique identifies proinflammatory cytokines in atopic dermatitis skin. Ann. Allergy Asthma Immunol., 2021, 126(1), 46-53.e2.
[http://dx.doi.org/10.1016/j.anai.2020.08.397] [PMID: 32896640]
[76]
Lee, Y.; Choi, H.K.; N’deh, K.P.U.; Choi, Y.J.; Fan, M.; Kim, E.; Chung, K.H.; An, J.H. Inhibitory effect of centella asiatica extract on dncb-induced atopic dermatitis in hacat cells and BALB/c mice. Nutrients, 2020, 12(2), 411.
[http://dx.doi.org/10.3390/nu12020411] [PMID: 32033291]
[77]
Danso, M.O.; van Drongelen, V.; Mulder, A.; van Esch, J.; Scott, H.; van Smeden, J.; El Ghalbzouri, A.; Bouwstra, J.A. TNF-α and Th2 cytokines induce atopic dermatitis-like features on epidermal differentiation proteins and stratum corneum lipids in human skin equivalents. J. Invest. Dermatol., 2014, 134(7), 1941-1950.
[http://dx.doi.org/10.1038/jid.2014.83] [PMID: 24518171]
[78]
Howell, M.D.; Kim, B.E.; Gao, P.; Grant, A.V.; Boguniewicz, M.; DeBenedetto, A.; Schneider, L.; Beck, L.A.; Barnes, K.C.; Leung, D.Y.M. Cytokine modulation of atopic dermatitis filaggrin skin expression. J. Allergy Clin. Immunol., 2007, 120(1), 150-155.
[http://dx.doi.org/10.1016/j.jaci.2007.04.031] [PMID: 17512043]

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