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Evidence-Based Complementary and Alternative Medicine
Volume 2013 (2013), Article ID 256782, 11 pages
Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network
1Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
2Department of Phytochemistry, School of Pharmacy, Second Military Medical University, Shanghai 200433, China
Received 5 March 2013; Accepted 7 April 2013
Academic Editor: Aiping Lu
Copyright © 2013 Mengzhu Xue 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.
- J. L. Stevens and T. K. Baker, “The future of drug safety testing: expanding the view and narrowing the focus,” Drug Discovery Today, vol. 14, no. 3-4, pp. 162–167, 2009.
- D. R. Abernethy, J. Woodcock, and L. J. Lesko, “Pharmacological mechanism-based drug safety assessment and prediction,” Clinical Pharmacology and Therapeutics, vol. 89, no. 6, pp. 793–797, 2011.
- H. Olson, G. Betton, D. Robinson et al., “Concordance of the toxicity of pharmaceuticals in humans and in animals,” Regulatory Toxicology and Pharmacology, vol. 32, no. 1, pp. 56–67, 2000.
- Z. Lu, “Technical challenges in designing post-marketing eCRFs to address clinical safety and pharmacovigilance needs,” Contemporary Clinical Trials, vol. 31, no. 1, pp. 108–118, 2010.
- J. Abraham and C. Davis, “A comparative analysis of drug safety withdrawals in the UK and the US (1971–1992): implications for current regulatory thinking and policy,” Social Science and Medicine, vol. 61, no. 5, pp. 881–892, 2005.
- M. Hauben and A. Bate, “Decision support methods for the detection of adverse events in post-marketing data,” Drug Discovery Today, vol. 14, no. 7-8, pp. 343–357, 2009.
- J. Moggs, P. Moulin, F. Pognan, et al., “Investigative safety science as a competitive advantage for Pharma,” Expert Opinion on Drug Metabolism & Toxicology, vol. 8, pp. 1071–1082, 2012.
- C. Ishiguro, M. Hall, G. A. Neyarapally, et al., “Post-market drug safety evidence sources: an analysis of FDA drug safety communications,” Pharmacoepidemiology and Drug Safety, vol. 21, pp. 1134–1136, 2012.
- L. G. Valerio Jr., “In silico toxicology for the pharmaceutical sciences,” Toxicology and Applied Pharmacology, vol. 241, no. 3, pp. 356–370, 2009.
- W. Muster, A. Breidenbach, H. Fischer, S. Kirchner, L. Müller, and A. Pähler, “Computational toxicology in drug development,” Drug Discovery Today, vol. 13, no. 7-8, pp. 303–310, 2008.
- S. Bureeva and Y. Nikolsky, “Quantitative knowledge-based analysis in compound safety assessment,” Expert Opinion on Drug Metabolism & Toxicology, vol. 7, no. 3, pp. 287–298, 2011.
- S. Singh and Y. K. Loke, “Drug safety assessment in clinical trials: methodological challenges and opportunities,” Trials, vol. 13, article 138, 2012.
- N. Chandra and J. Padiadpu, “Network approaches to drug discovery,” Expert Opinion on Drug Metabolism & Toxicology, vol. 8, pp. 7–20, 2013.
- A. L. Barabási and Z. N. Oltvai, “Network biology: understanding the cell's functional organization,” Nature Reviews Genetics, vol. 5, no. 2, pp. 101–113, 2004.
- A. L. Hopkins, “Network pharmacology: the next paradigm in drug discovery,” Nature Chemical Biology, vol. 4, no. 11, pp. 682–690, 2008.
- L. C. Huang, X. Wu, and J. Y. Chen, “Predicting adverse side effects of drugs,” BMC Genomics, vol. 12, supplement 5, article S11, 2011.
- C. J. Ross, H. Visscher, J. Sistonen et al., “The Canadian Pharmacogenomics Network for Drug Safety: a model for safety pharmacology,” Thyroid, vol. 20, no. 7, pp. 681–687, 2010.
- J. P. Bai and D. R. Abernethy, “Systems pharmacology to predict drug toxicity: integration across levels of biological organization,” Annual Review of Pharmacology and Toxicology, vol. 53, pp. 451–473, 2013.
- M. Campillos, M. Kuhn, A. C. Gavin, L. J. Jensen, and P. Bork, “Drug target identification using side-effect similarity,” Science, vol. 321, no. 5886, pp. 263–266, 2008.
- A. Cami, A. Arnold, S. Manzi, et al., “Predicting adverse drug events using pharmacological network models,” Science Translational Medicine, vol. 3, pp. 114–127, 2011.
- Y. Yamanishi, M. Kotera, M. Kanehisa, and S. Goto, “Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework,” Bioinformatics, vol. 26, no. 12, pp. i246–i254, 2010.
- Y. Yamanishi, M. Araki, A. Gutteridge, W. Honda, and M. Kanehisa, “Prediction of drug-target interaction networks from the integration of chemical and genomic spaces,” Bioinformatics, vol. 24, no. 13, pp. i232–i240, 2008.
- H. Itokawa, S. L. Morris-Natschke, T. Akiyama, and K. H. Lee, “Plant-derived natural product research aimed at new drug discovery,” Journal of Natural Medicines, vol. 62, no. 3, pp. 263–280, 2008.
- M. S. Butler, “The role of natural product chemistry in drug discovery,” Journal of Natural Products, vol. 67, no. 12, pp. 2141–2153, 2004.
- M. S. Butler, “Natural products to drugs: natural product derived compounds in clinical trials,” Natural Product Reports, vol. 22, no. 2, pp. 162–195, 2005.
- M. S. Butler, “Natural products to drugs: natural product-derived compounds in clinical trials,” Natural Product Reports, vol. 25, no. 3, pp. 475–516, 2008.
- H. Lachance, S. Wetzel, K. Kumar, et al., “Charting, navigating, and populating natural product chemical space for drug discovery,” Journal of Medicinal Chemistry, vol. 55, pp. 5989–6001, 2012.
- L. F. Tietze, H. P. Bell, and S. Chandrasekhar, “Natural product hybrids as new leads for drug discovery,” Angewandte Chemie, vol. 42, no. 34, pp. 3996–4028, 2003.
- F. D. Debelle, J. L. Vanherweghem, and J. L. Nortier, “Aristolochic acid nephropathy: a worldwide problem,” Kidney International, vol. 74, no. 2, pp. 158–169, 2008.
- Y. H. Hwang, T. Kim, W. K. Cho, et al., “In vitro and in vivo genotoxicity assessment of aristolochia manshuriensis kom,” Evidence-Based Complementary and Alternative Medicine, vol. 2012, Article ID 412736, 9 pages, 2012.
- 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.
- S. Zhang, W. Lu, X. Liu et al., “Fast and effective identification of the bioactive compounds and their targets from medicinal plants via computational chemical biology approach,” MedChemComm, vol. 2, no. 6, pp. 471–477, 2011.
- M. E. Smoot, K. Ono, J. Ruscheinski, P. L. Wang, and T. Ideker, “Cytoscape 2.8: new features for data integration and network visualization,” Bioinformatics, vol. 27, no. 3, pp. 431–432, 2011.
- P. Shannon, A. Markiel, O. Ozier et al., “Cytoscape: a software environment for integrated models of biomolecular interaction networks,” Genome Research, vol. 13, no. 11, pp. 2498–2504, 2003.
- B. H. Junker, D. Koschützki, and F. Schreiber, “Exploration of biological network centralities with CentiBiN,” BMC Bioinformatics, vol. 7, article 219, 2006.
- C. Ma, L. Wang, and X. Q. Xie, “GPU accelerated chemical similarity calculation for compound library comparison,” Journal of Chemical Information and Modeling, vol. 51, no. 7, pp. 1521–1527, 2011.
- P. Willett, “Chemical similarity searching,” Journal of Chemical Information and Computer Sciences, vol. 38, pp. 983–996, 1998.
- T. Aittokallio and B. Schwikowski, “Graph-based methods for analysing networks in cell biology,” Briefings in Bioinformatics, vol. 7, no. 3, pp. 243–255, 2006.
- E. Estrada, “Quantifying network heterogeneity,” Physical Review E, vol. 82, Article ID 066102, 2010.
- D. J. Klein, “Centrality measure in graphs,” Journal of Mathematical Chemistry, vol. 47, no. 4, pp. 1209–1223, 2010.
- P. Hage and F. Harary, “Eccentricity and centrality in networks,” Social Networks, vol. 17, no. 1, pp. 57–63, 1995.
- M. Kuhn, M. Campillos, I. Letunic, L. J. Jensen, and P. Bork, “A side effect resource to capture phenotypic effects of drugs,” Molecular Systems Biology, vol. 6, article 343, 2010.
- D. Cunningham, C. J. Bradley, G. J. Forrest et al., “A randomized trial of oral nabilone and prochlorperazine compared to intravenous metoclopramide and dexamethasone in the treatment of nausea and vomiting induced by chemotherapy regimens containing cisplatin or cisplatin analogues,” European Journal of Cancer and Clinical Oncology, vol. 24, no. 4, pp. 685–689, 1988.
- A. Niiranen and K. Mattson, “Antiemetic efficacy of nabilone and dexamethasone: a randomized study of patients with lung cancer receiving chemotherapy,” American Journal of Clinical Oncology, vol. 10, no. 4, pp. 325–329, 1987.
- L. H. Einhorn, C. Nagy, B. Furnas, and S. D. Williams, “Nabilone: an effective antiemetic in patients receiving cancer chemotherapy,” Journal of Clinical Pharmacology, vol. 21, no. 8-9, pp. 64S–69S, 1981.
- Y. Yang, J. Wolfram, H. Shen, et al., “Hesperetin: an inhibitor of the transforming growth factor-beta (TGF-beta) signaling pathway,” European Journal of Medicinal Chemistry, vol. 58, pp. 390–395, 2012.
- B. Zarebczan, S. N. Pinchot, M. Kunnimalaiyaan, and H. Chen, “Hesperetin, a potential therapy for carcinoid cancer,” American Journal of Surgery, vol. 201, no. 3, pp. 329–333, 2011.
- L. Ye, F. L. Chan, S. Chen, et al., “The citrus flavonone hesperetin inhibits growth of aromatase-expressing MCF-7 tumor in ovariectomized athymic mice,” Journal of Nutritional Biochemistry, vol. 23, pp. 1230–1237, 2012.
- F. Gaita, E. Richiardi, and M. Bocchiardo, “Short- and long-term effects of propafenone in ventricular arrhythmias,” International Journal of Cardiology, vol. 13, no. 2, pp. 163–170, 1986.
- I. Vassiliadis, P. Papoutsakis, I. Kallikazaros, and C. Stefanadis, “Propafenone in the prevention of non-ventricular arrhythmias associated with the Wolff-Parkinson-White syndrome,” International Journal of Cardiology, vol. 27, no. 1, pp. 63–70, 1990.
- K. Sampi, M. Hozumi, R. Kumai, Y. Honma, and M. Sakurai, “Differentiation of blasts from patients in myeloid crisis of chronic myelogenous leukemia by in-vivo and in-vitro plicamycin treatment,” Leukemia Research, vol. 11, no. 12, pp. 1089–1092, 1987.
- J. P. Dutcher, D. Coletti, E. Paietta, and P. H. Wiernik, “A pilot study of alpha-interferon and plicamycin for accelerated phase of chronic myeloid leukemia,” Leukemia Research, vol. 21, no. 5, pp. 375–380, 1997.
- S. J. Wimalawansa, “Dramatic response to plicamycin in a patient with severe Paget's disease refractory to calcitonin and pamidronate,” Seminars in Arthritis and Rheumatism, vol. 23, no. 4, 267 pages, 1994.
- R. D. Verschoyle, P. Greaves, K. Patel et al., “Evaluation of the cancer chemopreventive efficacy of silibinin in genetic mouse models of prostate and intestinal carcinogenesis: relationship with silibinin levels,” European Journal of Cancer, vol. 44, no. 6, pp. 898–906, 2008.
- F. Yin, J. Liu, X. Ji, Y. Wang, J. Zidichouski, and J. Zhang, “Silibinin: a novel inhibitor of Aβ aggregation,” Neurochemistry International, vol. 58, no. 3, pp. 399–403, 2011.
- J. Y. Wang, C. C. Chang, C. C. Chiang, et al., “Silibinin suppresses the maintenance of colorectal cancer stem-like cells by inhibiting PP2A/AKT/mTOR pathways,” Journal of Cellular Biochemistry, vol. 113, pp. 1733–1743, 2012.
- M. Dastpeyman, N. Motamed, K. Azadmanesh, et al., “Inhibition of silibinin on migration and adhesion capacity of human highly metastatic breast cancer cell line, MDA-MB-231, by evaluation of beta1-integrin and downstream molecules, Cdc42, Raf-1 and D4GDI,” Medical Oncology, vol. 29, pp. 2512–2518, 2012.
- W. Ai, Y. Zhang, Q. Z. Tang et al., “Silibinin attenuates cardiac hypertrophy and fibrosis through blocking EGFR-dependent signaling,” Journal of Cellular Biochemistry, vol. 110, no. 5, pp. 1111–1122, 2010.
- A. Tyagi, R. P. Singh, K. Ramasamy et al., “Growth inhibition and regression of lung tumors by silibinin: modulation of angiogenesis by macrophage-associated cytokines and nuclear factor-κB and signal transducers and activators of transcription 3,” Cancer Prevention Research, vol. 2, no. 1, pp. 74–83, 2009.
- B. Cheng, H. Gong, X. Li, et al., “Silibinin inhibits the toxic aggregation of human islet amyloid polypeptide,” Biochemical and Biophysical Research Communications, vol. 419, pp. 495–499, 2012.
- R. Barcena, A. Moreno, M. A. Rodriguez-Gandia, et al., “Safety and anti-HCV effect of prolonged intravenous silibinin in HCV genotype 1 subjects in the immediate liver transplant period,” Journal of Hepatology, vol. 58, pp. 421–426, 2013.
- L. Li, J. Zeng, Y. Gao, and D. He, “Targeting silibinin in the antiproliferative pathway,” Expert Opinion on Investigational Drugs, vol. 19, no. 2, pp. 243–255, 2010.
- X. Liu, H. Jiang, and H. Li, “SHAFTS: a hybrid approach for 3D molecular similarity calculation—1. Method and assessment of virtual screening,” Journal of Chemical Information and Modeling, vol. 51, pp. 2372–2385, 2011.
- R. A. Copeland, “The dynamics of drug-target interactions: drug-target residence time and its impact on efficacy and safety,” Expert Opinion on Drug Discovery, vol. 5, no. 4, pp. 305–310, 2010.
- H. Bisgin, Z. Liu, H. Fang, et al., “Ming FDA drug labels using an unsupervised learning technique-topic modeling,” BMC Bioinformatics, vol. 12, article S11, 2011.
- K. D. Shetty and S. R. Dalal, “Using information mining of the medical literature to improve drug safety,” Journal of the American Medical Informatics Association, vol. 18, pp. 668–674, 2011.
- E. Lounkine, M. J. Keiser, S. Whitebread, et al., “Large-scale prediction and testing of drug activity on side-effect targets,” Nature, vol. 486, pp. 361–367, 2012.
- M. J. Keiser, V. Setola, J. J. Irwin et al., “Predicting new molecular targets for known drugs,” Nature, vol. 462, no. 7270, pp. 175–181, 2009.
- M. J. Keiser, B. L. Roth, B. N. Armbruster, P. Ernsberger, J. J. Irwin, and B. K. Shoichet, “Relating protein pharmacology by ligand chemistry,” Nature Biotechnology, vol. 25, no. 2, pp. 197–206, 2007.
- J. Hert, M. J. Keiser, J. J. Irwin, T. I. Oprea, and B. K. Shoichet, “Quantifying the relationships among drug classes,” Journal of Chemical Information and Modeling, vol. 48, no. 4, pp. 755–765, 2008.
- K. Azzaoui, J. Hamon, B. Faller et al., “Modeling promiscuity based on in vitro safety pharmacology profiling data,” ChemMedChem, vol. 2, no. 6, pp. 874–880, 2007.