Feasibility of using molecular docking-based virtual screening for searching dual target kinase inhibitors

Journal of Chemical Information and Modeling

Volumn 53, Issue 4, 2013, Pages 982-996

  Zhou, Shunye ^a   Li, Youyong ^a   Hou, Tingjun ^a,b  

^a SOOCHOW UNIVERSITY   (China)

^b ZHEJIANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ENZYME INHIBITION;

FALSE POSITIVE RATES; KINASE INHIBITORS; MOLECULAR DOCKING; MULTIPLE KINASE; PREDICTION ACCURACY; STRUCTURAL CLUSTERING; THEORETICAL APPROACH; VIRTUAL SCREENING;

MOLECULAR MODELING;

CDK2 PROTEIN, HUMAN; CYCLIN DEPENDENT KINASE 2; GLYCOGEN SYNTHASE KINASE 3; GLYCOGEN SYNTHASE KINASE 3 BETA; LIGAND; PROTEIN KINASE INHIBITOR; PROTEIN TYROSINE KINASE;

ARTICLE; BINDING SITE; CHEMICAL DATABASE; CHEMISTRY; CLUSTER ANALYSIS; DRUG ANTAGONISM; DRUG DEVELOPMENT; FEASIBILITY STUDY; HUMAN; KINETICS; MOLECULAR DOCKING; PREDICTIVE VALUE; PROTEIN BINDING; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

BINDING SITES; CLUSTER ANALYSIS; CYCLIN-DEPENDENT KINASE 2; DATABASES, CHEMICAL; DRUG DISCOVERY; FEASIBILITY STUDIES; GLYCOGEN SYNTHASE KINASE 3; HUMANS; KINETICS; LIGANDS; MOLECULAR DOCKING SIMULATION; PREDICTIVE VALUE OF TESTS; PROTEIN BINDING; PROTEIN KINASE INHIBITORS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RECEPTOR PROTEIN-TYROSINE KINASES; SRC-FAMILY KINASES;

EID: 84876570722     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci400065e     Document Type: Article

References (49)

1. Drews, J. Drug discovery: A historical perspective Science 2000, 287, 1960-1964
2. Morphy, R. Selectively Nonselective Kinase Inhibition: Striking the Right Balance J. Med. Chem. 2010, 53, 1413-1437
3. Keith, C. T.; Borisy, A. A.; Stockwell, B. R. Multicomponent therapeutics for networked systems Nat. Rev. Drug Discov. 2005, 4, 71-78
4. Zimmermann, G. R.; Lehar, J.; Keith, C. T. Multi-target therapeutics: when the whole is greater than the sum of the parts Drug Discov. Today 2007, 12, 34-42
5. 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
6. Morphy, R.; Kay, C.; Rankovic, Z. From magic bullets to designed multiple ligands Drug Discov. Today 2004, 9, 641-651
7. Thangapandian, S.; John, S.; Sakkiah, S.; Lee, K. W. Molecular Docking and Pharmacophore Filtering in the Discovery of Dual-Inhibitors for Human Leukotriene A4 Hydrolase and Leukotriene C4 Synthase J. Chem. Inf. Model. 2011, 51, 33-44
8. Capdeville, R.; Buchdunger, E.; Zimmermann, J.; Matter, A. Glivec (ST1571, Imatinib), a rationally developed, targeted anticancer drug Nat. Rev. Drug Discov. 2002, 1, 493-502
9. Motzer, R. J.; Michaelson, M. D.; Redman, B. G.; Hudes, G. R.; Wilding, G.; Figlin, R. A.; Ginsberg, M. S.; Kim, S. T.; Baum, C. M.; DePrimo, S. E.; Li, J. Z.; Bello, C. L.; Theuer, C. P.; George, D. J.; Rini, B. I. Activity of SU11248, a multitargeted inhibitor of vascular endothelial growth factor receptor and platelet-derived growth factor receptor, in patients with metastatic renal cell carcinoma J. Clin. Oncol. 2006, 24, 16-24
10. Wilhelm, S.; Carter, C.; Lynch, M.; Lowinger, T.; Dumas, J.; Smith, R. A.; Schwartz, B.; Simantov, R.; Kelley, S. Discovery and development of sorafenib: a multikinase inhibitor for treating cancer Nat. Rev. Drug Discov. 2006, 5, 835-844
11. Quintas-Cardama, A.; Kantarjian, H.; Jones, D.; Nicaise, C.; O'Brien, S.; Giles, F.; Talpaz, M.; Cortes, J. Dasatinib (BMS-354825) is active in Philadelphia chromosome-positive chronic myelogenous leukemia after imatinib and nilotinib (AMN 107) therapy failure Blood 2007, 109, 497-499
12. Wood, E. R.; Truesdale, A. T.; McDonald, O. B.; Yuan, D.; Hassell, A.; Dickerson, S. H.; Ellis, B.; Pennisi, C.; Horne, E.; Lackey, K.; Alligood, K. J.; Rusnak, D. W.; Gilmer, T. M.; Shewchuk, L. A unique structure for epidermal growth factor receptor bound to GW572016 (Lapatinib): Relationships among protein conformation, inhibitor off-rate, and receptor activity in tumor cells Cancer Res. 2004, 64, 6652-6659
13. Scapin, G. Structural biology in drug design: selective protein kinase inhibitors Drug Discov. Today 2002, 7, 601-611
14. Kinnings, S. L.; Jackson, R. M. Binding Site Similarity Analysis for the Functional Classification of the Protein Kinase Family J. Chem. Inf. Model. 2009, 49, 318-329
15. Fabian, M. A.; Biggs, W. H.; Treiber, D. K.; Atteridge, C. E.; Azimioara, M. D.; Benedetti, M. G.; Carter, T. A.; Ciceri, P.; Edeen, P. T.; Floyd, M.; Ford, J. M.; Galvin, M.; Gerlach, J. L.; Grotzfeld, R. M.; Herrgard, S.; Insko, D. E.; Insko, M. A.; Lai, A. G.; Lelias, J. M.; Mehta, S. A.; Milanov, Z. V.; Velasco, A. M.; Wodicka, L. M.; Patel, H. K.; Zarrinkar, P. P.; Lockhart, D. J. A small molecule-kinase interaction map for clinical kinase inhibitors Nat. Biotechnol. 2005, 23, 329-336
16. Fedorov, O.; Marsden, B.; Pogacic, V.; Rellos, P.; Mueller, S.; Bullock, A. N.; Schwaller, J.; Sundstrom, 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
17. 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
18. Posy, S. L.; Hermsmeier, M. A.; Vaccaro, W.; Ott, K.-H.; Todderud, G.; Lippy, J. S.; Trainor, G. L.; Loughney, D. A.; Johnson, S. R. Trends in Kinase Selectivity Insights for Target Class-Focused Library Screening J. Med. Chem. 2011, 54, 54-66
19. Smyth, L. A.; Collins, I. Measuring and interpreting the selectivity of protein kinase inhibitors J. Chem. Biol. 2009, 2, 131-51
20. Goldstein, D. M.; Gray, N. S.; Zarrinkar, P. P. High-throughput kinase profiling as a platform for drug discovery Nat. Rev. Drug Discov. 2008, 7, 391-397
21. Sheridan, R. P.; Nam, K.; Maiorov, V. N.; McMasters, D. R.; Cornell, W. D. QSAR Models for Predicting the Similarity in Binding Profiles for Pairs of Protein Kinases and the Variation of Models between Experimental Data Sets J. Chem. Inf. Model. 2009, 49, 1974-1985
22. Niijima, S.; Shiraishi, A.; Okuno, Y. Dissecting Kinase Profiling Data to Predict Activity and Understand Cross-Reactivity of Kinase Inhibitors J. Chem. Inf. Model. 2012, 52, 901-912
23. Sciabola, S.; Stanton, R. V.; Wittkopp, S.; Wildman, S.; Moshinsky, D.; Potluri, S.; Xi, H. Predicting kinase selectivity profiles using free-Wilson QSAR analysis J. Chem. Inf. Model. 2008, 48, 1851-1867
24. Martin, E.; Mukherjee, P.; Sullivan, D.; Jansen, J. Profile-QSAR: A Novel meta-QSAR Method that Combines Activities across the Kinase Family To Accurately Predict Affinity, Selectivity, and Cellular Activity J. Chem. Inf. Model. 2011, 51, 1942-1956
25. Zhang, X.; Fernandez, A. In silico drug profiling of the human kinome based on a molecular marker for cross reactivity Mol. Pharmaceutics 2008, 5, 728-738
26. Lapins, M.; Wikberg, J. E. S. Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques BMC Bioinf. 2010, 11, 339-354
27. Martin, E.; Mukherjee, P. Kinase-Kernel Models: Accurate In silico Screening of 4 Million Compounds Across the Entire Human Kinome J. Chem. Inf. Model. 2012, 52, 156-170
28. Ma, X. H.; Wang, R.; Tan, C. Y.; Jiang, Y. Y.; Lu, T.; Rao, H. B.; Li, X. Y.; Go, M. L.; Low, B. C.; Chen, Y. Z. Virtual Screening of Selective Multitarget Kinase Inhibitors by Combinatorial Support Vector Machines Mol. Pharmaceutics 2010, 7, 1545-1560
29. Gozalbes, R.; Simon, L.; Froloff, N.; Sartori, E.; Monteils, C.; Baudelle, R. Development and experimental validation of a docking strategy for the generation of kinase-targeted libraries J. Med. Chem. 2008, 51, 3124-3132
30. Ma, X. H.; Shi, Z.; Tan, C.; Jiang, Y.; Go, M. L.; Low, B. C.; Chen, Y. Z. In-Silico Approaches to Multi-target Drug Discovery Pharm. Res. 2010, 27, 739-749
31. Liu, T.; Lin, Y.; Wen, X.; Jorissen, R. N.; Gilson, M. K. BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities Nucleic Acids Res. 2007, 35, D198-D201
32. Desai, P. V.; Patny, A.; Sabnis, Y.; Tekwani, B.; Gut, J.; Rosenthal, P.; Srivastava, A.; Avery, M. Identification of novel parasitic cysteine protease inhibitors using virtual screening. 1. The ChemBridge database J. Med. Chem. 2004, 47, 6609-6615
33. Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, P. E. The Protein Data Bank Nucleic Acids Res. 2000, 28, 235-242
34. Cozzini, P.; Kellogg, G. E.; Spyrakis, F.; Abraham, D. J.; Costantino, G.; Emerson, A.; Fanelli, F.; Gohlke, H.; Kuhn, L. A.; Morris, G. M.; Orozco, M.; Pertinhez, T. A.; Rizzi, M.; Sotriffer, C. A. Target Flexibility: An Emerging Consideration in Drug Discovery and Design J. Med. Chem. 2008, 51, 6237-6255
35. Russell, R. B.; Barton, G. J. Multiple protein sequence alignment from tertiary structure comparison: Assignment of global and residue confidence levels Proteins-Struct. Funct. Genet. 1992, 14, 309-323
36. Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual molecular dynamics J. Molec. Graph. Modell. 1996, 14, 33-38
37. Leng, L.; Chen, L.; Fan, J.; Greven, D.; Arjona, A.; Du, X.; Austin, D.; Kashgarian, M.; Yin, Z.; Huang, X. R. A small-molecule macrophage migration inhibitory factor antagonist protects against glomerulonephritis in lupus-prone NZB/NZW F1 and MRL/lpr mice J. Immunol. 2011, 186, 527-538
38. Kaminski, G. A.; Friesner, R. A.; Tirado-Rives, J.; Jorgensen, W. L. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides J. Phys. Chem. B 2001, 105, 6474-6487
39. Brown, F. G.; Nikolic-Paterson, D. J.; Hill, P. A.; Isbel, N. M.; Dowling, J.; Metz, C. M.; Atkins, R. C. Urine macrophage migration inhibitory factor reflects the severity of renal injury in human glomerulonephritis J. Am. Soc. Nephrol. 2002, 13, S7-S13
40. Discovery Studio 2.5 Guide; Accelrys Inc., San Diego, 2009, http://www.accelrys.com.
41. Yan, X.; Xue-jun, L. Multi-target therapeutics and new drug discovery Acta Pharmaceutica Sin. 2009, 44, 226-230
42. Schrödinger, version 9.0; Schrödinger, LLC, New York, NY, 2009, http://www.schrodinger.com.
43. Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.; Repasky, M. P.; Knoll, E. H.; Shelley, M.; Perry, J. K.; Shaw, D. E.; Francis, P.; Shenkin, P. S. Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy J. Med. Chem. 2004, 47, 1739-1749
44. Totrov, M.; Abagyan, R. Flexible ligand docking to multiple receptor conformations: a practical alternative Curr. Opin. Struct. Biol. 2008, 18, 178-184
45. B-Rao, C.; Subramanian, J.; Sharma, S. D. Managing protein flexibility in docking and its applications Drug Discov. Today 2009, 14, 394-400
46. Sheridan, R.; McGaughey, G.; Cornell, W. Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results J. Comput.-Aided Molec. Des. 2008, 22, 257-265
47. Santiago, D. N.; Pevzner, Y.; Durand, A. A.; Tran, M.; Scheerer, R. R.; Daniel, K.; Sung, S. S.; Lee Woodcock, H.; Guida, W. C.; Brooks, W. H. Virtual Target Screening: Validation Using Kinase Inhibitors J. Chem. Inf. Model. 2012, 52, 2192-2203
48. Bottegoni, G.; Rocchia, W.; Rueda, M.; Abagyan, R.; Cavalli, A. Systematic Exploitation of Multiple Receptor Conformations for Virtual Ligand Screening PLoS ONE 2012, 6, e18845
49. Betzi, S.; Alam, R.; Martin, M.; Lubbers, D. J.; Han, H.; Jakkaraj, S. R.; Georg, G. I.; Schoenbrunn, E. Discovery of a Potential Allosteric Ligand Binding Site in CDK2 ACS Chem. Biol. 2011, 6, 492-501