DOI QR코드

DOI QR Code

Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine

  • Lee, Soojin (Department of Physiology, College of Korean Medicine, Sangji University)
  • Received : 2015.08.19
  • Accepted : 2015.08.31
  • Published : 2015.09.30

Abstract

Objectives: Systems biology is a novel subject in the field of life science that aims at a systems' level understanding of biological systems. Because of the significant progress in high-throughput technologies and molecular biology, systems biology occupies an important place in research during the post-genome era. Methods: The characteristics of systems biology and its applicability to traditional medicine research have been discussed from three points of view: data and databases, network analysis and inference, and modeling and systems prediction. Results: The existing databases are mostly associated with medicinal herbs and their activities, but new databases reflecting clinical situations and platforms to extract, visualize and analyze data easily need to be constructed. Network pharmacology is a key element of systems biology, so addressing the multi-component, multi-target aspect of pharmacology is important. Studies of network pharmacology highlight the drug target network and network target. Mathematical modeling and simulation are just in their infancy, but mathematical modeling of dynamic biological processes is a central aspect of systems biology. Computational simulations allow structured systems and their functional properties to be understood and the effects of herbal medicines in clinical situations to be predicted. Conclusion: Systems biology based on a holistic approach is a pivotal research methodology for understanding the mechanisms of traditional medicine. If systems biology is to be incorporated into traditional medicine, computational technologies and holistic insights need to be integrated.

Acknowledgement

Supported by : National Research Foundation of Korea

References

  1. Barabasi AL, Gulbahce N, Loscalzo J. Network medicine:a network-based approach to human disease. Nat Rev Genet. 2011;12(1):56-68. https://doi.org/10.1038/nrg2918
  2. Calvete JJ, Sanz L, Pla D, Lomonte B, Gutierrez JM. Omics meets biology: application to the design and preclinical assessment of antivenoms. Toxins. 2014;6(12):3388-405. https://doi.org/10.3390/toxins6123388
  3. Kitano H. Looking beyond the details: a rise in system-oriented approaches in genetics and molecular biology. Curr Genet. 2002;41(1):1-10. https://doi.org/10.1007/s00294-002-0285-z
  4. Normile D. Asian medicine. the new face of traditional Chinese medicine. Science. 2003;299(5604):188-90. https://doi.org/10.1126/science.299.5604.188
  5. Noble D. Could there be a synthesis between Western and Oriental medicine, and with sasang constitutional medicine in particular?. Evid Based Complement Alternat Med. 2009;6(S1):5-10. https://doi.org/10.1093/ecam/nep101
  6. Cassman M, Arkin A, Doyle F, Katagiri F, Lauffenburger D, Stokes C. Systems biology - international research and development. Dordrecht: Netherlands Springer; 2007. p. 15, 47-9.
  7. Zhou X, Peng Y, Liu B. Text mining for traditional Chinese medical knowledge discovery: a survey. J Biomed Inform. 2010;43(4):650-60. https://doi.org/10.1016/j.jbi.2010.01.002
  8. Fan W. The traditional Chinese medical literature analysis and retrieval system (TCMLARS) and its application. Inspel. 2001;35(3):147-56.
  9. Korean traditional knowledge portal [Internet]. Seoul:Korean Intellectual Property Office; 2011 [cited 2015 Aug 10]. Available from: http://www.koreantk.com/.
  10. Knowledge of Oriental medicine web service [Internet]. Daejeon: KIOM; 2007 [cited 2015 Aug 10]. Available from: http://jisik.kiom.re.kr/.
  11. Wang JF, Zhou H, Han LY, Chen X, Chen YZ, Cao ZW. Traditional Chinese medicine information database. Clin Pharmacol Ther. 2005;78(1):92-3. https://doi.org/10.1016/j.clpt.2005.03.010
  12. 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;41:1089-95. https://doi.org/10.1093/nar/gks1100
  13. Chen CY. TCM database@Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico. PLoS One. 2011;6(1):e15939. https://doi.org/10.1371/journal.pone.0015939
  14. Ru J, Li P, Wang J, Zhou W, Li B, Huang C, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform. 2014;6(13):1-6. https://doi.org/10.1186/1758-2946-6-1
  15. Huang J, Wang JH. CEMTDD: Chinese ethnic minority traditional drug database. Apoptosis. 2014;19(9):1419-20. https://doi.org/10.1007/s10495-014-1011-2
  16. Kim SK, Nam SJ, Jang HC, Kim AN, Lee JJ. TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine. BMC Complement Altern Med. 2015;15(218):1-8. https://doi.org/10.1186/s12906-015-0520-z
  17. Tao W, Li B, Gao S, Bai Y, Shar PA, Zhang W, et al. CancerHSP: anticancer herbs database of systems pharmacology. Sci Rep. 2015;5(11481):1-6.
  18. Zhou X, Chen S, Liu B, Zhang R, Wang Y, Li P, et al. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support. Artif Intell Med. 2010;48(2-3):139-52. https://doi.org/10.1016/j.artmed.2009.07.012
  19. Li S, Zhang B. Traditional Chinese medicine network pharmacology: theory, methodology and application. Chin J Nat Med. 2013;11(S2):110-20.
  20. Li S, Zhang B, Jiang D, Wei Y, Zhang N. Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae. BMC Bioinformatics. 2010;11(S11):1-12. https://doi.org/10.1186/1471-2105-11-1
  21. Li S, Zhang ZQ, Wu LJ, Zhang XG, Li YD, Wang YY. Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network. IET Syst Biol. 2007;1(1):51-60. https://doi.org/10.1049/iet-syb:20060032
  22. Zhang B, Wang X, Li S. An integrative platform of TCM network pharmacology and its application on a herbal formula, qing-luo-yin. Evid Based Complement Alternat Med. 2013;2013:ID456747.
  23. Yue QX, Cao ZW, Guan SH, Liu XH, Tao L, Wu WY, et al. Proteomics characterization of the cytotoxicity mechanism of ganoderic acid D and computer-automated estimation of the possible drug target network. Mol Cell Proteomics. 2008;7(5):949-61. https://doi.org/10.1074/mcp.M700259-MCP200
  24. Gu J, Zhang H, Chen L, Xu S, Yuan G, Xu X. Drug-target network and polypharmacology studies of a traditional Chinese medicine for type II diabetes mellitus. Comput Biol Chem. 2011;35(5):293-7. https://doi.org/10.1016/j.compbiolchem.2011.07.003
  25. Wang X, Xu X, Tao W, Li Y, Wang Y, Yang L. A systems biology approach to uncovering pharmacological synergy in herbal medicines with applications to cardiovascular disease. Evid Based Complement Alternat Med. 2012;2012:ID519031.
  26. Liu H, Wang J, Zhou W, Wang Y, Yang L. Systems approaches and polypharmacology for drug discovery from herbal medicines: an example using licorice. J Ethnopharmacol. 2013;146(3):773-93. https://doi.org/10.1016/j.jep.2013.02.004
  27. Zhang J, Li Y, Chen X, Pan Y, Zhang S, Wang Y. Systems pharmacology dissection of multi-scale mechanisms of action for herbal medicines in stroke treatment and prevention. PLoS One. 2014;9(8):e102506. https://doi.org/10.1371/journal.pone.0102506
  28. Jiang M, Lu C, Chen G, Xiao C, Zha Q, Niu X, et al. Understanding the molecular mechanism of interventions in treating rheumatoid arthritis patients with corresponding traditional Chinese medicine patterns based on bioinformatics approach. Evid Based Complement Alternat Med. 2012;2012:ID129452.
  29. Gu H, Ma L, Ren Y, He W, Wang Y, Qiao Y. Exploration of the mechanism of pattern-specific treatments in coronary heart disease with network pharmacology approach. Comput Biol Med. 2014;51:198-204. https://doi.org/10.1016/j.compbiomed.2014.05.003
  30. Noble D. A modification of the hodgkin-huxley equations applicable to purkinje fibre action and pace-maker potentials. J Physiol. 1962;160(2):317-52. https://doi.org/10.1113/jphysiol.1962.sp006849
  31. Rodriguez B, Burrage K, Gavaghan D, Grau V, Kohl P, Noble D. The systems biology approach to drug development: application to toxicity assessment of cardiac drugs. Clin Pharmacol Ther. 2010;88(1):130-4. https://doi.org/10.1038/clpt.2010.95
  32. Bottino D, Penland RC, Stamps A, Traebert M, Dumotier B, Georgiva A, et al. Preclinical cardiac safety assessment of pharmaceutical compounds using an integrated systems-based computer model of the heart. Prog Biophys Mol Biol. 2006;90(1-3):414-43. https://doi.org/10.1016/j.pbiomolbio.2005.06.006
  33. Wang RR, Li N, Zhang YH, Ran YQ, Pu JL. The effects of paeoniflorin monomer of a Chinese herb on cardiac ion channels. Chin Med J. 2011;124(19):3105-11.
  34. Zhang GQ, Hao XM, Zhou PA, Wu CH. Effect of paeonol on L-type calcium channel in rat ventricular myocytes. Methods Find Exp Clin Pharmacol. 2003;25(4):281-5. https://doi.org/10.1358/mf.2003.25.4.769676
  35. Lee S, Noble P, Ma Y, Earm Y, Noble D, editors. Potential antiarrhythmic effects of paeoniflorin and paeonol extracted from the paeoniaceae family. The 36th international union of physiological sciences (IUPS); 2013 Jul 21-26; Birmingham, UK. London: IUPS; 2013. 275 p.
  36. Lee S. [A computer simulation study of the potential anti-arrhythmic properties of paeonol]. Korean J Orient Physiol Pathol. 2015;29(4):305-12. Korean. https://doi.org/10.15188/kjopp.2015.08.29.4.305
  37. Noble P, Tasaki K, Gavaghan D, Miram G, Noble D, editors. Simulation of the anti-arrhythmic properties of herbal remedics. The 36th International Union of Physiological Sciences (IUPS); 2013 Jul 21-26; Birmingham, UK. London: IUPS; 2013. 358 p.
  38. Hunter P, Coveney PV, de Bono B, Diaz V, Fenner J, Frangi AF, et al. A vision and strategy for the virtual physiological human in 2010 and beyond. Philos Trans A Math Phys Eng Sci. 2010;368(1920):2595-614. https://doi.org/10.1098/rsta.2010.0048
  39. de Bono B, Hunter P. Integrating knowledge representation and quantitative modelling in physiology. Biotechnol J. 2012;7(8):958-72. https://doi.org/10.1002/biot.201100304
  40. Fang YC, Huang HC, Chen HH, Juan HF. TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining. BMC Complement Altern Med. 2008;8(58):1-11. https://doi.org/10.1186/1472-6882-8-1
  41. Zhang A, Sun H, Yang B, Wang X. Predicting new molecular targets for rhein using network pharmacology. BMC Syst Biol. 2012;6(20):1-8. https://doi.org/10.1186/1752-0509-6-1
  42. Fang Z, Lu B, Liu M, Zhang M, Yi Z, Wen C, et al. Evaluating the pharmacological mechanism of Chinese medicine si-wu-tang through multi-level data integration. PLoS One. 2013;8(11):e72334. https://doi.org/10.1371/journal.pone.0072334
  43. Li B, Tao W, Zheng C, Shar PA, Huang C, Fu Y, et al. Systems pharmacology-based approach for dissecting the addition and subtraction theory of traditional Chinese medicine: an example using xiao-chaihu-decoction and da-chaihu-decoction. Comput Biol Med. 2014;53:19-29. https://doi.org/10.1016/j.compbiomed.2014.05.007
  44. Zhang J, Li Y, Chen SS, Zhang L, Wang J, Yang Y, et al. Systems pharmacology dissection of the anti-inflammatory mechanism for the medicinal herb Folium eriobotryae. Int J Mol Sci. 2015;16(2):2913-41. https://doi.org/10.3390/ijms16022913
  45. An L, Feng F. Network pharmacology-based antioxidant effect study of zhi-zi-da-huang decoction for alcoholic liver disease. Evid Based Complement Alternat Med. 2015;2015:ID492470.
  46. Li Y, Zhang J, Zhang L, Chen X, Pan Y, Chen SS, et al. Systems pharmacology to decipher the combinational anti-migraine effects of Tianshu formula. J Ethnopharmacol. 2015;S0378-8741(15):30056-8.
  47. Korea Institute of Science and Technology Evaluation and Planning. [Trend of technology and policy in Korean medicine]. Seoul: KISTEP; 2010. 30 p. Korean.

Cited by

  1. The Third International Genomic Medicine Conference (3rd IGMC, 2015): overall activities and outcome highlights vol.17, pp.S9, 2016, https://doi.org/10.1186/s12864-016-3085-4
  2. The Need for Systems Tools in the Practice of Clinical Medicine vol.20, pp.1, 2017, https://doi.org/10.1002/sys.21374
  3. Synergistic Effects of Chinese Herbal Medicine: A Comprehensive Review of Methodology and Current Research vol.7, 2016, https://doi.org/10.3389/fphar.2016.00201
  4. Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology vol.17, pp.5, 2016, https://doi.org/10.3390/ijms17050632
  5. A network pharmacology-based strategy deciphers the underlying molecular mechanisms of Qixuehe Capsule in the treatment of menstrual disorders vol.12, pp.1, 2017, https://doi.org/10.1186/s13020-017-0145-x
  6. Willd. in the Treatment of Gastric Cancer vol.2018, pp.1741-4288, 2018, https://doi.org/10.1155/2018/7802639