Structure-based protein-protein interaction networks and drug design

Abstract

Proteins carry out their functions by interacting with other proteins and small molecules, forming a complex interaction network. In this review, we briefly introduce classical graph theory based protein-protein interaction networks. We also describe the commonly used experimental methods to construct these networks, and the insights that can be gained from these networks. We then discuss the recent transition from graph theory based networks to structure based protein-protein interaction networks and the advantages of the latter over the former, using two networks as examples. We further discuss the usefulness of structure based protein-protein interaction networks for drug discovery, with a special emphasis on drug repositioning.

Keywords

protein-protein interaction / network / structure-based / drug design / drug reposition

References

[1] Hartwell, L. H.,Hopfield, J. J.,Leibler, S., and Murray, A. W. (1999) From molecular to modular cell biology. Nature, 402, C47–C52.

[2] Dunham, I.,Kundaje, A.,Aldred, S. F.,Collins, P. J.,Davis, C. A.,Doyle, F.,Epstein, C. B.,Frietze, S.,Harrow, J.,Kaul, R., and the ENCODE Project Consortium. (2012) An integrated encyclopedia of DNA elements in the human genome. Nature, 489, 57–74.

[3] Whisstock, J. C. and Lesk, A. M. (2003) Prediction of protein function from protein sequence and structure. Q. Rev. Biophys.,36, 307–340.

[4] Fields, S.Uetz, P.Giot, L.Cagney, G.Mansfield, T. A.Judson, R. S.Knight, J. R.Lockshon, D.Narayan, V.Srinivasan, M. (2000) A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature, 403, 623–627.

[5] Ito, T.Chiba, T.Ozawa, R.Yoshida, M.Hattori, M. and Sakaki, Y. (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. U.S.A., 98, 4569–4574.

[6] Li, S.Armstrong, C. M.Bertin, N.Ge, H.Milstein, S.Boxem, M.Vidalain, P. O.Han, J. D.Chesneau, A.Hao, T. (2004) A map of the interactome network of the metazoan C. elegans. Science, 303, 540–543.

[7] Rual, J.-F.Venkatesan, K.Hao, T.Hirozane-Kishikawa, T.Dricot, A.Li, N.Berriz, G. F.Gibbons, F. D.Dreze, M.Ayivi-Guedehoussou, N. (2005) Towards a proteome-scale map of the human protein-protein interaction network. Nature, 437, 1173–1178.

[8] Rajagopala, S. V. and Uetz, P. (2011) Analysis of protein-protein interactions using high-throughput yeast two-hybrid screens. Methods Mol. Biol., 781, 1–29.

[9] Gavin, A. C.Aloy, P.Grandi, P.Krause, R.Boesche, M.Marzioch, M.Rau, C.Jensen, L. J.Bastuck, S.Dümpelfeld, B. (2006) Proteome survey reveals modularity of the yeast cell machinery. Nature, 440, 631–636.

[10] Krogan, N. J.Cagney, G.Yu, H.Zhong, G.Guo, X.Ignatchenko, A.Li, J.Pu, S.Datta, N.Tikuisis, A. P. (2006) Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature, 440, 637–643.

[11] Soong, T. T.Wrzeszczynski, K. O. and Rost, B. (2008) Physical protein-protein interactions predicted from microarrays. Bioinformatics, 24, 2608–2614.

[12] Liu, C. T., Yuan, S. and Li, K. C. (2009) Patterns of co-expression for protein complexes by size in Saccharomyces cerevisiae. Nucleic Acids Res., 37, 526–532.

[13] Salwinski, L.Miller, C. S.Smith, A. J.Pettit, F. K.Bowie, J. U. and Eisenberg, D. (2004) The database of interacting Proteins: 2004 update. Nucleic Acids Res., 32, D449–D451.

[14] Licata, L.Briganti, L.Peluso, D.Perfetto, L.Iannuccelli, M.Galeota, E.Sacco, F.Palma, A.Nardozza, A. P.Santonico, E. (2012) MINT the molecular interaction database: 2012 update. Nucleic Acids Res., 40, D857–D861.

[15] Keshava Prasad, T. S.Goel, R.Kandasamy, K.Keerthikumar, S.Kumar, S.Mathivanan, S.Telikicherla, D.Raju, R.Shafreen, B.Venugopal, A. (2009) Human Protein Reference Database--2009 update. Nucleic Acids Res., 37, D767–D772.

[16] Stark, C.Breitkreutz, B. J.Chatr-Aryamontri, A.Boucher, L.Oughtred, R.Livstone, M. S.Nixon, J.Van Auken, K.Wang, X.Shi, X. (2011) The BioGRID Interaction Database: 2011 update. Nucleic Acids Res., 39, D698–D704.

[17] Willis, R. C. and Hogue, C. W. (2006) Searching viewing and visualizing data in the Biomolecular Interaction Network Database (BIND) Curr. Protoc. Bioinformatics, 8.9.1–8.9.30.

[18] Kerrien, S.Aranda, B.Breuza, L.Bridge, A.Broackes-Carter, F.Chen, C.Duesbury, M.Dumousseau, M.Feuermann, M.Hinz, U. (2012) The IntAct molecular interaction database in 2012. Nucleic Acids Res., 40, D841–D846.

[19] Jeong, H.Mason, S. P.Barabási, A.-L. and Oltvai, Z. N. (2001) Lethality and centrality in protein networks. Nature, 411, 41–42.

[20] Barabási, A.-L. and Bonabeau, E. (2003) Scale-free networks. Sci. Am., 288, 60–69.

[21] Han, J.-D.Bertin, N.Hao, T.Goldberg, D. S.Berriz, G. F.Zhang, L. V.Dupuy, D.Walhout, A. J.Cusick, M. E.Roth, F. P. (2004) Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature, 430, 88–93.

[22] Yook, S. H.Oltvai, Z. N. and Barabási, A. L. (2004) Functional and topological characterization of protein interaction networks. Proteomics, 4, 928–942.

[23] Lim, J.Hao, T.Shaw, C.Patel, A. J.Szabá G.Rual, J. F.Fisk, C. J.Li, N.Smolyar, A.Hill, D. E. (2006) A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration. Cell, 125, 801–814.

[24] Huang, H.Jedynak, B. M. and Bader, J. S. (2007) Where have all the interactions gone? Estimating the coverage of two-hybrid protein interaction maps. PLoS Comput. Biol., 3, e214.

[25] Shen-Orr, S. S.Milo, R.Mangan, S. and Alon, U. (2002) Network motifs in the transcriptional regulation network of Escherichia coli. Nat. Genet., 31, 64–68.

[26] Milo, R.Shen-Orr, S.Itzkovitz, S.Kashtan, N.Chklovskii, D. and Alon, U. (2002) Network motifs: simple building blocks of complex networks. Science, 298, 824–827.

[27] Said, M. R.Begley, T. J.Oppenheim, A. V.Lauffenburger, D. A. and Samson, L. D. (2004) Global network analysis of phenotypic effects: protein networks and toxicity modulation in Saccharomyces cerevisiae. Proc. Natl. Acad. Sci. U.S.A., 101, 18006–18011

[28] Shachar, R.Unger, L.Kupiec, M.Ruppin, R. and Sharan, R. (2008) A systems-level approach to mapping the telomere-length maintenance gene circuitryMol. Syst. Biol., 4, 172.

[29] Wachi, S.Yoneda, K. and Wu, R. (2005) Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues. Bioinformatics, 21, 4205–4208.

[30] Jonsson, P. F. and Bates, P. A. (2006) Global topological features of cancer proteins in the human interactome. Bioinformatics, 22, 2291–2297.

[31] Goh, K. I.Cusick, M. E.Valle, D.Childs, B.Vidal, M. and Barabási, A. L. (2007) The human disease network. Proc. Natl. Acad. Sci. U.S.A., 104, 8685–8690

[32] Nguyen, T. N. and Goodrich, J. A. (2006) Protein-protein interaction assays: eliminating false positive interactions. Nat. Methods, 3, 135–139.

[33] Fullwood, M. J. and Ruan, Y. (2009) ChIP-based methods for the identification of long-range chromatin interactions. J. Cell. Biochem.,107, 30–39

[34] Cusick, M. E.Yu, H.Smolyar, A.Venkatesan, K.Carvunis, A. R.Simonis, N.Rual, J. F.Borick, H.Braun, P.Dreze, M. (2009) Literature-curated protein interaction datasets. Nat. Methods6, 39–46.

[35] Ennifar, E. (2012) X-ray crystallography as a tool for mechanism-of-action studies and drug discovery. Curr. Pharm. Biotechnol., PMID: 22429136

[36] Guerry, P. and Herrmann, T. (2011) Advances in automated NMR protein structure determination. Q. Rev. Biophys., 44, 257–309

[37] Glaeser, R. M. and Hall, R. J. (2011) Reaching the information limit in cryo-EM of biological macromolecules: experimental aspects. Biophys. J., 100, 2331–2337.

[38] Berman, H. M.Westbrook, J.Feng, Z.Gilliland, G.Bhat, T. N.Weissig, H.Shindyalov, I. N. and Bourne, P. E. (2000) The protein data bank. Nucleic Acids Res., 28, 235–242.

[39] Dunitz, J. D. and Gavezzotti, A. (2005) Molecular recognition in organic crystals: directed intermolecular bonds or nonlocalized bonding? Angew. Chem. Int. Ed. Engl., 44, 1766–1787.

[40] Chen, R., Li, L. and Weng, Z. (2003) ZDOCK: an initial-stage protein-docking algorithm. Proteins, 52, 80–87.

[41] Kozakov, D.Brenke, R.Comeau, S. R. and Vajda, S. (2006) PIPER: an FFT-based protein docking program with pairwise potentials. Proteins, 65, 392–406.

[42] Kozakov, D.Hall, D. R.Beglov, D.Brenke, R.Comeau, S. R.Shen, Y.Li, K.Zheng, J.Vakili, P.Paschalidis, I. C. (2010) Achieving reliability and high accuracy in automated protein docking: Cluspro PIPER SDU and stability analysis in CAPRI rounds 13–19, Proteins. Proteins, 78, 3124–3130.

[43] de Vries, S. J.van Dijk, M. and Bonvin, A. M. (2010) The HADDOCK web server for data-driven biomolecular docking. Nat. Protoc., 5, 883–897.

[44] Lyskov, S. and Gray, J. J. (2008) The RosettaDock server for local protein-protein docking. Nucleic Acids Res., 36, W233-8.

[45] Schneidman-Duhovny, D.Inbar, Y.Nussinov, R. and Wolfson, H. J. (2005) PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res., 33, W363-7.

[46] Fernández-Recio, J. and Sternberg, M. J. E. (2010) The 4th meeting on the Critical Assessment of Predicted Interaction (CAPRI) held at the Mare NostrumBarcelona Proteins, 78, 3065–3066.

[47] Aloy, P. and Russell, R. B. (2002) Interrogating protein interaction networks through structural biology. Proc. Natl. Acad. Sci. U.S.A., 99, 5896–5901.

[48] Aloy, P. and Russell, R. B. (2003) InterPreTS: protein interaction prediction through tertiary structure. Bioinformatics, 19, 161–162.

[49] Kundrotas, P. J.Lensink, M. F. and Alexov, E. (2008) Homology-based modeling of 3D structures of protein-protein complexes using alignments of modified sequence profiles. Int. J. Biol. Macromol., 43, 198–208.

[50] Zhang, Q. C.Petrey, D.Deng, L.Qiang, L.Shi, Y.Thu, C. A.Bisikirska, B.Lefebvre, C.Accili, D.Hunter, T. (2012) Structure-based prediction of protein-protein interactions on a genome-wide scale. Nature, 490, 556–560

[51] Ogmen, U.Keskin, O.Aytuna, A. S.Nussinov, R. and Gursoy, A. (2005) PRISM: protein interactions by structural matching. Nucleic Acids Res., 33, W331-6.

[52] Gunther, S.May, P.Hoppe, A.Frommel, C. and Preissner, R. (2007) Docking without docking: ISEARCH-prediction of interactions using known interfaces. Proteins, 69, 839–844.

[53] Sinha, R.Kundrotas, P. J. and Vakser, I. A. (2010) Docking by structural similarity at protein-protein interfaces. Proteins, 78, 3235–3241.

[54] Tyagi, M.Thangudu, R. R.Zhang, D.Bryant, S. H.Madej, T. and Panchenko, A. R. (2012) Homology inference of protein-protein interactions via conserved binding sites. PLoS ONE, 7, e28896

[55] Fraser, H. B.Wall, D. P. and Hirsh, A. E. (2003) A simple dependence between protein evolution rate and the number of protein-protein interactions. BMC Evol. Biol., 3, 11.

[56] Fraser, H. B. (2005) Modularity and evolutionary constraint on proteins. Nat. Genet., 37, 351–352.

[57] Choi, Y. S.Yang, J. S.Choi, Y.Ryu, S. H. and Kim, S. (2009) Evolutionary conservation in multiple faces of protein interaction. Proteins, 77, 14–25.

[58] Zhao, J.Dundas, J.Kachalo, S.Ouyang, Z. and Liang, J. (2011) Accuracy of functional surfaces on comparatively modeled protein structures. J. Struct. Funct. Genomics, 12, 97–107.

[59] Naveed, H.Jackups, R. Jr and Liang, J. (2009) Predicting weakly stable regions oligomerization state and protein-protein interfaces in transmembrane domains of outer membrane proteins. Proc. Natl. Acad. Sci. U. S. A., 106, 12735–12740

[60] Bordner, A. J. (2009) Predicting protein-protein binding sites in membrane proteins. BMC Bioinformatics, 10, 312.

[61] Gessmann, D.Mager, F.Naveed, H.Arnold, T.Weirich, S.Linke, D.Liang, J. and Nussberger, S. (2011) Improving the resistance of a eukaryotic β-barrel protein to thermal and chemical perturbations. J. Mol. Biol., 413, 150–161.

[62] Geula, S.Naveed, H.Liang, J. and Shoshan-Barmatz, V. (2012) Structure-based analysis of VDAC1 protein: defining oligomer contact sites. J. Biol. Chem., 287, 2179–2190

[63] Naveed, H.Jimenez-Morales, D.Tian, J.Pasupuleti, V.Kenney, L. J. and Liang, J. (2012) Engineered oligomerization state of OmpF protein through computational design decouples oligomer dissociation from unfolding. J. Mol. Biol., 419, 89–101.

[64] Naveed, H. and Liang, J. (2012) TMBB-Explorer: A Webserver to Predict the Structure, Oligomerization State PPI Interface and Thermodynamic Properties of the Transmembrane Domains of Outer Membrane Proteins. Biophys. J., 102, 469a.

[65] Levitt, D. G. and Banaszak, L. J. (1992) POCKET: a computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. J. Mol. Graph., 10, 174–177.

[66] Dundas, J.Ouyang, Z.Tseng, J.Binkowski, A.Turpaz, Y. and Liang, J. (2006) CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res., 34, W116-8.

[67] Eyrisch, S. and Helms, V. (2007) Transient pockets on protein surfaces involved in protein-protein interaction. J. Med. Chem., 50, 3457–3464.

[68] Shoemaker, B. A.Zhang, D.Tyagi, M.Thangudu, R. R.Fong, J. H.Marchler-Bauer, A.Bryant, S. H.Madej, T. and Panchenko, A. R. (2012) IBIS (Inferred Biomolecular Interaction Server) reports predicts and integrates multiple types of conserved interactions for proteins. Nucleic Acids Res., 40, D834–D840.

[69] Brady, G. P. Jr and Stouten, P. F. W. (2000) Fast prediction and visualization of protein binding pockets with PASS. J. Comput. Aided Mol. Des., 14, 383–401.

[70] Jeong, H.Tombor, B.Albert, R.Oltvai, Z. N. and Barabási, A.-L. (2000) The large-scale organization of metabolic networks. Nature,407, 651–654.

[71] Mirzarezaee, M.Araabi, B. N. and Sadeghi, M. (2010) Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces cerevisiae. BMC Syst. Biol., 4, 172.

[72] Dunker, A. K.Cortese, M. S.Romero, P.Iakoucheva, L. M. and Uversky, V. N. (2005) Flexible nets. The roles of intrinsic disorder in protein interaction networks. FEBS J., 272, 5129–5148.

[73] Sarmady, M.Dampier, W. and Tozeren, A. (2011) HIV protein sequence hotspots for crosstalk with host hub proteins. PLoS ONE, 6, e23293.

[74] Matthews, L. R.Vaglio, P.Reboul, J.Ge, H.Davis, B. P.Garrels, J.Vincent, S. and Vidal, M. (2001) Identification of potential interaction networks using sequence-based searches for conserved protein-protein interactions or “interologs”. Genome Res., 11, 2120–2126.

[75] Wang, X.Wei, X.Thijssen, B.Das, J.Lipkin, S. M. and Yu, H. (2012) Three-dimensional reconstruction of protein networks provides insight into human genetic disease. Nat. Biotechnol., 30, 159–164.

[76] Tuncbag, N.Gursoy, A.Nussinov, R. and Keskin, O. (2011) Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM. Nat. Protoc., 6, 1341–1354.

[77] Kuzu, G.Keskin, O.Gursoy, A. and Nussinov, R. (2012) Constructing structural networks of signaling pathways on the proteome scaleCurr. Opin. Struct. Biol., 22, 367–377.

[78] Shin, C. J.Wong, S.Davis, M. J. and Ragan, M. A. (2009) Protein-protein interaction as a predictor of subcellular location. BMC Syst. Biol., 3, 28.

[79] Jiang, J. Q. and Wu, M. (2012) Predicting multiplex subcellular localization of proteins using protein-protein interaction network: a comparative study. BMC Bioinformatics, 13, S20.

[80] Liu, J.Zhao, H.Tan, J.Luo, D.Yu, W.Harner, E. J. and Shih, W. J. (2008) Is subcellular localization informative for modeling protein-protein interaction signal? Research Letters in Signal Processing, DOI: 10.1155/2008/365152

[81] Kanehisa, M.Goto, S.Sato, Y.Furumichi, M. and Tanabe, M. (2012) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res., 40, D109–D114.

[82] Keseler, I. M.Mackie, A.Peralta-Gil, M.Santos-Zavaleta, A.Gama-Castro, S.Bonavides-Martínez, C.Fulcher, C.Huerta, A. M.Kothari, A.Krummenacker, M. (2013) EcoCyc: fusing model organism databases with systems biology. Nucleic Acids Res., 41, D605–D612.

[83] Caspi, R.Altman, T.Dale, J. M.Dreher, K.Fulcher, C. A.Gilham, F.Kaipa, P.Karthikeyan, A. S.Kothari, A.Krummenacker, M. (2010) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res.,38, D473–D479.

[84] Whitaker, J. W.Letunic, I.McConkey, G. A. and Westhead, D. R. (2009) MetaTIGER: a metabolic evolution resource. Nucleic Acids Res., 37, D531–D538.

[85] Ideker, T. and Sharan, R. (2008) Protein networks in disease. Genome Res., 18, 644–652.

[86] Wong, J. M.Ionescu, D. and Ingles, C. J. (2003) Interaction between BRCA2 and replication protein A is compromised by a cancer-predisposing mutation in BRCA2. Oncogene, 22, 28–33.

[87] Bruncko, M.Oost, T. K.Belli, B. A.Ding, H.Joseph, M. K.Kunzer, A.Martineau, D.McClellan, W. J.Mitten, M.Ng, S. C. (2007) Studies leading to potent dual inhibitors of Bcl-2 and Bcl-xL. J. Med. Chem., 50, 641–662.

[88] Schuster-Böckler, B. and Bateman, A. (2008) Protein interactions in human genetic diseases. Genome Biol., 9, R9.

[89] London, N.Raveh, B.Movshovitz-Attias, D. and Schueler-Furman, O. (2010) Can self-inhibitory peptides be derived from the interface of globular protein-protein interactions? Proteins, 78, 3140–3149.

[90] Eldar-Finkelman, H. and Eisenstein, M. (2009) Peptide inhibitors targeting protein kinases. Curr. Pharm. Des., 15, 2463–2470.

[91] Xie, L., Xie, L. and Bourne, P. E. (2011) Structure-based systems biology for analyzing off-target binding. Curr. Opin. Struct. Biol., 21, 189–199.

[92] Nwaka, S. and Hudson, A. (2006) Innovative lead discovery strategies for tropical diseases. Nat. Rev. Drug Discov., 5, 941–955.

[93] Arrowsmith, J. (2011) Trial watch: phase III and submission failures: 2007–2010. Nat. Rev. Drug Discov., 10, 87.

[94] Arrowsmith, J. (2011) Trial watch: Phase II failures: 2008–2010. Nat. Rev. Drug Discov., 10, 328–329

[95] Major, E. O. (2010) Progressive multifocal leukoencephalopathy in patients on immunomodulatory therapies. Annu. Rev. Med., 61, 35–47.

[96] Booth, B. and Zemmel, R. (2003) Quest for the best. Nat. Rev. Drug Discov., 2, 838–841.

[97] Mestres, J.Gregori-Puigjané E.Valverde, S. and Solé R. V. (2009) The topology of drug-target interaction networks: implicit dependence on drug properties and target families. Mol. Biosyst., 5, 1051–1057.

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

[99] Hopkins, A. L. and Groom, C. R. (2002) The druggable genome. Nat. Rev. Drug Discov., 1, 727–730.

[100] Bisson, W. H.Cheltsov, A. V.Bruey-Sedano, N.Lin, B.Chen, J.Goldberger, N.May, L. T.Christopoulos, A.Dalton, J. T.Sexton, P. M. (2007) Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs. Proc. Natl. Acad. Sci. U.S.A., 104, 11927–11932.

[101] Liu, C. I.Liu, G. Y.Song, Y.Yin, F.Hensler, M. E.Jeng, W. Y.Nizet, V.Wang, A. H. and Oldfield, E. (2008) A cholesterol biosynthesis inhibitor blocks Staphylococcus aureus virulence. Science, 319, 1391–1394.

[102] Specker, E.Böttcher, J.Lilie, H.Heine, A.Schoop, A.Müller, G.Griebenow, N. and Klebe, G. (2005) An old target revisited: two new privileged skeletons and an unexpected binding mode for HIV-protease inhibitors. Angew. Chem. Int. Ed. Engl., 44, 3140–3144.

[103] Weber, A.Casini, A.Heine, A.Kuhn, D.Supuran, C. T.Scozzafava, A. and Klebe, G. (2004) Unexpected nanomolar inhibition of carbonic anhydrase by COX-2-selective celecoxib: new pharmacological opportunities due to related binding site recognition. J. Med. Chem.,47, 550–557.

[104] Stauch, B.Hofmann, H.Perkovic, M.Weisel, M.Kopietz, F.Cichutek, K.Münk, C. and Schneider, G. (2009) Model structure of APOBEC3C reveals a binding pocket modulating ribonucleic acid interaction required for encapsidation. Proc. Natl. Acad. Sci. U.S.A.,106, 12079–12084.

[105] Amaro, R. E.Schnaufer, A.Interthal, H.Hol, W.Stuart, K. D. and McCammon, J. A. (2008) Discovery of drug-like inhibitors of an essential RNA-editing ligase in Trypanosoma brucei. Proc. Natl. Acad. Sci. U.S.A., 105, 17278–17283.

[106] Lounkine, E.Keiser, M. J.Whitebread, S.Mikhailov, D.Hamon, J.Jenkins, J. L.Lavan, P.Weber, E.Doak, A. K.Côté S. (2012) Large-scale prediction and testing of drug activity on side-effect targets. Nature486, 361–367.

[107] Butcher, E. C.Berg, E. L. and Kunkel, E. J. (2004) Systems biology in drug discovery. Nat. Biotechnol., 22, 1253–1259

[108] Yildirim, M. A.Goh, K. I.Cusick, M. E.Barabási, A. L. and Vidal, M. (2007) Drug-target network. Nat. Biotechnol., 25, 1119–1126.

[109] Taylor, I. W.Linding, R.Warde-Farley, D.Liu, Y.Pesquita, C.Faria, D.Bull, S.Pawson, T.Morris, Q. and Wrana, J. L. (2009) Dynamic modularity in protein interaction networks predicts breast cancer outcome. Nat. Biotechnol., 27, 199–204.

[110] Chang, R. L.Xie, L.Xie, L.Bourne, P. E. and Palsson, B. Ø. (2010) Drug off-target effects predicted using structural analysis in the context of a metabolic network model. PLOS Comput. Biol., 6, e1000938.

[111] Raman, K. and Chandra, N. (2008) Mycobacterium tuberculosis interactome analysis unravels potential pathways to drug resistance. BMC Microbiol., 8, 234.

[112] DiMasi, J. A.Hansen, R. W. and Grabowski, H. G. (2003) The price of innovation: new estimates of drug development costs. J. Health Econ.,22, 151–185.

[113] Hughes, J. P.Rees, S.Kalindjian, S. B. and Philpott, K. L. (2011) Principles of early drug discovery. Br. J. Pharmacol., 162, 1239–1249.

[114] Ashburn, T. T. and Thor, K. B. (2004) Drug repositioning: identifying and developing new uses for existing drugs. Nat. Rev. Drug Discov., 3, 673–683.

[115] Dudley, J. T.Deshpande, T. and Butte, A. J. (2011) Exploiting drug-disease relationships for computational drug repositioning. Brief. Bioinform., 12, 303–311.

[116] von Eichborn, J.Murgueitio, M. S.Dunkel, M.Koerner, S.Bourne, P. E. and Preissner, R. (2011) PROMISCUOUS: a database for network-based drug-repositioning. Nucleic Acids Res., 39, D1060–D1066.

[117] Chen, B.Dong, X.Jiao, D.Wang, H.Zhu, Q.Ding, Y. and Wild, D. J. (2010) Chem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology data. BMC Bioinformatics, 11, 255.

[118] Ekins, S.Williams, A. J.Krasowski, M. D. and Freundlich, J. S. (2011) In silico repositioning of approved drugs for rare and neglected diseases. Drug Discov. Today, 16, 298–310.

[119] Sardana, D.Zhu, C.Zhang, M.Gudivada, R. C.Yang, L. and Jegga, A. G. (2011) Drug repositioning for orphan diseases. Brief. Bioinform.,12, 346–356

[120] Campillos, M.Kuhn, M.Gavin, A. C.Jensen, L. J. and Bork, P. (2008) Drug target identification using side-effect similarity. Science321, 263–266.

[121] Duran-Frigola, M. and Aloy, P. (2012) Recycling side-effects into clinical markers for drug repositioning. Genome Med., 4 3.

[122] Rajkumar, S. V. (2004) Thalidomide: tragic past and promising future. Mayo Clin. Proc., 79, 899–903.

[123] Tatro, D. S. (1992) Drug Interaction Facts 1992. St Louis: Facts and Comparisons.

[124] Huang, J.Niu, C.Green, C. D.Yang, L.Mei, H. and Han, J.-D. (2013) Systematic prediction of pharmacodynamic drug-drug interactions through protein-protein-interaction network. PLoS Comput. Biol., 9, e1002998.

[125] Greco, F. and Vicent, M. J. (2009) Combination therapy: opportunities and challenges for polymer-drug conjugates as anticancer nanomedicines. Adv. Drug Deliv. Rev., 61, 1203–1213.

[126] Breen, E. C. and Walsh, J. J. (2010) Tubulin-targeting agents in hybrid drugs. Curr. Med. Chem., 17, 609–639.

[127] Altundag, O.Dursun, P. and Ayhan, A. (2010) Emerging drugs in endometrial cancers. Expert Opin. Emerg. Drugs, 15, 557–568.

[128] De Clercq, E. (2012) Where rilpivirine meets with tenofovir, the start of a new anti-HIV drug combination era. Biochem. Pharmacol.,84, 241–248.

[129] Schuelter, E.Luebke, N.Jensen, B.Zazzi, M.Sönnerborg, A.Lengauer, T.Incardona, F.Camacho, R.Schmit, J.Clotet, B. (2012) Etravirine in protease inhibitor-free antiretroviral combination therapies. J. Int. AIDS Soc., 15, 18260.

[130] Bogojeska, J. and Lengauer, T. (2012) Hierarchical Bayes Model for predicting effectiveness of HIV combination therapies. Stat. Appl. Genet. Mol. Biol., 11, 11.

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg