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A robustness-based approach to systems-oriented drug design

Nature Reviews Drug Discovery volume 6, pages 202210 (2007) | Download Citation

Abstract

Many potential drugs that specifically target a particular protein considered to underlie a given disease have been found to be less effective than hoped, or to cause significant side effects. The intrinsic robustness of living systems against various perturbations is a key factor that prevents such compounds from being successful. By studying complex network systems and reformulating control and communication theories that are well established in engineering, a theoretical foundation for a systems-oriented approach to more effectively control the robustness of living systems, particularly at the cellular level, could be developed. Here, I use examples that are based on existing drugs to illustrate the concept of robustness, and then discuss how a greater consideration of the importance of robustness could influence the design of new drugs that will be intended to control complex systems.

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References

  1. 1.

    Drug research: myths, hype and reality. Nature Rev. Drug Discov. 2, 665–668 (2003).

  2. 2.

    Modern biomedical research: an internally self-consistent universe with little contact with medical reality? Nature Rev. Drug Discov. 2, 151–154 (2003).

  3. 3.

    Can cell systems biology rescue drug discovery? Nature Rev. Drug Discov. 4, 461–467 (2005).

  4. 4.

    , & Systems biology in drug discovery. Nature Biotech. 22, 1253–1259 (2004).

  5. 5.

    & The impact of systems approaches on biological problems in drug discovery. Nature Biotech. 22, 1215–1217 (2004).

  6. 6.

    & Rescuing drug discovery: in vivo systems pathology and systems pharmacology. Nature Rev. Drug Discov. 4, 961–967 (2005).

  7. 7.

    , & Multicomponent therapeutics for networked systems. Nature Rev. Drug Discov. 4, 71–78 (2005).

  8. 8.

    The concept of synthetic lethality in the context of anticancer therapy. Nature Rev. Cancer 5, 689–698 (2005).

  9. 9.

    , , & The challenges of modeling mammalian biocomplexity. Nature Biotech. 22, 1268–1274 (2004).

  10. 10.

    , , & Metabolite profiling: from diagnostics to systems biology. Nature Rev. Mol. Cell Biol. 5, 763–769 (2004).

  11. 11.

    & Understanding 'global' systems biology: metabonomics and the continuum of metabolism. Nature Rev. Drug Discov. 2, 668–676 (2003).

  12. 12.

    et al. Metabolic footprinting and systems biology: the medium is the message. Nature Rev. Microbiol. 3, 557–565 (2005).

  13. 13.

    Biological robustness. Nature Rev. Genet. 5, 826–837 (2004).

  14. 14.

    , , , & Robustness of cellular functions. Cell 118, 675–685 (2004).

  15. 15.

    & Reverse engineering of biological complexity. Science 295, 1664–1669 (2002).

  16. 16.

    & Bow ties, metabolism and disease. Trends Biotechnol. 22, 446–450 (2004).

  17. 17.

    & Highly optimized tolerance: robustness and design in complex systems. Phys. Rev. Lett. 84, 2529–2532 (2000).

  18. 18.

    & Complexity and robustness. Proc. Natl Acad. Sci. USA 99 (Suppl. 1), 2538–2545 (2002).

  19. 19.

    Self-perpetuating states in signal transduction: positive feedback, double-negative feedback and bistability. Curr. Opin. Cell. Biol. 14, 140–148 (2002).

  20. 20.

    & Robustness of the bistable behavior of a biological signaling feedback loop. Chaos 11, 221–226 (2001).

  21. 21.

    Between genotype and phenotype: protein chaperones and evolvability. Nature Rev. Genet. 4, 263–274 (2003).

  22. 22.

    , , & Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph. Bioinformatics 20, 1870–1876 (2004).

  23. 23.

    , , & A comprehensive pathway map of epidermal growth factor receptor signaling. Mol. Syst. Biol. 1, 25 May 2005 (doi:10.1038/msb4100014).

  24. 24.

    & Robustness trade-offs and host-microbial symbiosis in the immune system. Mol. Syst. Biol. 2, 17 Jan 2006 (doi:10.1038/msb4100039).

  25. 25.

    & A comprehensive pathway map of toll-like receptor signaling network. Mol. Syst. Biol. 2, 18 April 2006 (doi:10.1038/msb4100057).

  26. 26.

    et al. The 'robust yet fragile' nature of the internet. Proc. Natl Acad. Sci. USA 102, 14497–14502 (2005).

  27. 27.

    , & The Byzantine Generals problem. ACM Trans. Program. Languages Syst. 27, 382–401 (1982).

  28. 28.

    et al. Metabolic syndrome and robustness tradeoffs. Diabetes 53 (Suppl. 3), 6–15 (2004).

  29. 29.

    Cancer as a robust system: implications for anticancer therapy. Nature Rev. Cancer 4, 227–235 (2004).

  30. 30.

    Cancer robustness: tumour tactics. Nature 426, 125 (2003).

  31. 31.

    & Lysogenic conversion by a filamentous phage encoding cholera toxin. Science 272, 1910–1914 (1996).

  32. 32.

    , , & Small-molecule inhibitor of Vibrio cholerae virulence and intestinal colonization. Science 310, 670–674 (2005).

  33. 33.

    & Evolution and spread of antibiotic resistance. J. Intern. Med. 252, 91–106 (2002).

  34. 34.

    et al. Efficacy and safety of a specific inhibitor of the BCR–ABL tyrosine kinase in chronic myeloid leukemia. N. Engl. J. Med. 344, 1031–1037 (2001).

  35. 35.

    A new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and Giemsa staining. Nature 243, 290–293 (1973).

  36. 36.

    , & Induction of chronic myelogenous leukemia in mice by the P210bcr/abl gene of the Philadelphia chromosome. Science 247, 824–830 (1990).

  37. 37.

    , , & Induction of a chronic myelogenous leukemia-like syndrome in mice with v-abl and BCR/ABL. Proc. Natl Acad. Sci. USA 87, 6649–6653 (1990).

  38. 38.

    et al. Acute leukaemia in bcr/abl transgenic mice. Nature 344, 251–253 (1990).

  39. 39.

    , , & Tyrosine kinase activity and transformation potency of bcr–abl oncogene products. Science 247, 1079–1082 (1990).

  40. 40.

    , & Strategies to overcome resistance to targeted protein kinase inhibitors. Nature Rev. Drug Discov. 3, 1001–1010 (2004).

  41. 41.

    Advair: combination treatment with fluticasone propionate/salmeterol in the treatment of asthma. J. Allergy Clin. Immunol. 107, 398–416 (2001).

  42. 42.

    & Lovastatin and extended-release niacin combination product: the first drug combination for the management of hyperlipidemia. Heart Dis. 4, 124–137 (2002).

  43. 43.

    et al. Comparison of once-daily, niacin extended-release/lovastatin with standard doses of atorvastatin and simvastatin (the advicor versus other cholesterol-modulating agents trial evaluation [ADVOCATE]). Am. J. Cardiol. 91, 667–672 (2003).

  44. 44.

    , & Potential mechanism for sustained antiretroviral efficacy of AZT–3TC combination therapy. Science 269, 696–699 (1995).

  45. 45.

    et al. Systematic discovery of multicomponent therapeutics. Proc. Natl Acad. Sci. USA 100, 7977–7982 (2003).

  46. 46.

    , & The efficiency of multi-target drugs: the network approach might help drug design. Trends Pharmacol. Sci. 26, 178–182 (2005).

  47. 47.

    , & Multiple weak hits confuse complex systems: a transcriptional regulatory network as an example. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71, 051909 (2005).

  48. 48.

    & Traditional Chinese medicine: an approach to scientific proof and clinical validation. Pharmacol. Ther. 86, 191–198 (2000).

  49. 49.

    et al. Metabolomics in the context of systems biology: bridging traditional Chinese medicine and molecular pharmacology. Phytother. Res. 19, 173–182 (2005).

  50. 50.

    Scale-rich metabolic networks. Phys. Rev. Lett. 94, 168101 (2005).

  51. 51.

    et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Med. 7, 673–679 (2001).

  52. 52.

    & Zipf's law in importance of genes for cancer classification using microarray data. J. Theor. Biol. 219, 539–551 (2002).

  53. 53.

    & Cell cycle-mediated drug resistance: an emerging concept in cancer therapy. Clin. Cancer Res. 7, 2168–2181 (2001).

  54. 54.

    et al. Oxaliplatin, a potent inhibitor of survivin, enhances paclitaxel-induced apoptosis and mitotic catastrophe in colon cancer cells. Jpn. J. Clin. Oncol. 35, 453–463 (2005).

  55. 55.

    et al. Augmentation of apoptosis and tumor regression by flavopiridol in the presence of CPT-11 in Hct116 colon cancer monolayers and xenografts. Clin. Cancer Res. 7, 4209–4219 (2001).

  56. 56.

    & Targeting the cell cycle: a new approach to cancer therapy. J. Clin. Oncol. 23, 9408–9421 (2005).

  57. 57.

    et al. A Phase I clinical trial of the sequential combination of irinotecan followed by flavopiridol. Clin. Cancer Res. 11, 3836–3845 (2005).

  58. 58.

    Cancer chronotherapy. J. Pharm. Pharmacol. 51, 891–898 (1999).

  59. 59.

    Circadian chronotherapy for human cancers. Lancet Oncol. 2, 307–315 (2001).

  60. 60.

    et al. Deregulated expression of the PER1, PER2 and PER3 genes in breast cancers. Carcinogenesis 26, 1241–1246 (2005).

  61. 61.

    et al. The circadian gene PER1 plays an important role in cell growth and DNA damage control in human cancer cells. Mol. Cell. 22, 375–382 (2006).

  62. 62.

    Principles of Spread Spectrum Communication Systems (Springer, New York, 2004).

  63. 63.

    , & In vivo robustness analysis of cell division cycle genes in Saccharomyces cerevisiae. PLoS Genet. 2, e111 (2006).

  64. 64.

    , & Cells on chips. Nature 442, 403–411 (2006).

  65. 65.

    & Bifurcation analysis of a model of mitotic control in frog eggs. J. Theor. Biol. 195, 69–85 (1998).

  66. 66.

    et al. ZD1839 (Iressa): an orally active inhibitor of epidermal growth factor signaling with potential for cancer therapy. Cancer Res. 62, 5749–5754 (2002).

  67. 67.

    , , & Epidermal growth factor receptor (EGFR) and EGFR mutations, function and possible role in clinical trials. Ann. Oncol. 8, 1197–1206 (1997).

  68. 68.

    , , & Epidermal growth factor-related peptides and their receptors in human malignancies. Crit. Rev. Oncol. Hematol. 19, 183–232 (1995).

  69. 69.

    et al. Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839). Hum. Mol. Genet. 13, 3029–3043 (2004).

  70. 70.

    et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).

  71. 71.

    et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

  72. 72.

    et al. United States Food and Drug Administration drug approval summary: gefitinib (ZD1839; Iressa) tablets. Clin. Cancer Res. 10, 1212–1218 (2004).

  73. 73.

    et al. Uncoupling between epidermal growth factor receptor and downstream signals defines resistance to the antiproliferative effect of gefitinib in bladder cancer cells. Cancer Res. 65, 10524–10535 (2005).

  74. 74.

    et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 352, 786–792 (2005).

  75. 75.

    et al. Humanization of an anti-p185HER2 antibody for human cancer therapy. Proc. Natl Acad. Sci. USA 89, 4285–4289 (1992).

  76. 76.

    et al. Human breast cancer: correlation of relapse and survival with amplification of the HER2/neu oncogene. Science 235, 177–182 (1987).

  77. 77.

    et al. Multinational study of the efficacy and safety of humanized anti-HER2 monoclonal antibody in women who have HER2-overexpressing metastatic breast cancer that has progressed after chemotherapy for metastatic disease. J. Clin. Oncol. 17, 2639–2648 (1999).

  78. 78.

    et al. Efficacy and safety of trastuzumab as a single agent in first-line treatment of HER2-overexpressing metastatic breast cancer. J. Clin. Oncol. 20, 719–726 (2002).

  79. 79.

    , , , & Insulin-like growth factor-I receptor signaling and resistance to trastuzumab (Herceptin). J. Natl Cancer Inst. 93, 1852–1857 (2001).

  80. 80.

    et al. PTEN activation contributes to tumor inhibition by trastuzumab, and loss of PTEN predicts trastuzumab resistance in patients. Cancer Cell 6, 117–127 (2004).

  81. 81.

    & The coxibs, selective inhibitors of cyclooxygenase-2. N. Engl. J. Med. 345, 433–442 (2001).

  82. 82.

    et al. Characterization of prostaglandin G/H synthase 1 and 2 in rat, dog, monkey, and human gastrointestinal tracts. Gastroenterology 111, 445–454 (1996).

  83. 83.

    , , , & Prostaglandin G/H synthase isoenzyme 2 expression in fibroblasts: regulation by dexamethasone, mitogens, and oncogenes. Arch. Biochem. Biophys. 306, 169–177 (1993).

  84. 84.

    The development of COX2 inhibitors. Nature Rev. Drug Discov. 2, 179–191 (2003).

  85. 85.

    et al. Cardiovascular events associated with rofecoxib in a colorectal adenoma chemoprevention trial. N. Engl. J. Med. 352, 1092–1102 (2005).

  86. 86.

    & Coxibs and heart disease. J. Am. Coll. Cardiol. 49, 1–14 (2007).

  87. 87.

    & New targeted approaches in chronic myeloid leukemia. J. Clin. Oncol. 23, 6316–6324 (2005).

  88. 88.

    & Heat shock protein 90. Curr. Opin. Oncol. 15, 419–424 (2003).

  89. 89.

    , & Geldanamycin and its analogue 17-allylamino-17-demethoxygeldanamycin lowers Bcr–Abl levels and induces apoptosis and differentiation of Bcr–Abl-positive human leukemic blasts. Cancer Res. 61, 1799–1804 (2001).

  90. 90.

    , , , & BCRABL point mutants isolated from patients with imatinib mesylate-resistant chronic myeloid leukemia remain sensitive to inhibitors of the BCR–ABL chaperone heat shock protein 90. Blood 100, 3041–3044 (2002).

  91. 91.

    et al. Hsp90 inhibitor 17-AAG reduces ErbB2 levels and inhibits proliferation of the trastuzumab resistant breast tumor cell line JIMT-1. Immunol. Lett. 104, 146–155 (2005).

  92. 92.

    , , & Epidermal growth factor receptors harboring kinase domain mutations associate with the heat shock protein 90 chaperone and are destabilized following exposure to geldanamycins. Cancer Res. 65, 6401–6408 (2005).

  93. 93.

    & Multiple mutations in HIV-1 reverse transcriptase confer high-level resistance to zidovudine (AZT). Science 246, 1155–1158 (1989).

  94. 94.

    , , & Rapid in vitro selection of human immunodeficiency virus type 1 resistant to 3′-thiacytidine inhibitors due to a mutation in the YMDD region of reverse transcriptase. Proc. Natl Acad. Sci. USA 90, 5653–5656 (1993).

  95. 95.

    et al. Cooperative cell-growth inhibition by combination treatment with ZD1839 (Iressa) and trastuzumab (Herceptin) in non-small-cell lung cancer. Cancer Lett. 230, 33–46 (2005).

  96. 96.

    et al. In vivo antitumor activity of SU11248, a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor and platelet-derived growth factor receptors: determination of a pharmacokinetic/pharmacodynamic relationship. Clin. Cancer Res. 9, 327–337 (2003).

  97. 97.

    et al. A recent illustration of some essentials of circadian chronotherapy study design. J. Clin. Oncol. 22, 2971–2972 (2004).

  98. 98.

    et al. Chronotherapy for cancer. Biomed. Pharmacother. 57 (Suppl. 1), 92–95 (2003).

  99. 99.

    & Circadian-system alterations during cancer processes: a review. Int. J. Cancer 70, 241–247 (1997).

  100. 100.

    , & Randomised multicentre trial of chronotherapy with oxaliplatin, fluorouracil, and folinic acid in metastatic colorectal cancer. International Organization for Cancer Chronotherapy. Lancet 350, 681–686 (1997).

  101. 101.

    , , & Maintenance chemotherapy for childhood acute lymphoblastic leukaemia: better in the evening. Lancet 2, 1264–1266 (1985).

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Acknowledgements

This research was supported in part by the Exploratory Research for Advanced Technology (ERATO) and the Solution-Oriented Research for Science and Technology (SORST) programs (Japan Science and Technology Agency), a New Energy and Industrial Technology Development Organization Grant (NEDO) of the Japanese Ministry of Economy, Trade and Industry (METI), and the Genome Network Project by the Ministry of Education, Culture, Sports, Science, and Technology.

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  1. Hiroaki Kitano is at Sony Computer Science Laboratories Inc., 3-14-13 Higashi-Gotanda, Shinagawa, Tokyo 141-0022, Japan; The Systems Biology Institute, Suite 6A M31 6-31-15 Jingumae, Shuibuya, Tokyo 150-0001, Japan; and the Department of Cancer Systems Biology, The Cancer Institute, 3-10-6 Ariake, Koutou-ku, Tokyo 135-8550, Japan.  kitano@sbi.jp

    • Hiroaki Kitano

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The author declares no competing financial interests.

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    Using multistage drugs to achieve efficacy and selectivity.

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    The spread spectrum control problem and the long-tail control problem

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