Making sense of large-scale kinase inhibitor bioactivity data sets: A comparative and integrative analysis

Journal of Chemical Information and Modeling

Volumn 54, Issue 3, 2014, Pages 735-743

  Tang, Jing ^a   Szwajda, Agnieszka ^a   Shakyawar, Sushil ^a   Xu, Tao ^a   Hintsanen, Petteri ^a   Wennerberg, Krister ^a   Aittokallio, Tero ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BIOACTIVITY; DATABASE SYSTEMS; DRUG INTERACTIONS; ENZYME INHIBITION; PETROLEUM RESERVOIR EVALUATION;

COMPARATIVE EVALUATIONS; COMPUTATIONAL STRATEGY; DATA HETEROGENEITY; DRUG-TARGET INTERACTIONS; INTEGRATIVE ANALYSIS; KINASE INHIBITORS; MODEL-BASED INTEGRATIONS; SYSTEMATIC EVALUATION;

CLASSIFICATION (OF INFORMATION);

PROTEIN KINASE; PROTEIN KINASE INHIBITOR;

ANIMAL; BIOLOGY; COMPARATIVE STUDY; DRUG DEVELOPMENT; FACTUAL DATABASE; HUMAN; METABOLISM; PROCEDURES;

ANIMALS; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; DRUG DISCOVERY; HUMANS; PROTEIN KINASE INHIBITORS; PROTEIN KINASES;

EID: 84896960173     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci400709d     Document Type: Article

References (50)

1. Overington, J. P.; Al-Lazikani, B.; Hopkins, A. L. How many drug targets are there? Nat. Rev. Drug Discovery 2006, 5, 993-996
2. Hopkins, A. L. Network pharmacology: the next paradigm in drug discovery Nat. Chem. Biol. 2008, 4, 682-690
3. Tang, J.; Karhinen, L.; Xu, T.; Szwajda, A.; Yadav, B.; Wennerberg, K.; Aittokallio, T. Target inhibition networks: predicting selective combinations of druggable targets to block cancer survival pathways PLoS Comput. Biol. 2013, 9, e1003226
4. Xie, L.; Xie, L.; Kinnings, S. L.; Bourne, P. E. Novel computational approaches to polypharmacology as a means to define responses to individual drugs Annu. Rev. Pharmacol. Toxicol. 2012, 52, 361-379
5. Kitano, H. A robustness-based approach to systems-oriented drug design Nat. Rev. Drug Discovery 2007, 6, 202-210
6. Lehár, J.; Krueger, A. S.; Avery, W.; Heilbut, A. M.; Johansen, L. M.; Price, E. R.; Rickles, R. J.; Short, G. F., 3rd; Staunton, J. E.; Jin, X.; Lee, M. S.; Zimmermann, G. R.; Borisy, A. A. Synergistic drug combinations tend to improve therapeutically relevant selectivity Nat. Biotechnol. 2009, 27, 659-666
7. Knight, Z. A.; Lin, H.; Shokat, K. M. Targeting the cancer kinome through polypharmacology Nat. Rev. Cancer 2010, 10, 130-137
8. Karczewski, K. J.; Daneshjou, R.; Altman, R. B. Chapter 7: Pharmacogenomics PLoS Comput. Biol. 2012, 8, e1002817
9. Futamura, Y.; Muroi, M.; Osada, H. Target identification of small molecules based on chemical biology approaches Mol. Biosyst. 2013, 9, 897-914
10. Zhao, S.; Iyengar, R. Systems pharmacology: network analysis to identify multiscale mechanisms of drug action Annu. Rev. Pharmacol. Toxicol. 2012, 52, 505-521
11. Tang, J.; Aittokallio, T. Network pharmacology strategies toward multi-target anticancer therapies: from computational models to experimental design principles Curr. Pharm. Des. 2014, 20, 23-36
12. Li, Y. Y.; Jones, S. J. Drug repositioning for personalized medicine Genome Med. 2012, 4, 27
13. Yildirim, M. A.; Goh, K.-I.; Cusick, M. E.; Barabási, A.-L.; Vidal, M. Drug-target network Nat. Biotechnol. 2007, 25, 1119-1126
14. Janga, S. C.; Tzakos, A. Structure and organization of drug-target networks: insights from genomic approaches for drug discovery Mol. Biosyst. 2009, 5, 1536-1548
15. Azuaje, F. J.; Zhang, L.; Devaux, Y.; Wagner, D. R. Drug-target network in myocardial infarction reveals multiple side effects of unrelated drugs Sci. Rep. 2011, 1, 52
16. Takigawa, I.; Tsuda, K.; Mamitsuka, H. Mining significant substructure pairs for interpreting polypharmacology in drug-target network PloS One 2011, 6, e16999
17. Cheng, F.; Liu, C.; Jiang, J.; Lu, W.; Li, W.; Liu, G.; Zhou, W.; Huang, J.; Tang, Y. Prediction of drug-target interactions and drug repositioning via network-based inference PLoS Comput. Biol. 2012, 8, e1002503
18. Mestres, J.; Gregori-Puigjané, E.; Valverde, S.; Solé, R. V. Data completeness - the Achilles heel of drug-target networks Nat. Biotechnol. 2008, 26, 983-984
19. Kanehisa, M.; Goto, S.; Sato, Y.; Furumichi, M.; Tanabe, M. KEGG for integration and interpretation of large-scale molecular data sets Nucleic Acids Res. 2012, 40, D109-114
20. Chang, A.; Scheer, M.; Grote, A.; Schomburg, I.; Schomburg, D. Nucleic Acids Res. 2009, 37, D588-592
21. Hecker, N.; Ahmed, J.; von Eichborn, J.; Dunkel, M.; Macha, K.; Eckert, A.; Gilson, M. K.; Bourne, P. E.; Preissner, R. SuperTarget goes quantitative: update on drug-target interactions Nucleic Acids Res. 2012, 40, D1113-1117
22. Zhu, F.; Shi, Z.; Qin, C.; Tao, L.; Liu, X.; Xu, F.; Zhang, L.; Song, Y.; Liu, X.; Zhang, J.; Han, B.; Zhang, P.; Chen, Y. Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery Nucleic Acids Res. 2012, 40, D1128-1136
23. Knox, C.; Law, V.; Jewison, T.; Liu, P.; Ly, S.; Frolkis, A.; Pon, A.; Banco, K.; Mak, C.; Neveu, V.; Djoumbou, Y.; Eisner, R.; Guo, A. C.; Wishart, D. S. DrugBank 3.0: a comprehensive resource for omics research on drugs Nucleic Acids Res. 2011, 39, D1035-1041
24. Yamanishi, Y. Chemogenomic approaches to infer drug-target interaction networks Methods Mol. Biol. 2013, 939, 97-113
25. Gönen, M. Predicting drug-target interactions from chemical and genomic kernels using Bayesian matrix factorization Bioinformatics 2012, 28, 2304-2310
26. Chen, H.; Zhang, Z. A semi-supervised method for drug-target interaction prediction with consistency in networks PloS One 2013, 8, e62975
27. Pahikkala, T.; Airola, A.; Pietilä, S.; Shakyawar, S.; Szwajda, A.; Tang, J.; Aittokallio, T. Toward more realistic drug-target interaction predictions. Submitted.
28. Gaulton, A.; Bellis, L. J.; Bento, A. P.; Chambers, J.; Davies, M.; Hersey, A.; Light, Y.; McGlinchey, S.; Michalovich, D.; Al-Lazikani, B.; Overington, J. P. ChEMBL: a large-scale bioactivity database for drug discovery Nucleic Acids Res. 2012, 40, D1100-1107
29. Lounkine, E.; Keiser, M. J.; Whitebread, S.; Mikhailov, D.; Hamon, J.; Jenkins, J. L.; Lavan, P.; Weber, E.; Doak, A. K.; Côté, S.; Shoichet, B. K.; Urban, L. Large-scale prediction and testing of drug activity on side-effect targets Nature 2012, 486, 361-367
30. Gfeller, D.; Michielin, O.; Zoete, V. Shaping the interaction landscape of bioactive molecules Bioinformatics 2013, 29, 3073-3079
31. Martínez-Jiménez, F.; Papadatos, G.; Yang, L.; Wallace, I. M.; Kumar, V.; Pieper, U.; Sali, A.; Brown, J. R.; Overington, J. P.; Marti-Renom, M. A. Target prediction for an open access set of compounds active against mycobacterium tuberculosis PLoS Comput. Biol. 2013, 9, e1003253
32. Kruger, F. A.; Overington, J. P. Global analysis of small molecule binding to related protein targets PLoS Comput. Biol. 2012, 8, e1002333
33. Kramer, C.; Kalliokoski, T.; Gedeck, P.; Vulpetti, A. The experimental uncertainty of heterogeneous public K(i) data J. Med. Chem. 2012, 55, 5165-5173
34. 50 data-a statistical analysis PloS One 2013, 8, e61007
35. Davis, M. I.; Hunt, J. P.; Herrgard, S.; Ciceri, P.; Wodicka, L. M.; Pallares, G.; Hocker, M.; Treiber, D. K.; Zarrinkar, P. P. Comprehensive analysis of kinase inhibitor selectivity Nat. Biotechnol. 2011, 29, 1046-1051
36. Metz, J. T.; Johnson, E. F.; Soni, N. B.; Merta, P. J.; Kifle, L.; Hajduk, P. J. Navigating the kinome Nat. Chem. Biol. 2011, 7, 200-202
37. Anastassiadis, T.; Deacon, S. W.; Devarajan, K.; Ma, H.; Peterson, J. R. Comprehensive assay of kinase catalytic activity reveals features of kinase inhibitor selectivity Nat. Biotechnol. 2011, 29, 1039-1045
38. Kuhn, M.; Szklarczyk, D.; Franceschini, A.; von Mering, C.; Jensen, L. J.; Bork, P. STITCH 3: zooming in on protein-chemical interactions Nucleic Acids Res. 2012, 40, D876-880
39. Karaman, M. W.; Herrgard, S.; Treiber, D. K.; Gallant, P.; Atteridge, C. E.; Campbell, B. T.; Chan, K. W.; Ciceri, P.; Davis, M. I.; Edeen, P. T.; Faraoni, R.; Floyd, M.; Hunt, J. P.; Lockhart, D. J.; Milanov, Z. V.; Morrison, M. J.; Pallares, G.; Patel, H. K.; Pritchard, S.; Wodicka, L. M.; Zarrinkar, P. P. A quantitative analysis of kinase inhibitor selectivity Nat. Biotechnol. 2008, 26, 127-132
40. Subramanian, A.; Tamayo, P.; Mootha, V. K.; Mukherjee, S.; Ebert, B. L.; Gillette, M. A.; Paulovich, A.; Pomeroy, S. L.; Golub, T. R.; Lander, E. S.; Mesirov, J. P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 15545-15550
41. Robin, X.; Turck, N.; Hainard, A.; Tiberti, N.; Lisacek, F.; Sanchez, J.-C.; Müller, M. pROC: an open-source package for R and S+ to analyze and compare ROC curves BMC Bioinf. 2011, 12, 77
42. Cer, R. Z.; Mudunuri, U.; Stephens, R.; Lebeda, F. J. IC50-to-Ki: a web-based tool for converting IC50 to Ki values for inhibitors of enzyme activity and ligand binding Nucleic Acids Res. 2009, 37, W441-445
43. Chen, N.; Bürli, R. W.; Neira, S.; Hungate, R.; Zhang, D.; Yu, V.; Nguyen, Y.; Tudor, Y.; Plant, M.; Flynn, S.; Meagher, K. L.; Lee, M. R.; Zhang, X.; Itano, A.; Schrag, M.; Xu, Y.; Ng, G. Y.; Hu, E. Discovery of a potent and selective c-Kit inhibitor for the treatment of inflammatory diseases Bioorg. Med. Chem. Lett. 2008, 18, 4137-4141
44. Dietrich, J.; Hulme, C.; Hurley, L. H. The design, synthesis, and evaluation of 8 hybrid DFG-out allosteric kinase inhibitors: a structural analysis of the binding interactions of Gleevec, Nexavar, and BIRB-796 Bioorg. Med. Chem. 2010, 18, 5738-5748
45. Yonesaka, K.; Zejnullahu, K.; Okamoto, I.; Satoh, T.; Cappuzzo, F.; Souglakos, J.; Ercan, D.; Rogers, A.; Roncalli, M.; Takeda, M.; Fujisaka, Y.; Philips, J.; Shimizu, T.; Maenishi, O.; Cho, Y.; Sun, J.; Destro, A.; Taira, K.; Takeda, K.; Okabe, T.; Swanson, J.; Itoh, H.; Takada, M.; Lifshits, E.; Okuno, K.; Engelman, J. A.; Shivdasani, R. A.; Nishio, K.; Fukuoka, M.; Varella-Garcia, M.; Nakagawa, K.; Jänne, P. A. Activation of ERBB2 signaling causes resistance to the EGFR-directed therapeutic antibody cetuximab Sci. Transl. Med. 2011, 3, 99ra86
46. Seeliger, M. A.; Nagar, B.; Frank, F.; Cao, X.; Henderson, M. N.; Kuriyan, J. c-Src binds to the cancer drug imatinib with an inactive Abl/c-Kit conformation and a distributed thermodynamic penalty Structure 2007, 15, 299-311
47. Iorio, F.; Rittman, T.; Ge, H.; Menden, M.; Saez-Rodriguez, J. Transcriptional data: a new gateway to drug repositioning? Drug Discovery Today 2013, 18, 350-357
48. Zhang, C.; Habets, G.; Bollag, G. Interrogating the kinome Nat. Biotechnol. 2011, 29, 981-983
49. Fedorov, O.; Marsden, B.; Pogacic, V.; Rellos, P.; Müller, S.; Bullock, A. N.; Schwaller, J.; Sundström, M.; Knapp, S. A systematic interaction map of validated kinase inhibitors with Ser/Thr kinases Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 20523-20528
50. Taipale, M.; Krykbaeva, I.; Whitesell, L.; Santagata, S.; Zhang, J.; Liu, Q.; Gray, N. S.; Lindquist, S. Chaperones as thermodynamic sensors of drug-target interactions reveal kinase inhibitor specificities in living cells Nat. Biotechnol. 2013, 31, 630-637