- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Evidence-Based Complementary and Alternative Medicine
Volume 2013 (2013), Article ID 548498, 12 pages
A Systems Biology-Based Investigation into the Pharmacological Mechanisms of Wu Tou Tang Acting on Rheumatoid Arthritis by Integrating Network Analysis
Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16, Nanxiaojie, Dongzhimennei, Beijing 100700, China
Received 11 January 2013; Accepted 20 February 2013
Academic Editor: Aiping Lu
Copyright © 2013 Yanqiong Zhang 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.
- C. Böhler, H. Radner, M. Ernst et al., “Rheumatoid arthritis and falls: the influence of disease activity,” Rheumatology, vol. 51, no. 11, pp. 2051–2057, 2012.
- J. Liu and R. L. Liu, “The potential role of Chinese medicine in ameliorating extra-articular manifestations of rheumatoid arthritis,” Chinese Journal of Integrative Medicine, vol. 17, no. 10, pp. 735–737, 2011.
- S. Y. Zhang and J. Liu, “Clinical observalion of modified Wu Tou Tang in the treatment of active rheumatoid arthriti,” Chinese Journal of Traditional Medical Science and Technology, vol. 17, pp. 326–327, 2010.
- W. D. Hu, C. S. Lin, D. Q. Kong et al., “Clinical observalion of modified Guizhishaoyaozbimu decoction in the treatment of active rheumatoid arthriti,” Chinese Journal of Primary Medicine and Pharmacy, vol. 12, pp. 1699–1700, 2005.
- N. Lin, C. Liu, C. Xiao et al., “Triptolide, a diterpenoid triepoxide, suppresses inflammation and cartilage destruction in collagen-induced arthritis mice,” Biochemical Pharmacology, vol. 73, no. 1, pp. 136–146, 2007.
- Y. P. Zhu and H. J. Woerdenbag, “Traditional Chinese herbal medicine,” Pharmacy World and Science, vol. 17, no. 4, pp. 103–112, 1995.
- Z. Zheng, T. Yan, W. Chen, L. Ye, L. Tang, and Z. Liu, “Pharmacokinetic determination of ephedrine in Herba Ephedrae and Wu Tou Tang decoctions in rats using ultra performance liquid chromatography tandem mass spectrometry,” Xenobiotica, vol. 42, no. 8, pp. 775–783, 2012.
- C. Elder, C. Ritenbaugh, M. Aickin et al., “Reductions in pain medication use associated with traditional chinese medicine for chronic pain,” The Permanente Journal, vol. 16, no. 3, pp. 18–23, 2012.
- H. J. Wang and B. H. Chiang, “Anti-diabetic effect of a traditional Chinese medicine formula,” Food & Function, vol. 3, no. 11, pp. 1161–1169, 2012.
- H. Shi, C. Zhou, Y. Li, G. Wang, and Y. Sun, “Anti-inflammatory effect of aconitines,” Zhongguo Zhong Yao Za Zhi, vol. 15, no. 3, pp. 174–192, 1990.
- J. Hallas, L. Bjerrum, H. Støvring, and M. Andersen, “Use of a prescribed ephedrine/caffeine combination and the risk of serious cardiovascular events: a registry-based case-crossover study,” American Journal of Epidemiology, vol. 168, no. 8, pp. 966–973, 2008.
- W. Tao, X. Xu, X. Wang et al., “Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease,” Journal of Ethnopharmacology, vol. 145, no. 1, pp. 1–10, 2013.
- Z. H. Liu and X. B. Sun, “Network pharmacology: new opportunity for the modernization of traditional Chinese medicine,” Yao Xue Xue Bao, vol. 47, pp. 696–703, 2012.
- S. Zhao and S. Li, “Network-based relating pharmacological and genomic spaces for drug target identification,” PLoS ONE, vol. 5, no. 7, Article ID e11764, 2010.
- S. Li, B. Zhang, and N. Zhang, “Network target for screening synergistic drug combinations with application to traditional Chinese medicine,” BMC Systems Biology, vol. 5, supplement 1, p. S10, 2011.
- S. Li, B. Zhang, D. Jiang, Y. Wei, and N. Zhang, “Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae,” BMC Bioinformatics, vol. 11, supplement 11, p. S6, 2010.
- C. Y.-C. Chen, “TCM database Taiwan: the world's largest traditional Chinese medicine database for drug screening In Silico,” PLoS ONE, vol. 6, no. 1, Article ID e15939, 2011.
- D. S. Wishart, C. Knox, A. C. Guo et al., “DrugBank: a knowledgebase for drugs, drug actions and drug targets,” Nucleic Acids Research, vol. 36, no. 1, pp. D901–D906, 2008.
- J. Y. Chen, S. R. Mamidipalli, and T. Huan, “HAPPI: an online database of comprehensive human annotated and predicted protein interactions,” BMC Genomics, vol. 10, supplement 1, p. S16, 2009.
- L. Matthews, G. Gopinath, M. Gillespie et al., “Reactome knowledgebase of human biological pathways and processes,” Nucleic Acids Research, vol. 37, no. 1, pp. D619–D622, 2009.
- K. R. Brown and I. Jurisica, “Online predicted human interaction database,” Bioinformatics, vol. 21, no. 9, pp. 2076–2082, 2005.
- B. Aranda, P. Achuthan, Y. Alam-Faruque et al., “The IntAct molecular interaction database in 2010,” Nucleic Acids Research, vol. 38, no. 1, Article ID gkp878, pp. D525–D531, 2009.
- T. S. Keshava Prasad, R. Goel, K. Kandasamy et al., “Human protein reference database-2009 update,” Nucleic Acids Research, vol. 37, no. 1, pp. D767–D772, 2009.
- A. Ceol, A. Chatr Aryamontri, L. Licata et al., “MINT, the molecular interaction database: 2009 update,” Nucleic Acids Research, vol. 38, no. 1, Article ID gkp983, pp. D532–D539, 2009.
- B. Lehne and T. Schlitt, “Protein-protein interaction databases: keeping up with growing interactomes,” Human Genomics, vol. 3, no. 3, pp. 291–297, 2009.
- T. Beuming, L. Skrabanek, M. Y. Niv, P. Mukherjee, and H. Weinstein, “PDZBase: a protein-protein interaction database for PDZ-domains,” Bioinformatics, vol. 21, no. 6, pp. 827–828, 2005.
- F. Zhu, Z. Shi, C. Qin et al., “Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery,” Nucleic Acids Research, vol. 40, no. 1, pp. D1128–D1136, 2012.
- S. Briesemeister, J. Rahnenführer, and O. Kohlbacher, “Going from where to why—interpretable prediction of protein subcellular localization,” Bioinformatics, vol. 26, no. 9, Article ID btq115, pp. 1232–1238, 2010.
- G. Dennis Jr., B. T. Sherman, D. A. Hosack et al., “DAVID: database for annotation, visualization, and integrated discovery,” Genome Biology, vol. 4, no. 5, p. P3, 2003.
- J. Wixon and D. Kell, “The Kyoto encyclopedia of genes and genomes—KEGG,” Yeast, vol. 17, no. 1, pp. 48–55, 2000.
- Y. Wang, Z. Liu, C. Li et al., “Drug target prediction based on the herbs components: the study on the multitargets pharmacological mechanism of qishenkeli acting on the coronary heart disease,” Evidence-Based Complementary and Alternative Medicine, vol. 2012, Article ID 698531, 10 pages, 2012.
- S. Wuchty and E. Almaas, “Evolutionary cores of domain co-occurrence networks,” BMC Evolutionary Biology, vol. 5, p. 24, 2005.
- Z. Zsoldos, D. Reid, A. Simon, B. S. Sadjad, and A. P. Johnson, “eHiTS: an innovative approach to the docking and scoring function problems,” Current Protein and Peptide Science, vol. 7, no. 5, pp. 421–435, 2006.
- P. W. Rose, B. Beran, C. Bi et al., “The RCSB protein data bank: redesigned web site and web services,” Nucleic Acids Research, vol. 39, no. 1, pp. D392–D401, 2011.
- S. B. Su, A. Lu, S. Li, and W. Jia, “Evidence-based ZHENG: a traditional Chinese medicine syndrome,” Evidence-Based Complementary and Alternative Medicine, vol. 2012, Article ID 246538, 2 pages, 2012.
- S. Li, Z. Q. Zhang, L. J. Wu, X. G. Zhang, Y. D. Li, and Y. Y. Wang, “Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network,” IET Systems Biology, vol. 1, no. 1, pp. 51–60, 2007.
- E. V. Davies and M. B. Hallett, “Cytosolic Ca2+ signalling in inflammatory neutrophils: implications for rheumatoid arthritis (Review),” International Journal of Molecular Medicine, vol. 1, no. 2, pp. 485–490, 1998.
- C. Lu, C. Xiao, G. Chen et al., “Cold and heat pattern of rheumatoid arthritis in traditional Chinese medicine: distinct molecular signatures indentified by microarray expression profiles in CD4-positive T cell,” Rheumatology International, pp. 1–8, 2010.
- S. H. Yeh, H. Y. Yeh, and V. W. Soo, “A network flow approach to predict drug targets from microarray data, disease genes and interactome network-case study on prostate cancer,” Journal of Clinical Bioinformatics, vol. 2, no. 1, p. 1, 2012.
- P. Holme, B. J. Kim, C. N. Yoon, and S. K. Han, “Attack vulnerability of complex networks,” Physical Review E, vol. 65, no. 5, Article ID 056109, pp. 056109/1–056109/14, 2002.
- A. M. Malfait, A. S. Malik, L. Marinova-Mutafchieva, D. M. Butler, R. N. Maini, and M. Feldmann, “The β2-adrenergic agonist salbutamol is a potent suppressor of established collagen-induced arthritis: mechanisms of action,” Journal of Immunology, vol. 162, no. 10, pp. 6278–6283, 1999.
- M. Wahle, G. Hanefeld, S. Brunn et al., “Failure of catecholamines to shift T-cell cytokine responses toward a Th2 profile in patients with rheumatoid arthritis,” Arthritis Research and Therapy, vol. 8, no. 5, p. R138, 2006.
- C. G. O. Baerwald, M. Wahle, T. Ulrichs et al., “Reduced catecholamine response of lymphocytes from patients with rheumatoid arthritis,” Immunobiology, vol. 200, no. 1, pp. 77–91, 1999.
- G. Pont-Kingdon, J. Bohnsack, K. Sumner et al., “Lack of association between beta 2-adrenergic receptor polymorphisms and juvenile idiopathic arthritis,” Scandinavian Journal of Rheumatology, vol. 38, no. 2, pp. 91–95, 2009.
- B. Xu, L. Ärlehag, S. B. Rantapää-Dahlquist, and A. K. Lefvert, “β2-adrenergic receptor gene single-nucleotide polymorphisms are associated with rheumatoid arthritis in northern Sweden,” Scandinavian Journal of Rheumatology, vol. 33, no. 6, pp. 395–398, 2004.
- O. Malysheva, M. Pierer, U. Wagner, M. Wahle, U. Wagner, and C. G. Baerwald, “Association between β2 adrenergic receptor polymorphisms and rheumatoid arthritis in conjunction with human leukocyte antigen (HLA)-DRB1 shared epitope,” Annals of the Rheumatic Diseases, vol. 67, no. 12, pp. 1759–1764, 2008.
- D. Lorton, C. Lubahn, and D. L. Bellinger, “Potential use of drugs that target neural-immune pathways in the treatment of rheumatoid arthritis and other autoimmune diseases,” Current Drug Targets-Inflammation & Allergy, vol. 2, no. 1, pp. 1–30, 2003.
- C. Roupe Van Der Voort, C. J. Heijnen, N. Wulffraat, W. Kuis, and A. Kavelaars, “Stress induces increases in IL-6 production by leucocytes of patients with the chronic inflammatory disease juvenile rheumatoid arthritis: a putative role for α1-adrenergic receptors,” Journal of Neuroimmunology, vol. 110, no. 1-2, pp. 223–229, 2000.
- R. Beck, N. Dejeans, C. Glorieux et al., “Hsp90 is cleaved by reactive oxygen species at a highly conserved N-terminal amino acid motif,” PLoS One, vol. 7, no. 7, Article ID e40795, p. 1, 2012.
- S. Solier, K. W. Kohn, B. Scroggins et al., “Heat shock protein 90α (HSP90α), a substrate and chaperone of DNA-PK necessary for the apoptotic response,” Proceedings of the National Academy of Sciences of the United States of America, vol. 109, no. 32, pp. 12866–12872, 2012.
- L. Sedlackova, A. Sosna, P. Vavrincova et al., “Heat shock protein gene expression profile may differentiate between rheumatoid arthritis, osteoarthritis, and healthy controls,” Scandinavian Journal of Rheumatology, vol. 40, no. 5, pp. 354–357, 2011.
- V. Nicolaidou, M. M. Wong, A. N. Redpath et al., “Monocytes induce STAT3 activation in human mesenchymal stem cells to promote osteoblast formation,” PLoS One, vol. 7, no. 7, Article ID e39871, 2012.
- M. Seddighzadeh, A. Gonzalez, B. Ding et al., “Variants within STAT genes reveal association with anticitrullinated protein antibody-negative rheumatoid arthritis in 2 European populations,” Journal of Rheumatology, vol. 39, no. 8, pp. 1509–1516, 2012.
- H. Wang, Y. Fang, Y. Wang et al., “Inhibitory effect of curcumol on Jak2-STAT signal pathway molecules of fibroblast-like synoviocytes in patients with rheumatoid arthritis,” Evidence-Based Complementary and Alternative Medicine, vol. 2012, Article ID 746426, 8 pages, 2012.
- H. Yoshida, A. Kimura, T. Fukaya et al., “Low dose CP-690, 550 (tofacitinib), a pan-JAK inhibitor, accelerates the onset of experimental autoimmune encephalomyelitis by potentiating Th17 differentiation,” Biochemical and Biophysical Research Communications, vol. 418, no. 2, pp. 234–240, 2012.
- S. R. Witzmann, J. D. Turner, S. B. Mériaux, O. C. Meijer, and C. P. Muller, “Epigenetic regulation of the glucocorticoid receptor promoter 1 7 in adult rats,” Epigenetics, vol. 7, no. 11, pp. 1290–1301, 2012.
- A. Rauch, V. Gossye, D. Bracke et al., “An anti-inflammatory selective glucocorticoid receptor modulator preserves osteoblast differentiation,” FASEB Journal, vol. 25, no. 4, pp. 1323–1332, 2011.
- E. Oda, Y. Nakamura, M. Yamamoto, and M. Kojiro, “Immunohistochemical distribution of tubulin beta II in human normal and neoplastic tissues,” Kurume Medical Journal, vol. 52, no. 4, pp. 117–125, 2005.
- R. Ramos-Ruiz, J. Avila, J. P. Lopez-Bote, C. Bernabeu, and V. Larraga, “Decreased tubulin synthesis in synoviocytes from adjuvant-induced arthritic rats,” Biochimica et Biophysica Acta, vol. 1138, no. 3, pp. 184–190, 1992.
- T. Kamada, M. S. Kurokawa, T. Kato et al., “Proteomic analysis of bone marrow-adherent cells in rheumatoid arthritis and osteoarthritis,” International Journal of Rheumatic Diseases, vol. 15, no. 2, pp. 169–178, 2012.
- R. J. Bienstock, “Computational drug design targeting protein-protein interactions,” Current Pharmaceutical Design, vol. 18, no. 9, pp. 1240–1254, 2012.