Targeting molecular networks for drug research

Frontiers in Genetics

Volumn 5, Issue JUN, 2014, Pages

  Pinto, José P ^a   Machado, Rui S R ^a   Xavier, Joana M ^a   Futschik, Matthias E ^a  

^a UNIVERSITY OF ALGARVE   (Portugal)

Author keywords

Diseases; Drugs; Molecular interactions; Networks; Stem cells

Indexed keywords

GROWTH ARREST AND DNA DAMAGE INDUCIBLE PROTEIN 45; PARKIN; SYNUCLEIN;

DATA ANALYSIS; DRUG IDENTIFICATION; DRUG REPOSITIONING; DRUG RESEARCH; DRUG TARGETING; GENE CONTROL; GENE EXPRESSION; HUMAN; HUMAN GENOME; MOLECULAR BIOLOGY; MOLECULAR DOCKING; MOLECULAR INTERACTION; MOLECULAR NETWORK; NEUROLOGIC DISEASE; PHENOTYPIC VARIATION; PROTEIN PROTEIN INTERACTION; SHORT SURVEY; SIDE EFFECT; SYSTEMATIC REVIEW (TOPIC);

EID: 84906249332     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2014.00160     Document Type: Short Survey

References (45)

1. Albert, R. (2005). Scale-free networks in cell biology. J. Cell Sci. 118, 4947-4957. doi: 10.1242/jcs.02714
2. Al-Lazikani, B., Banerji, U., and Workman, P. (2012). Combinatorial drug therapy for cancer in the post-genomic era. Nat. Biotechnol. 30, 679-692. doi: 10.1038/nbt.2284
3. Badano, J. L., and Katsanis, N. (2002). Beyond Mendel: an evolving view of human genetic disease transmission. Nat. Rev. Genet. 3, 779-789. doi: 10.1038/nrg910
4. Barabási, A. L., Gulbahce, N., and Loscalzo, J. (2011). Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 12, 56-68. doi: 10.1038/nrg2918
5. Campillos, M., Kuhn, M., Gavin, A. C., Jensen, L. J., and Bork, P. (2008). Drug target identification using side-effect similarity. Science 321, 263-266. doi: 10.1126/science.1158140
6. Chaurasia, G., Iqbal, Y., Hänig, C., Herzel, H., Wanker, E. E., and Futschik, M. E. (2007). UniHI: an entry gate to the human protein interactome. Nucleic Acids Res. 35(Suppl. 1), D590-D594. doi: 10.1093/nar/gkl817
7. Cheng, F., Liu, C., Jiang, J., Lu, W., Li, W., Liu, G., et al. (2012). Prediction of drug-target interactions and drug repositioning via network-based inference. PLoS Comput. Biol. 8:e1002503. doi: 10.1371/journal.pcbi.1002503
8. Csermely, P., Korcsmáros, T., Kiss, H. J., London, G., and Nussinov, R. (2013). Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol. Ther. 138, 333-408. doi: 10.1016/j.pharmthera.2013.01.016
9. De Cegli, R., Iacobacci, S., Flore, G., Gambardella, G., Mao, L., Cutillo, L., et al. (2013). Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation. Nucleic Acids Res. 41, 711-726. doi: 10.1093/nar/gks1136
10. Futschik, M. E., Chaurasia, G., and Herzel, H. (2007). Comparison of human protein-protein interaction maps. Bioinformatics 23, 605-611. doi: 10.1093/bioinformatics/btl683
11. Gashaw, I., Ellinghaus, P., Sommer, A., and Asadullah, K. (2011). What makes a good drug target? Drug Discov. Today 16, 1037-1043. doi: 10.1016/j.drudis.2011.09.007
12. Hartwell, L., Hopfield, J., Leibler, S., and Murray, A. (1999). From molecular to modular cell biology. Nature 402(Suppl.), C47-C52. doi: 10.1038/35011540
13. Hopkins, A. L. (2008). Network pharmacology: the next paradigm in drug discovery. Nat. Chem. Biol. 4, 682-690. doi: 10.1038/nchembio.118
14. Hou, P., Li, Y., Zhang, X., Liu, C., Guan, J., Li, H., et al. (2013). Pluripotent stem cells induced from mouse somatic cells by small-molecule compounds. Science 341, 651-654. doi: 10.1126/science.1239278
15. Huang, J., Niu, C., Green, C. D., Yang, L., Mei, H., and Han, J.-D. J. (2013). Systematic prediction of pharmacodynamic drug-drug interactions through protein-protein-interaction network. PLoS Comput. Biol. 9:e1002998. doi: 10.1371/journal.pcbi.1002998
16. Huangfu, D., Maehr, R., Guo, W., Eijkelenboom, A., Snitow, M., Chen, A. E., et al. (2008). Induction of pluripotent stem cells by defined factors is greatly improved by small-molecule compounds. Nat. biotechnol. 26, 795-797. doi: 10.1038/nbt1418
17. Hwang, W. C., Zhang, A., and Ramanathan, M. (2008). Identification of information flow-modulating drug targets: a novel bridging paradigm for drug discovery. Clin. Pharmacol. Ther. 84, 563-572. doi: 10.1038/clpt.2008.129
18. Iorio, F., Bosotti, R., Scacheri, E., Belcastro, V., Mithbaokar, P., Ferriero, R., et al. (2010). Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc. Natl. Acad. Sci. U.S.A. 107, 14621-14626. doi: 10.1073/pnas.1000138107
19. Kalathur, R. K., Pinto, J. P., Hernández-Prieto, M. A., Machado, R. S., Almeida, D., Chaurasia, G., et al. (2014). UniHI 7: an enhanced database for retrieval and interactive analysis of human molecular interaction networks. Nucleic Acids Res. 42, D408-D414. doi: 10.1093/nar/gkt1100
20. Keiser, M. J., Setola, V., Irwin, J. J., Laggner, C., Abbas, A. I., Hufeisen, S. J., et al. (2009). Predicting new molecular targets for known drugs. Nature 462, 175-181. doi: 10.1038/nature08506
21. Knox, C., Law, V., Jewison, T., Liu, P., Ly, S., Frolkis, A., et al. (2011). DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res. 39(Suppl. 1), D1035-D1041. doi: 10.1093/nar/gkq1126
22. Korcsmáros, T., Farkas, I. J., Szalay, M. S., Rovó, P., Fazekas, D., Spiró, Z., et al. (2010). Uniformly curated signaling pathways reveal tissue-specific cross-talks and support drug target discovery. Bioinformatics 26, 2042-2050. doi: 10.1093/bioinformatics/btq310
23. Kuhn, M., Campillos, M., Letunic, I., Jensen, L. J., and Bork, P. (2010). A side effect resource to capture phenotypic effects of drugs. Mol. Syst. Biol. 6, 343. doi: 10.1038/msb.2009.98
24. Kuhn, M., Szklarczyk, D., Franceschini, A., von Mering, C., Jensen, L. J., and Bork, P. (2012). STITCH 3: zooming in on protein-chemical interactions. Nucleic Acids Res. 40, D876-D880. doi: 10.1093/nar/gkr1011
25. Laenen, G., Thorrez, L., Börnigen, D., and Moreau, Y. (2013). Finding the targets of a drug by integration of gene expression data with a protein interaction network. Mol. Biosyst. 9, 1676-1685. doi: 10.1039/C3MB25438K
26. Lee, H. S., Bae, T., Lee, J. H., Kim, D. G., Oh, Y. S., Jang, Y., et al. (2012). Rational drug repositioning guided by an integrated pharmacological network of protein, disease and drug. BMC Syst. Biol. 6:80. doi: 10.1186/1752-0509-6-80
27. Luo, H., Chen, J., Shi, L., Mikailov, M., Zhu, H., Wang, K., 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(Suppl. 2), W492-W498. doi: 10.1093/nar/gkr299
28. Manolio, T. A. (2010). Genomewide association studies and assessment of the risk of disease. N. Engl. J. Med. 363, 166-176. doi: 10.1056/NEJMra0905980
29. Marbach, D., Costello, J. C., Küffner, R., Vega, N. M., Prill, R. J., Camacho, D. M., et al. (2012). Wisdom of crowds for robust gene network inference. Nat. Methods 9, 796-804. doi: 10.1038/nmeth.2016
30. Mathur, S., and Dinakarpandian, D. (2011). Drug repositioning using disease associated biological processes and network analysis of drug targets. AMIA Annu. Symp. Proc. 2011, 305-311.
31. Milenkoviæ, T., Memiševiæ, V., Bonato, A., and Pržulj, N. (2011). Dominating biological networks. PLoS ONE 6:e23016. doi: 10.1371/journal.pone.0023016
32. Mizutani, S., Pauwels, E., Stoven, V., Goto, S., and Yamanishi, Y. (2012). Relating drug-protein interaction network with drug side effects. Bioinformatics 28, i522-i528. doi: 10.1093/bioinformatics/bts383
33. Oti, M., and Brunner, H. G. (2007). The modular nature of genetic diseases. Clin. Genet. 71, 1-11. doi: 10.1111/j.1399-0004.2006.00708.x
34. Overington, J. P., Al-Lazikani, B., and Hopkins, A. L. (2006). How many drug targets are there? Nat. Rev. Drug Discov. 5, 993-996. doi: 10.1038/nrd2199
35. Pacini, C., Iorio, F., Gonçalves E., Iskar, M., Klabunde, T., Bork, P., et al. (2013). DvD: an R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data. Bioinformatics 29, 132-134. doi: 10.1093/bioinformatics/bts656
36. Pinto, J. P. (2012). Computational Tools for Large-Scale Biological Network Analysis . Ph.D. thesis, University of Minho, Braga.
37. Prinz, F., Schlange, T., and Asadullah, K. (2011). Believe it or not: how much can we rely on published data on potential drug targets? Nat. Rev. Drug Discov . 10, 712-712. doi: 10.1038/nrd3439-c1
38. Silva, J., Barrandon, O., Nichols, J., Kawaguchi, J., Theunissen, T. W., and Smith, A. (2008). Promotion of reprogramming to ground state pluripotency by signal inhibition. PLoS Biol . 6:e253. doi: 10.1371/journal.pbio.0060253
39. Takahashi, K., and Yamanaka, S. (2006). Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663-676. doi: 10.1016/j.cell.2006.07.024
40. Tobinick, E. L. (2009). The value of drug repositioning in the current pharmaceutical market. Drug News Perspect. 22, 119-125. doi: 10.1358/dnp.2009.22.2.1343228
41. 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(Suppl. 1), D1060-D1066. doi: 10.1093/nar/gkq1037
42. Wagner, A. (2005). Distributed robustness versus redundancy as causes of mutational robustness. Bioessays 27, 176-188. doi: 10.1002/bies.20170
43. Wells, J. A., and McClendon, C. L. (2007). Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450, 1001-1009. doi: 10.1038/nature06526
44. Yamanishi, Y., Araki, M., Gutteridge, A., Honda, W., and Kanehisa, M. (2008). Prediction of drug-target interaction networks from the integration of chemical and genomic spaces. Bioinformatics 24, i232-i240. doi: 10.1093/bioinformatics/btn162
45. Yildirim, M. A., Goh, K. I., Cusick, M. E., Barabási, A. L., and Vidal, M. (2007). Drug-target network. Nat. Biotechnol . 25, 1119-1126. doi: 10.1038/nbt1338