A Practical Guide for Exploring Opportunities of Repurposing Drugs for CNS Diseases in Systems Biology

  • Hongkang Mei
  • Gang Feng
  • Jason Zhu
  • Simon Lin
  • Yang Qiu
  • Yue Wang
  • Tian Xia
Part of the Methods in Molecular Biology book series (MIMB, volume 1303)


Systems biology has shown its potential in facilitating pathway-focused therapy development for central nervous system (CNS) diseases. An integrated network can be utilized to explore the multiple disease mechanisms and to discover repositioning opportunities. This review covers current therapeutic gaps for CNS diseases and the role of systems biology in pharmaceutical industry. We conclude with a Multiple Level Network Modeling (MLNM) example to illustrate the great potential of systems biology for CNS diseases. The system focuses on the benefit and practical applications in pathway centric therapy and drug repositioning.

Key words

Systems biology Disease network Multiple level network modeling (MLNM) Drug repositioning Pharmacology 


  1. 1.
    Yang Y, Adelstein SJ, Kassis AI (2009) Target discovery from data mining approaches. Drug Discov Today 14:147–154PubMedCrossRefGoogle Scholar
  2. 2.
    Kola I, Landis J (2004) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3:711–715PubMedCrossRefGoogle Scholar
  3. 3.
    Azmi AS, Wang Z, Philip PA et al (2010) Proof of concept: network and systems biology approaches aid in the discovery of potent anticancer drug combinations. Mol Cancer Ther 9:3137–3144PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    Stein A, Pache RA, Bernado P et al (2009) Dynamic interactions of proteins in complex networks: a more structured view. FEBS J 276:5390–5405PubMedCrossRefGoogle Scholar
  5. 5.
    Li Y, Agarwal P (2009) A pathway-based view of human diseases and disease relationships. PLoS One 4:e4346PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Goh KI, Cusick ME, Valle D et al (2007) The human disease network. Proc Natl Acad Sci U S A 104:8685–8690PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Loscalzo J, Kohane I, Barabasi AL (2007) Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Mol Syst Biol 3:124PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Hu G, Agarwal P (2009) Human disease-drug network based on genomic expression profiles. PLoS One 4:e6536PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Stegmaier P, Krull M, Voss N et al (2010) Molecular mechanistic associations of human diseases. BMC Syst Biol 4:124PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Vidal M, Cusick ME, Barabasi AL (2011) Interactome networks and human disease. Cell 144:986–998PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Hidalgo CA, Blumm N, Barabasi AL, Christakis NA (2009) A dynamic network approach for the study of human phenotypes. PLoS Comput Biol 5:e1000353PubMedCentralPubMedCrossRefGoogle Scholar
  12. 12.
    Arrell DK, Terzic A (2010) Network systems biology for drug discovery. Clin Pharmacol Ther 88:120–125PubMedCrossRefGoogle Scholar
  13. 13.
    Finkbeiner S (2010) Bridging the valley of death of therapeutics for neurodegeneration. Nat Med 16:1227–1232PubMedCrossRefGoogle Scholar
  14. 14.
    Flordellis CS, Manolis AS, Paris H, Karabinis A (2006) Rethinking target discovery in polygenic diseases. Curr Top Med Chem 6:1791–1798PubMedCrossRefGoogle Scholar
  15. 15.
    Brunden KR, Trojanowski JQ, Lee VM (2009) Advances in tau-focused drug discovery for Alzheimer’s disease and related tauopathies. Nat Rev Drug Discov 8:783–793PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    Decision Resources (2010) Target product profiles 2009: physician insights on key attributes: Parkinson’s disease (report). Chapter 1. Etiology and pathophysiology. Decision Resources Inc http://decisionresources.com/Products-and-Services/;  http://www.businesswire.com/news/home/20100311005839/en/Research-Markets-Target-Product-Profiles-2009-Physician#.U77e0rFHSf0
  17. 17.
    Simunovic F, Yi M, Wang Y et al (2009) Gene expression profiling of substantia nigra dopamine neurons: further insights into Parkinson’s disease pathology. Brain 132:1795–1809PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    Zhang X, Zhou JY, Chin MH et al (2010) Region-specific protein abundance changes in the brain of MPTP-induced Parkinson’s disease mouse model. J Proteome Res 9:1496–1509PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    Skovronsky DM, Lee VM, Trojanowski JQ (2006) Neurodegenerative diseases: new concepts of pathogenesis and their therapeutic implications. Annu Rev Pathol 1:151–170PubMedCrossRefGoogle Scholar
  20. 20.
    Qu XA, Gudivada RC, Jegga AG et al (2009) Inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships. BMC Bioinformatics 10(Suppl 5):S4PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Haupt VJ, Schroeder M (2011) Old friends in new guise: repositioning of known drugs with structural bioinformatics. Brief Bioinform 12:312–326PubMedCrossRefGoogle Scholar
  22. 22.
    Ha S, Seo YJ, Kwon MS et al (2008) IDMap: facilitating the detection of potential leads with therapeutic targets. Bioinformatics 24:1413–1415PubMedCrossRefGoogle Scholar
  23. 23.
    Chiang AP, Butte AJ (2009) Systematic evaluation of drug-disease relationships to identify leads for novel drug uses. Clin Pharmacol Ther 86:507–510PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Barabasi AL, Gulbahce N, Loscalzo J (2011) Network medicine: a network-based approach to human disease. Nat Rev Genet 12:56–68PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Pujana MA, Han JD, Starita LM et al (2007) Network modeling links breast cancer susceptibility and centrosome dysfunction. Nat Genet 39:1338–1349PubMedCrossRefGoogle Scholar
  26. 26.
    Omenn GS (2011) An omics perspective on cancer research. Expert Rev Proteomics 8:147–148CrossRefGoogle Scholar
  27. 27.
    Auffray C, Adcock IM, Chung KF et al (2010) An integrative systems biology approach to understanding pulmonary diseases. Chest 137:1410–1416PubMedCrossRefGoogle Scholar
  28. 28.
    Soler-Lopez M, Zanzoni A, Lluis R et al (2011) Interactome mapping suggests new mechanistic details underlying Alzheimer’s disease. Genome Res 21:364–376PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    de Chassey B, Navratil V, Tafforeau L et al (2008) Hepatitis C virus infection protein network. Mol Syst Biol 4:230PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    Diez D, Wheelock AM, Goto S et al (2010) The use of network analyses for elucidating mechanisms in cardiovascular disease. Mol Biosyst 6:289–304PubMedCrossRefGoogle Scholar
  31. 31.
    Tanaka T, Oka T, Shimada Y et al (2008) Pharmacogenomics of cardiovascular pharmacology: pharmacogenomic network of cardiovascular disease models. J Pharmacol Sci 107:8–14PubMedCrossRefGoogle Scholar
  32. 32.
    Hwang S, Son SW, Kim SC et al (2008) A protein interaction network associated with asthma. J Theor Biol 252:722–731PubMedCrossRefGoogle Scholar
  33. 33.
    Fedeles SV, Tian X, Gallagher AR et al (2011) A genetic interaction network of five genes for human polycystic kidney and liver diseases defines polycystin-1 as the central determinant of cyst formation. Nat Genet 43:639–647PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    Kaimal V, Sardana D, Bardes EE et al (2011) Integrative systems biology approaches to identify and prioritize disease and drug candidate genes. Methods Mol Biol 700:241–259PubMedCrossRefGoogle Scholar
  35. 35.
    Elmer GI, Kafkafi N (2009) Drug discovery in psychiatric illness: mining for gold. Schizophr Bull 35:287–292PubMedCentralPubMedCrossRefGoogle Scholar
  36. 36.
    Pujol A, Mosca R, Farres J, Aloy P (2010) Unveiling the role of network and systems biology in drug discovery. Trends Pharmacol Sci 31:115–123PubMedCrossRefGoogle Scholar
  37. 37.
    Wu Z, Zhao XM, Chen L (2010) A systems biology approach to identify effective cocktail drugs. BMC Syst Biol 4(Suppl 2):S7PubMedCentralPubMedCrossRefGoogle Scholar
  38. 38.
    Fliri AF, Loging WT, Volkmann RA (2010) Cause-effect relationships in medicine: a protein network perspective. Trends Pharmacol Sci 31:547–555PubMedCrossRefGoogle Scholar
  39. 39.
    Geva-Zatorsky N, Dekel E, Cohen AA et al (2010) Protein dynamics in drug combinations: a linear superposition of individual-drug responses. Cell 140:643–651PubMedCrossRefGoogle Scholar
  40. 40.
    Sardana D, Zhu C, Zhang M et al (2011) Drug repositioning for orphan diseases. Brief Bioinform 12:346–356PubMedCrossRefGoogle Scholar
  41. 41.
    Dimond PF (2010) Drug repositioning gains in popularity. Gen Eng Biotechnol News 30; http://www.genengnews.com/gen-articles/drug-repositioning-gains-in-popularity/3263/
  42. 42.
    Deftereos SN, Andronis C, Friedla EJ, Persidis A (2011) Drug repurposing and adverse event prediction using high-throughput literature analysis. Wiley Interdiscip Rev Syst Biol Med 3:323–334PubMedCrossRefGoogle Scholar
  43. 43.
    Iorio F, Bosotti R, Scacheri E et al (2010) Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc Natl Acad Sci U S A 107:14621–14626PubMedCentralPubMedCrossRefGoogle Scholar
  44. 44.
    Kotelnikova E, Yuryev A, Mazo I, Daraselia N (2010) Computational approaches for drug repositioning and combination therapy design. J Bioinform Comput Biol 8:593–606PubMedCrossRefGoogle Scholar
  45. 45.
    Dubus E, Ijjaali I, Barberan O, Petitet F (2009) Drug repositioning using in silico compound profiling. Future Med Chem 1:1723–1736PubMedCrossRefGoogle Scholar
  46. 46.
    von Eichborn J, Murgueitio MS, Dunkel M et al (2011) PROMISCUOUS: a database for network-based drug-repositioning. Nucleic Acids Res 39:D1060–D1066CrossRefGoogle Scholar
  47. 47.
    Luo H, Chen J, Shi L et al (2011) DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical-protein interactome. Nucleic Acids Res 39(Web Server issue):W492–W498PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Keiser MJ, Setola V, Irwin JJ et al (2009) Predicting new molecular targets for known drugs. Nature 462:175–181PubMedCentralPubMedCrossRefGoogle Scholar
  49. 49.
    Cockell SJ, Weile J, Lord P et al (2010) An integrated dataset for in silico drug discovery. J Integr Bioinform 7:116Google Scholar
  50. 50.
    Wallach I, Jaitly N, Lilien R (2010) A structure-based approach for mapping adverse drug reactions to the perturbation of underlying biological pathways. PLoS One 5:e12063PubMedCentralPubMedCrossRefGoogle Scholar
  51. 51.
    Yang L, Chen J, He L (2009) Harvesting candidate genes responsible for serious adverse drug reactions from a chemical-protein interactome. PLoS Comput Biol 5:e1000441PubMedCentralPubMedCrossRefGoogle Scholar
  52. 52.
    Campillos M, Kuhn M, Gavin AC et al (2008) Drug target identification using side-effect similarity. Science 321:263–266PubMedCrossRefGoogle Scholar
  53. 53.
    Xie L, Evangelidis T, Bourne PE (2011) Drug discovery using chemical systems biology: weak inhibition of multiple kinases may contribute to the anti-cancer effect of nelfinavir. PLoS Comput Biol 7:e1002037PubMedCentralPubMedCrossRefGoogle Scholar
  54. 54.
    Feng G, Du P, Krett NL et al (2010) A collection of bioconductor methods to visualize gene-list annotations. BMC Res Notes 3:10PubMedCentralPubMedCrossRefGoogle Scholar
  55. 55.
    Smoot ME, Ono K, Ruscheinski J et al (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27:431–432PubMedCentralPubMedCrossRefGoogle Scholar
  56. 56.
    Capell K (2009) The FDA O.K.’s Novartis Ilaris. Business Week. http://www.businessweek.com/bwdaily/dnflash/content/jun2009/db20090618_060721.htm
  57. 57.
    Smith B, Ashburner M, Rosse C et al (2007) The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25:1251–1255PubMedCentralPubMedCrossRefGoogle Scholar
  58. 58.
    Brazma A, Krestyaninova M, Sarkans U (2006) Standards for systems biology. Nat Rev Genet 7:593–605PubMedCrossRefGoogle Scholar
  59. 59.
    Antezana E, Kuiper M, Mironov V (2009) Biological knowledge management: the emerging role of the Semantic Web technologies. Brief Bioinform 10:392–407PubMedCrossRefGoogle Scholar
  60. 60.
    Klipp E, Liebermeister W, Helbig A et al (2007) Systems biology standards – the community speaks. Nat Biotechnol 25:390–391PubMedCrossRefGoogle Scholar
  61. 61.
    Shannon P, Markiel A, Ozier O et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504PubMedCentralPubMedCrossRefGoogle Scholar
  62. 62.
    Wu X, Jiang R, Zhang MQ, Li S (2008) Network-based global inference of human disease genes. Mol Syst Biol 4:189PubMedCentralPubMedCrossRefGoogle Scholar
  63. 63.
    Zhao S, Li S (2010) Network-based relating pharmacological and genomic spaces for drug target identification. PLoS One 5:e11764PubMedCentralPubMedCrossRefGoogle Scholar
  64. 64.
    Yao X, Hao H, Li Y, Li S (2011) Modularity-based credible prediction of disease genes and detection of disease subtypes on the phenotype-gene heterogeneous network. BMC Syst Biol 5:79PubMedCentralPubMedCrossRefGoogle Scholar
  65. 65.
    Suthram S, Dudley JT, Chiang AP et al (2010) Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. PLoS Comput Biol 6:e1000662PubMedCentralPubMedCrossRefGoogle Scholar
  66. 66.
    Mullard A (2011) 2010 FDA drug approvals. Nat Rev Drug Discov 10:82–85PubMedCrossRefGoogle Scholar
  67. 67.
    Rajasethupathy P, Vayttaden SJ, Bhalla US (2005) Systems modeling: a pathway to drug discovery. Curr Opin Chem Biol 9:400–406PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Hongkang Mei
    • 1
  • Gang Feng
    • 2
  • Jason Zhu
    • 1
  • Simon Lin
    • 2
  • Yang Qiu
    • 1
  • Yue Wang
    • 3
  • Tian Xia
    • 3
  1. 1.Informatics and Structure BiologyR&D China, GlaxoSmithKlineShanghaiChina
  2. 2.Biomedical Informatics CenterNorthwestern University Clinical and Translational Sciences InstituteChicagoUSA
  3. 3.Department of Electronics and Information EngineeringHuazhong University of Science and TechnologyWuhanChina

Personalised recommendations