Why so few drug targets: A mathematical explanation?

Current Computer-Aided Drug Design

Volumn 7, Issue 3, 2011, Pages 206-213

  Tun, Kyaw ^a,b   Menghini, Marta ^c   D'Andrea, Lina ^c   Dhar, Pawan ^d   Tanaka, Hiroshi ^b   Giuliani, Alessandro ^e  

^a RIKEN   (Japan)

^b TOKYO MEDICAL AND DENTAL UNIVERSITY   (Japan)

^c SAPIENZA UNIVERSITY OF ROME   (Italy)

^d UNIVERSITY OF KERALA   (India)

^e ISTITUTO SUPERIORE DI SANITÀ   (Italy)

Author keywords

Drug development; Multiple targets; Networks; Pharmacology; Systems biology

Indexed keywords

BIOLOGICAL PATHWAYS; DRUG DEVELOPMENT; DRUG TARGETS; GENOMIC SCIENCE; MATHEMATICAL APPROACH; MULTIPLE TARGETS; NETWORK; PHARMACOLOGY; POTENTIAL DRUG TARGETS; SYSTEMS BIOLOGY;

NETWORK ARCHITECTURE;

MITOGEN ACTIVATED PROTEIN KINASE;

ARTICLE; DEPHOSPHORYLATION; DRUG DEVELOPMENT; MATHEMATICAL MODEL; MOLECULARLY TARGETED THERAPY; OSCILLATION; PHARMACOLOGY; PHOSPHORYLATION;

EID: 79961088430     PISSN: 15734099     EISSN: 18756697     Source Type: Journal    
DOI: 10.2174/157340911796504297     Document Type: Article

References (25)

1. Hopkins, A.L. Network pharmacology: the next paradigm in drug discovery. Nat. Chem Biol., 2008, 4, 682-690.
2. Overington, J.P.; Al-Lazikani, B.; Hopkins A.L. How many drug targets are there? Nat. Rev. Drug Discov., 2006, 5, 993-996.
3. Koonin, E.V.; Galperin, M.Y. Sequence-evolution-function computational approaches in comparative genomics. Kluwer Academic, 2003, ISBN: 1-40207-274-0.
4. Knight, Z.A.; Lin, H.; Shokat, K.M. Targeting the cancer kinome through polypharmacology. Nat. Rev. Cancer, 2010, 10, 130-137.
5. Boran, A.D.W.; Iyengar, R. Systems approaches to polypharmacology and drug discovery. Curr. Opin. Drug Discov. Devel., 2010, 13, 297-310.
6. Csermely, P.; Agoston, V.; Pongor, S. The efficiency of multi-target drugs: The network approach might help drug design. Trends Pharmacol. Sci., 2005, 26, 178-182.
7. Funahashi, A.; Matsuoka, Y.; Jouraku, A.; Morohashi, M.; Kikuchi, N.; Kitano, H. CellDesigner 3.5: a versatile modeling tool for biochemical networks. Proceed. IEEE, 2008, 96, 1254-1265.
8. Kholodenko, B.N. Negative feedback and ultrasensitivity can bring about oscillation in the mitogen-activated protein kinase cascades. FEBS J., 2000, 276, 1583-1588.
9. Farina, L.; De Santis, A.; Salvucci, S.; Morelli, G.; Ruberti, I. Embedding mRNA stability in correlation analysis of time-series gene expression data. PLoS Comput. Biol., 2008, 4, e1000141.
10. Huang, S. Reprogramming cell fates: reconciling rarity with robustness, BioEssays, 2009, 31, 546-560.
11. Bar-Yam, Y.; Harmon, D.; de Bivert, B. Attractors and democratic dynamics. Science, 2009, 323, 1016-1017.
12. Giuliani, A. Collective motions and specific effectors: a statistical mechanics perspective on biological regulation. BMC Genomics, 2010, 11(suppl. 1), S2.
13. Huang, S.; Eichler, G.; Bar-Yam, Y.; Ingber, D. Cell fates as highdimensional attractor states of a complex gene regulatory network. Phys. Rev. Lett., 2005, 94, 128701-128711.
14. Lima-De-Faria, A. How to produce a human with 3 chromosomes and 1000 primary genes? Hereditas, 1980, 93, 47-73.
15. Craigmyle, M.B.L. A colour atlas of histology. Wolfe Medical Publications, 1975, pp-1-312.
16. Denton, M.; Marshall, C. Laws of form revisited. Nature, 2001, 410, 417.
17. Conti, F.; Valerio, M.C.; Zbilut, J.P.; Giuliani, A. Will systems biology offer new holistic paradigms to life sciences? Syst. Synth. Biol., 2007, 4, 161-165.
18. Ge, H.; Liu, Z.; Church, G.M.; Vidal, M. Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat. Genet., 2001, 29, 482-486.
19. Ingber, D. Tensegrity, I. Cell structure and hierarchical systems biology. J. Cell Sci., 2003, 116, 1157-1173.
20. Ingber, D. Tensegrity II. How structural networks influence cellular information processing networks. J. Cell Sci., 2003, 116, 1397-1408.
21. Hammond, T.G.; Benes, E.; O'Reilly, K.C.; Wolf, D.A.; Linnehan, R.M.; Taher, A.; Kaysen, J.H.; Allen, P.L.; Goodwin, T.J. Mechanical culture condition effect gene expression: gravity induced changes on space-shuttle. Physiol. Genomics, 2000, 3, 163-173.
22. Frantz, S. Drug discovery: playing dirty. Nature, 2000, 437, 942-943.
23. Keiser, M.J.; Irwin, J.J.; Shoichet, B.K. The chemical basis of pharmacology. Biochemistry, 2010, 49, 10267-10276.
24. Paolini, G.V.; Shapland, R.H.; van Hoorn, W.P.; Mason, J.S.; Hopkins, A.L. Global mapping of pharmacological space. Nat. Biotechnol., 2006, 24, 805-815.
25. Mugler, A.; Grinshpun, B.; Franks, R.; Wiggins, C.H. Statistical method for revealing form-function relations in biological networks. Proc. Natl. Acad. Sci. USA, 2011, 108, 446-451.