New approaches to molecular cancer therapeutics

  • A Corrigendum to this article was published on 01 February 2007

Abstract

Cancer drug development is leading the way in exploiting molecular biological and genetic information to develop 'personalized' medicine. The new paradigm is to develop agents that target the precise molecular pathology driving the progression of individual cancers. Drug developers have benefited from decades of academic cancer research and from investment in genomics, genetics and automation; their success is exemplified by high-profile drugs such as Herceptin (trastuzumab), Gleevec (imatinib), Tarceva (erlotinib) and Avastin (bevacizumab). However, only 5% of cancer drugs entering clinical trials reach marketing approval. Cancer remains a high unmet medical need, and many potential cancer targets remain undrugged. In this review we assess the status of the discovery and development of small-molecule cancer therapeutics. We show how chemical biology approaches offer techniques for interconnecting elements of the traditional linear progression from gene to drug, thereby providing a basis for increasing speed and success in cancer drug discovery.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The process of developing new molecular-targeted therapeutics, 'from gene to drug'.

Katie Ris

Figure 2: Understanding the genetic and biological causation of cancer generates new targets for therapy.
Figure 3: Protein-ligand cocrystal structures showing the canonical protein folds and inhibitor binding modes for protein kinases, HSP90 and HDAC.
Figure 4: Kinase binding selectivity for representative inhibitors shown on the human kinome dendrogram.
Figure 5: The pharmacologic audit trail.

Katie Ris

Accession codes

Accessions

Protein Data Bank

References

  1. 1

    Kola, I. & Landis, J. Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov. 3, 711–715 (2004).

  2. 2

    Dalton, W.S. & Friend, S.H. Cancer biomarkers-an invitation to the table. Science 312, 1165–1168 (2006).

  3. 3

    Wesche, H., Xiao, S. & Young, S.W. High-throughput screening for protein kinase inhibitors. Comb. Chem. High Throughput Screen. 8, 181–195 (2005).

  4. 4

    Clemons, P.A. Complex phenotypic assays in high-throughput screening. Curr. Opin. Chem. Biol. 8, 334–338 (2004).

  5. 5

    Noble, M.E.M., Endicott, J.A. & Johnson, L.N. Protein kinase inhibitors: insights into drug design from structure. Science 303, 1800–1805 (2004).

  6. 6

    Fan, Q.W. et al. A dual PI3 kinase/mTOR inhibitor reveals emergent efficacy in glioma. Cancer Cell 9, 341–349 (2006).

  7. 7

    Workman, P. How much gets there and what does it do?: the need for better pharmacokinetic and pharmacodynamic endpoints in contemporary drug discovery and development. Curr. Pharm. Des. 9, 891–902 (2003).

  8. 8

    Becker, F. et al. A three-hybrid approach to scanning the proteome for targets of small molecule kinase inhibitors. Chem. Biol. 11, 211–223 (2004).

  9. 9

    Fabian, M.A. et al. A small molecule–kinase interaction map for clinical kinase inhibitors. Nat. Biotechnol. 23, 329–336 (2005).

  10. 10

    Farmer, H. et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917–921 (2005).

  11. 11

    Morgan-Lappe, S. et al. RNAi-based screening of the human kinome identifies Akt-cooperating kinases: a new approach to designing efficacious multi-targeted kinase inhibitors. Oncogene 25, 1340–1348 (2006).

  12. 12

    Varmus, H. The new era in cancer research. Science 312, 1162–1165 (2006).

  13. 13

    Workman, P. Drugging the cancer kinome: progress and challenges in developing personalized molecular cancer therapeutics. Cold Spring Harb. Symp. Quant. Biol. 70, 499–515 (2005).

  14. 14

    Workman, P. Genomics and the second golden era of cancer drug development. Mol. Biosyst. 1, 17–26 (2005).

  15. 15

    Marsham, P.R. et al. Design and synthesis of potent non-polyglutamatable quinazoline antifolate thymidylate synthase inhibitors. J. Med. Chem. 42, 3809–3820 (1999).

  16. 16

    Vogelstein, B. & Kinzler, K.W. Cancer genes and the pathways they control. Nat. Med. 10, 789–799 (2004).

  17. 17

    Hanahan, D. & Weinberg, R.A. The hallmarks of cancer. Cell 100, 57–70 (2000).

  18. 18

    McDonald, E., Workman, P. & Jones, K. Inhibitors of the HSP90 molecular chaperone: attacking the master regulator in cancer. Curr. Med. Chem. 6, 1091–1107 (2006).

  19. 19

    Minucci, S. & Pelicci, P.G. Histone deacetylase inhibitors and the promise of epigenetic (and more) treatments for cancer. Nat. Rev. Cancer 6, 38–51 (2006).

  20. 20

    Capdeville, R., Buchdunger, E., Zimmerman, J. & Matter, A. Glivec (ST571, imatinib), a rationally developed, targeted anticancer drug. Nat. Rev. Drug Discov. 1, 493–502 (2002).

  21. 21

    Weinstein, I.B. Cancer. Addiction to oncogenes-the Achilles heal of cancer. Science 297, 63–64 (2002).

  22. 22

    Benson, J.D. et al. Validating cancer drug targets. Nature 441, 451–456 (2006).

  23. 23

    Solit, D. et al. BRAF mutation predicts sensitivity to MEK inhibition. Nature 439, 358–362 (2006).

  24. 24

    Garraway, L. et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436, 117–122 (2005).

  25. 25

    Futreal, P.A. et al. A census of human cancer genes. Nat. Rev. Cancer 4, 177–183 (2004).

  26. 26

    Thomas, R.K. et al. Sensitive mutation detection in heterogeneous cancer specimens by massively parallel picoliter reactor sequencing. Nat. Med. 12, 852–855 (2006).

  27. 27

    Davies, H. et al. Mutations of the BRAF gene in human cancer. Nature 417, 949–954 (2002).

  28. 28

    Brummelkamp, T.R. et al. An shRNA barcode screen provides insight into cancer cell vulnerability to MDM2 inhibitors. Nat. Chem. Biol. 2, 202–206 (2006).

  29. 29

    Chatterjee-Kishore, M. & Miller, C.P. Exploring the sounds of silence: RNAi-mediated gene silencing for target identification and validation. Drug Discov. Today 10, 1559–1565 (2005).

  30. 30

    Lacouture, M.E. Mechanisms of cutaneous toxicities to EGFR inhibitors. Nat. Rev. Cancer 6, 803–812 (2006).

  31. 31

    Newbatt, Y. et al. Identification of inhibitors of the kinase activity of oncogenic V600E BRAF in an enzyme cascade high-throughput screen. J. Biomol. Screen. 11, 145–154 (2006).

  32. 32

    Park, S. et al. Hexachlorophene inhibits Wnt/beta-catenin pathway by promoting Siah-mediated beta-catenin degradation. Mol. Pharmacol. 70, 960–966 (2006).

  33. 33

    Hart, C.P. Finding the target after screening the phenotype. Drug Discov. Today 10, 513–519 (2005).

  34. 34

    Luesch, H. et al. A genome-wide overexpression screen in yeast for small-molecule target identification. Chem. Biol. 12, 55–63 (2005).

  35. 35

    Evans, M.J., Saghatelian, A., Sorensen, E.J. & Cravatt, B.F. Target discovery in small-molecule cell-based screens by in situ proteome reactivity profiling. Nat. Biotechnol. 23, 1303–1307 (2005).

  36. 36

    Lundholt, B.K. et al. Identification of Akt pathway inhibitors using redistribution screening on the FLIPR and the IN cell 3000 analyzer. J. Biomol. Screen. 10, 20–29 (2005).

  37. 37

    Wolff, M. et al. Automated high content screening for phosphoinositide 3 kinase inhibition using an AKT 1 redistribution assay. Comb. Chem. High Throughput Screen. 9, 339–350 (2006).

  38. 38

    Kau, T.R. et al. A chemical genetic screen identifies inhibitors of regulated nuclear export of a Forkhead transcription factor in PTEN-deficient tumor cells. Cancer Cell 4, 463–476 (2003).

  39. 39

    Rees, D.C., Congreve, M., Murray, C.W. & Carr, R.A.E. Fragment-based lead discovery. Nat. Rev. Drug Discov. 3, 660–672 (2004).

  40. 40

    Gill, A.L. et al. Identification of novel p38alpha MAP kinase inhibitors using fragment based lead generation. J. Med. Chem. 48, 414–426 (2005).

  41. 41

    Card, G.L. et al. A family of phosphodiesterase inhibitors discovered by cocrystallography and scaffold-based drug design. Nat. Biotechnol. 23, 201–207 (2005).

  42. 42

    Lipinski, C.A., Lombardo, F., Dominy, B.W. & Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 46, 3–26 (2001).

  43. 43

    Lumley, J.A. Compound selection and filtering in library design. QSAR Comb. Sci. 24, 1066–1075 (2005).

  44. 44

    Oprea, T.I., Davis, A.M., Teague, S.J. & Leeson, P.D. Is there a difference between leads and drugs? A historical perspective. J. Chem. Inf. Comput. Sci. 41, 1308–1315 (2001).

  45. 45

    Veber, D.F., Johnson, S.R., Cheng, H., Ward, K.W. & Kopple, K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem. 45, 2615–2623 (2002).

  46. 46

    Vieth, M. et al. Characteristic physical properties and structural fragments of marketed oral drugs. J. Med. Chem. 47, 224–232 (2004).

  47. 47

    Lu, J.J. et al. Influence of molecular flexibility and polar surface area metrics on oral bioavailability in the rat. J. Med. Chem. 47, 6104–6107 (2004).

  48. 48

    McGovern, S.L., Caselli, E., Grigorieff, N. & Schoichet, B.K. A common mechanism underlying promiscuous inhibitors from virtual and high-throughput screening. J. Med. Chem. 45, 1712–1722 (2002).

  49. 49

    Rishton, G.M. Nonleadlikeness and leadlikeness in biochemical screening. Drug Discov. Today 8, 86–96 (2003).

  50. 50

    Kitchen, D.B., Decornez, H., Furr, J.R. & Bajorath, J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat. Rev. Drug Discov. 3, 935–949 (2004).

  51. 51

    Lyne, P.D. et al. Identification of compounds with nanomolar binding affinity for checkpoint kinase-1 using knowledge-based virtual screening. J. Med. Chem. 47, 1962–1968 (2004).

  52. 52

    Muller, O. et al. Identification of potent Ras signaling inhibitors by pathway-selective phenotype-based screening. Angew. Chem. Int. Edn Engl. 43, 450–454 (2004).

  53. 53

    Prien, O. Target-family-oriented focused libraries for kinases – conceptual design aspects and commercial availability. ChemBioChem 6, 500–505 (2005).

  54. 54

    Muller, G. Medicinal chemistry of target family-directed masterkeys. Drug Discov. Today 8, 681–691 (2003).

  55. 55

    Mann, J. Natural products in cancer chemotherapy: past, present and future. Nat. Rev. Cancer 2, 143–148 (2002).

  56. 56

    Noren-Muller, A. et al. Discovery of protein phosphatase inhibitor classes by biology-oriented synthesis. Proc. Natl. Acad. Sci. USA 103, 10606–10611 (2006).

  57. 57

    Tan, D.S. Diversity-oriented synthesis: exploring the intersections between chemistry and biology. Nat. Chem. Biol. 1, 74–84 (2005).

  58. 58

    Clardy, J. & Walsh, C. Lessons from natural molecules. Nature 432, 829–837 (2004).

  59. 59

    Lipinski, C.A. & Hopkins, A. Navigating chemical space for biology and medicine. Nature 432, 855–861 (2004).

  60. 60

    Fry, D.C. & Vassilev, L.T. Targeting protein-protein interactions for cancer therapy. J. Mol. Med. 83, 955–983 (2005).

  61. 61

    Liu, Y. & Gray, N.S. Rational design of inhibitors that bind to inactive kinase conformations. Nat. Chem. Biol. 2, 358–364 (2006).

  62. 62

    Cohen, P. Protein kinases – the major drug targets of the twenty-first century? Nat. Rev. Drug Discov. 1, 309–315 (2002).

  63. 63

    Ohren, J.F. et al. Structures of human MAP kinase kinase 1 (MEK1) and MEK2 describe novel noncompetitive kinase inhibition. Nat. Struct. Mol. Biol. 11, 1192–1197 (2004); erratum 12, 278 (2005).

  64. 64

    Barnett, S.F., Bilodeau, M.T. & Lindsley, C.W. The Akt/PKB family of protein kinases: a review of small molecule inhibitors and progress towards target validation. Curr. Top. Med. Chem. 5, 109–125 (2005).

  65. 65

    Choi, J., Chen, J., Schreiber, S. & Clardy, J. Structure of the FKBP12-rapamycin complex interacting with the binding domain of human FRAP. Science 273, 239–242 (1996).

  66. 66

    Gorre, M.E. et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science 293, 876–880 (2001).

  67. 67

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

  68. 68

    Blencke, S., Ullrich, A. & Daub, H. Mutation of threonine 766 in the epidermal growth factor receptor reveals a hotspot for resistance formation against selective tyrosine kinase inhibitors. J. Biol. Chem. 278, 15435–15440 (2003).

  69. 69

    Shokat, K. & Velleca, M. Novel chemical genetic approaches to the discovery of signal transduction inhibitors. Drug Discov. Today 7, 872–879 (2002).

  70. 70

    Fry, D.W. Site-directed irreversible inhibitors of the erbB family of receptor tyrosine kinase as novel chemotherapeutic agents for cancer. Anticancer Drug Des. 15, 3–16 (2000).

  71. 71

    Cohen, M.S., Zhang, C., Shokat, K.M. & Taunton, J. Structural bioinformatics-based design of selective, irreversible kinase inhibitors. Science 308, 1318–1321 (2005).

  72. 72

    Roe, S.M. et al. Structural basis for inhibition of of the Hsp90 molecular chaperone by the antitumour antibiotics radicicol and geldanamycin. J. Med. Chem. 42, 260–266 (1999).

  73. 73

    Cheung, K.M. et al. The identification, synthesis, protein crystal structure and in vitro biochemical evaluation of a new 3,4-diarylpyrazole class of Hsp90 inhibitors. Bioorg. Med. Chem. Lett. 15, 3338–3343 (2005).

  74. 74

    Chiosis, G. et al. A small molecule designed to bind to the adenine nucleotide pocket of Hsp90 causes Her2 degradation and the growth arrest and differentiation of breast cancer cells. Chem. Biol. 8, 289–299 (2001).

  75. 75

    Wright, L. et al. Structure-activity relationships in purine-based inhibitor binding to HSP90 isoforms. Chem. Biol. 11, 775–785 (2004).

  76. 76

    Finnin, M.S. et al. Structures of a histone deacetylase homologue bound to the TSA and SAHA inhibitors. Nature 401, 188–193 (1999).

  77. 77

    Somoza, J.R. et al. Structural snapshots of human HDAC8 provide insights into the class I histone deacetylases. Structure 12, 1325–1334 (2004).

  78. 78

    Hildmann, C. et al. Substrate and inhibitor specificity of class 1 and class 2 histone deacetylases. J. Biotechnol. 124, 258–270 (2006).

  79. 79

    Koeller, K.M. et al. Chemical genetic modifier screens: small molecule trichostatin suppressors as probes of intracellular histone and tubulin acetylation. Chem. Biol. 10, 397–410 (2003).

  80. 80

    Davis, A.M., Keeling, D.J., Steele, J., Tomkinson, N.P. & Tinker, A.C. Components of successful lead generation. Curr. Top. Med. Chem. 5, 421–439 (2005).

  81. 81

    Shuttleworth, S.J. et al. Design and synthesis of protein superfamily-targeted chemical libraries for lead identification and optimization. Curr. Med. Chem. 12, 1239–1281 (2005).

  82. 82

    Lowinger, T.B., Riedl, B., Dumas, J. & Smith, R.A. Design and discovery of small molecules targeting Raf-1 kinase. Curr. Pharm. Des. 8, 2269–2278 (2002).

  83. 83

    Adams, J. et al. Potent and selective inhibitors of the proteasome: dipeptidyl boronic acids. Bioorg. Med. Chem. Lett. 8, 333–338 (1998).

  84. 84

    Swinney, D.C. Biochemical mechanisms of drug action: what does it take for success? Nat. Rev. Drug Discov. 3, 801–808 (2004).

  85. 85

    Hopkins, A.L., Groom, C.R. & Alex, A. Ligand efficiency: a useful metric for lead selection. Drug Discov. Today 9, 430–431 (2004).

  86. 86

    Knight, Z.A. & Shokat, K.M. Features of selective kinase inhibitors. Chem. Biol. 12, 621–637 (2005).

  87. 87

    Kung, C., Kenski, D.M., Krukenberg, K., Madhani, H.D. & Shokat, K.M. Selective kinase inhibition by exploiting differential pathway selectivity. Chem. Biol. 13, 399–407 (2006).

  88. 88

    Bain, J., McLauchlan, H., Elliott, M. & Cohen, P. The specificities of protein kinase inhibitors: an update. Biochem. J. 371, 199–204 (2003).

  89. 89

    Brehmer, D. et al. Cellular targets of gefitinib. Cancer Res. 65, 379–382 (2005).

  90. 90

    Wan, Y. et al. Synthesis and target identification of hymenialdisine analogues. Chem. Biol. 11, 247–259 (2004).

  91. 91

    Obata, K., Sugano, K., Machida, M. & Aso, Y. Biopharmaceutics classification by high throughput solubility assay and PAMPA. Drug Dev. Ind. Pharm. 30, 181–185 (2004).

  92. 92

    Kerns, E.H. et al. Combined application of parallel artificial membrane permeability assay and Caco-2 permeability assays in drug discovery. J. Pharm. Sci. 93, 1440–1453 (2004).

  93. 93

    Longley, D.B. & Johnston, P.G. Molecular mechanisms of drug resistance. J. Pathol. 205, 275–292 (2005).

  94. 94

    Nassar, A.E., Kamel, A.M. & Clarimont, C. Improving the decision-making process in the structural modification of drug candidates: enhancing metabolic stability. Drug Discov. Today 9, 1020–1028 (2004).

  95. 95

    Hutzler, J.M., Messing, D.M. & Wienkers, L.C. Predicting drug-drug interactions in drug discovery: where are we now and where are we going? Curr. Opin. Drug Discov. Devel. 8, 51–58 (2005).

  96. 96

    Raynaud, F.I. et al. Cassette dosing pharmacokinetics of a library of 2,6,9-trisubstituted purine cyclin-dependent kinase 2 inhibitors prepared by parallel synthesis. Mol. Cancer Ther. 3, 353–362 (2004).

  97. 97

    Smith, N.F. et al. Preclinical pharmacokinetics and metabolism of a novel diaryl pyrazole resorcinol series of heat shock protein 90 inhibitors. Mol. Cancer Ther. 5, 1628–1637 (2006).

  98. 98

    Banerji, U. et al. Pharmacokinetic-pharmacodynamic relationships for the heat shock protein 90 molecular chaperone inhibitor 17-allylamino, 17-demethoxygeldanamycin in human ovarian cancer xenograft models. Clin. Cancer Res. 11, 7023–7032 (2005).

  99. 99

    Sausville, E.A. & Burger, A.M. Contributions of human tumour xenografts to anticancer drug development. Cancer Res. 66, 3351–3354 (2006).

  100. 100

    Becher, O.J. & Holland, E.C. Genetically engineered models have advantages over xenografts for preclinical studies. Cancer Res. 66, 3355–3359 (2006).

  101. 101

    Whitebread, S., Hamon, J., Bojanic, D. & Urban, L. In vitro safety pharmacology profiling: an essential tool for successful drug development. Drug Discov. Today 10, 1421–1433 (2005).

  102. 102

    Haystead, T.A. The purinome, a complex mix of drug and toxicity targets. Curr. Top. Med. Chem. 6, 1117–1127 (2006).

  103. 103

    Judson, I. Gastrointestinal stromal tumours (GIST): biology and treatment. Ann. Oncol. 13, 287–289 (2002).

  104. 104

    Shah, N.P. et al. Overriding imatinib resistance with a novel ABL kinase inhibitor. Science 305, 399–401 (2004).

  105. 105

    Strumberg, D. Preclinical and clinical development of the oral multikinase inhibitor sorafenib in cancer. Drugs Today (Barc). 41, 773–784 (2005).

  106. 106

    Banerji, U. et al. Phase I pharmacokinetic and pharmacodynamic study of 17-allylamino, 17-demethoxygeldanamycin in patients with advanced malignancies. J. Clin. Oncol. 23, 4152–4161 (2005).

  107. 107

    Dymock, B.W. et al. Novel, potent small-molecule inhibitors of the molecular chaperone Hsp90 discovered through structure-based design. J. Med. Chem. 48, 4212–4215 (2005).

  108. 108

    Kelly, W.K. & Marks, P.A. Drug insight: histone deacetylase inhibitors–development of the new targeted anticancer agent suberoylanilide hydroxamic acid. Nat. Clin. Pract. Oncol. 2, 150–157 (2005).

  109. 109

    Remiszewski, S.W. The discovery of NVP-LAQ824: from concept to clinic. Curr. Med. Chem. 10, 2393–2402 (2003).

  110. 110

    Sawyers, C.L. Opportunities and challenges in the development of kinase inhibitor therapy for cancer. Genes Dev. 17, 2998–3010 (2003).

  111. 111

    Frank, R. & Hargreaves, R. Clinical biomarkers in drug discovery and development. Nat. Rev. Drug Discov. 2, 566–580 (2003).

  112. 112

    Workman, P. Challenges of PK/PD measurements in modern drug development. Eur. J. Cancer 38, 2189–2193 (2002).

  113. 113

    Workman, P. Auditing the pharmacological accounts for Hsp90 molecular chaperone inhibitors: unfolding the relationship between pharmacokinetics and pharmacodynamics. Mol. Cancer Ther. 2, 131–138 (2003).

  114. 114

    Workman, P. & Johnston, P.G. Genomic profiling of cancer: what next? J. Clin. Oncol. 23, 7253–7256 (2005).

  115. 115

    Workman, P. et al. Minimally invasive pharmacokinetic and pharmacodynamic technologies in hypothesis-testing clinical trials of innovative therapies. J. Natl. Cancer Inst. 98, 580–598 (2006).

  116. 116

    Garrett, M.D. et al. Novel isoquinoline-5-sulfonamides as biochemical and cellular inhibitors of PKB/AKt. Eur. J. Cancer Suppl. 2, 98 (2004).

  117. 117

    Vassilev, L.T. et al. In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science 303, 844–888 (2004).

  118. 118

    Oltersdorf, T. et al. An inhibitor of Bcl-2 family proteins induces regression of solid tumours. Nature 435, 677–681 (2005).

  119. 119

    Inglese, J. et al. Quantitative high-throughput screening: a titration-based approach that efficiently identifies biological activities in large chemical libraries. Proc. Natl. Acad. Sci. USA 103, 11473–11478 (2006).

  120. 120

    Paolini, G.V. et al. Global mapping of pharmacological space. Nat. Biotechnol. 24, 805–815 (2006).

  121. 121

    Shoemaker, R. The NCI60 human tumour cell line anticancer drug screen. Nat. Rev. Cancer 6, 813–823 (2006).

  122. 122

    Sharpless, N.E. & DePinho, R.A. The mighty mouse: genetically engineered mouse models in cancer drug development. Nat. Rev. Drug Discov. 5, 741–754 (2006).

  123. 123

    Ratain, M.J. & Eckardt, S.G. Phase II studies of modern drugs directed against new targets: if you are fazed, too, then resist RECIST. J. Clin. Oncol. 22, 4442–4445 (2004).

  124. 124

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

  125. 125

    Fitzgerald, J.B., Schoeberl, B., Nielsen, U.B. & Sorger, P.K. Systems biology and combination therapy in the quest for clinical efficacy. Nat. Chem. Biol. 2, 458–466 (2006).

  126. 126

    Alves, R., Antunes, F. & Salvador, A. Tools for kinetic modeling of biochemical networks. Nat. Biotechnol. 24, 667–672 (2006).

  127. 127

    Harrington, L.S. et al. The TSC1–2 tumor suppressor controls insulin-PI3K signaling via regulation of IRS proteins. J. Cell Biol. 166, 213–223 (2004).

  128. 128

    Workman P., Clarke, P.A., Guillard, S. & Raynaud, F.I. Drugging the PI3 kinome. Nat. Biotechnol. 24, 794–796 (2006); corrigendum 24, 1033 (2006).

  129. 129

    Clarke, M.F. & Fuller, M. Stem cells and cancer: two faces of eve. Cell 124, 1111–1115 (2006).

  130. 130

    Schreiber, S.L. Stuart Schreiber: biology from a chemist's perspective. Interview by Joanna Owens. Drug Discov. Today 9, 299–303 (2004).

  131. 131

    Kassel, D.B. Applications of high-throughput ADME in drug discovery. Curr. Opin. Chem. Biol. 8, 339–345 (2004).

Download references

Acknowledgements

This article is dedicated to our late friend and colleague F.T. (Tom) Boyle, who spent most of his successful career working on the medicinal chemistry of cancer drugs. The authors' work (http://www.icr.ac.uk/) is funded primarily by Cancer Research UK [CUK] Programme Grant C309/A2187, and P. Workman is a Cancer Research UK Life Fellow. We thank our many colleagues and collaborators for stimulating discussions.

Author information

Correspondence to Ian Collins or Paul Workman.

Ethics declarations

Competing interests

The authors have received research funding and/or have collaboration/licensing arrangements with Vernalis, Astex Therapeutics, Chroma Therapeutics, PIramed, Sareum, Cyclacel, Novartis, AstraZeneca, Genentech and GlaxoSmithKline. P.W. holds stock/options in Chroma Therapeutics, PIramed and Avalon Pharmaceuticals and is a consultant for Chroma Therapeutics, PIramed, Avalon Pharmaceuticals and Novartis.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Collins, I., Workman, P. New approaches to molecular cancer therapeutics. Nat Chem Biol 2, 689–700 (2006). https://doi.org/10.1038/nchembio840

Download citation

Further reading