Profile-QSAR: A novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity

Journal of Chemical Information and Modeling

Volumn 51, Issue 8, 2011, Pages 1942-1956

  Martin, Eric ^a   Mukherjee, Prasenjit ^a   Sullivan, David ^a,b   Jansen, Johanna ^a  

^a NOVARTIS INSTITUTES FOR BIOMEDICAL RESEARCH   (United States)

^b PFIZER INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINDERS; CELL PROLIFERATION; COMPUTATIONAL CHEMISTRY; FORECASTING; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; MATRIX ALGEBRA; MOLECULAR GRAPHICS; PREDICTIVE ANALYTICS;

CELLULAR ACTIVITIES; CHEMICAL DESCRIPTORS; HIGH-THROUGHPUT SCREENING; LINEAR COMBINATIONS; MEDIUM-THROUGHPUT SCREENING; PARTIAL LEAST SQUARES MODELS; PREDICTIVE MODELING; SYNTHETIC ACTIVITIES;

ENZYMES;

DRUG; ENZYME INHIBITOR; LIGAND; PROTEIN KINASE;

ARTICLE; BAYES THEOREM; BINDING SITE; CELL LINE; CELL PROLIFERATION; CHEMISTRY; COMPUTER INTERFACE; DRUG DEVELOPMENT; DRUG EFFECT; HIGH THROUGHPUT SCREENING; HUMAN; KINETICS; LABORATORY AUTOMATION; METABOLISM; METHODOLOGY; PROTEIN BINDING; PROTEIN DATABASE; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REGRESSION ANALYSIS; SENSITIVITY AND SPECIFICITY;

AUTOMATION, LABORATORY; BAYES THEOREM; BINDING SITES; CELL LINE; CELL PROLIFERATION; CHEMISTRY, PHARMACEUTICAL; DATABASES, PROTEIN; DRUG DISCOVERY; ENZYME INHIBITORS; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; KINETICS; LEAST-SQUARES ANALYSIS; LIGANDS; PHARMACEUTICAL PREPARATIONS; PROTEIN BINDING; PROTEIN KINASES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SENSITIVITY AND SPECIFICITY; USER-COMPUTER INTERFACE;

EID: 80052015102     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci1005004     Document Type: Article

References (48)

1. Bleicher, K. H.; Boehm, H. J.; Mueller, K.; Alanine, A. I. A guide to drug discovery: Hit and lead generation: Beyond high-throughput screening Nat. Rev. Drug Discovery 2003, 2, 369-378 (Pubitemid 37361707)
2. Harris, C. J.; Stevens, A. P. Chemogenomics: Structuring the drug discovery process to gene families Drug Discov Today 2006, 11, 880-888 (Pubitemid 44403186)
3. Martin, E. J.; Sullivan, D. C. Surrogate AutoShim: Predocking into a universal ensemble kinase receptor for three dimensional activity prediction, very quickly, without a crystal structure J. Chem. Inf. Model. 2008, 48, 873-881 (Pubitemid 351757752)
4. Cavasotto, C. N.; Orry, A. J. W. Ligand docking and structure-based virtual screening in drug discovery Curr. Top. Med. Chem. (Sharjah, United Arab Emirates) 2007, 7, 1006-1014 (Pubitemid 47040528)
5. Guido, R. V. C.; Oliva, G.; Andricopulo, A. D. Virtual screening and its integration with modern drug design technologies Curr. Med. Chem. 2008, 15, 37-46 (Pubitemid 351234626)
6. Green, D. V. S. Virtual screening of chemical libraries for drug discovery Expert Opin. Drug Discovery 2008, 3, 1011-1026
7. Kubinyi, H. Success Stories of Computer-Aided Design. In Computer Applications in Pharmaceutical Research and Development; Ekins, S., Ed.; WileySeries in Drug Discovery and Development; Wiley-Interscience: Hoboken, NJ, 2006; pp 377-424.
8. Doman, T. N.; McGovern, S. L.; Witherbee, B. J.; Kasten, T. P.; Kurumbail, R.; Stallings, W. C.; Connolly, D. T.; Shoichet, B. K. Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B J. Med. Chem. 2002, 45, 2213-2221 (Pubitemid 34525801)
9. Paiva, A. M.; Vanderwall, D. E.; Blanchard, J. S.; Kozarich, J. W.; Williamson, J. M.; Kelly, T. M. Inhibitors of dihydrodipicolinate reductase, a key enzyme of the diaminopimelate pathway of Mycobacterium tuberculosis Biochim. Biophys. Acta, Protein Struct. Mol. Enzymol. 2001, 1545, 67-77 (Pubitemid 32124808)
10. Birault, V.; Harris, C. J.; Le, J.; Lipkin, M.; Nerella, R.; Stevens, A. Bringing kinases into focus: Efficient drug design through the use of chemogenomic toolkits Curr. Med. Chem. 2006, 13, 1735-1748 (Pubitemid 43871752)
11. Oshiro, C.; Bradley, E. K.; Eksterowicz, J.; Evensen, E.; Lamb, M. L.; Lanctot, J. K.; Putta, S.; Stanton, R.; Grootenhuis, P. D. J. Performance of 3D-database molecular docking studies into homology models J. Med. Chem. 2004, 47, 764-767 (Pubitemid 38129734)
12. Manallack, D. T.; Pitt, W. R.; Gancia, E.; Montana, J. G.; Livingstone, D. J.; Ford, M. G.; Whitley, D. C. Selecting screening candidates for kinase and G protein-coupled receptor targets using neural networks J. Chem. Inf. Comput. Sci. 2002, 42, 1256-1262 (Pubitemid 35360310)
13. Xia, X.; Maliski, E. G.; Gallant, P.; Rogers, D. Classification of kinase inhibitors using a bayesian model J. Med. Chem. 2004, 47, 4463-4470 (Pubitemid 39096834)
14. 50 training data J. Chem. Inf. Model. 2008, 48, 861-872 (Pubitemid 351757751)
15. Caron, P. R.; Mullican, M. D.; Mashal, R. D.; Wilson, K. P.; Su, M. S.; Murcko, M. A. Chemogenomic approaches to drug discovery Curr. Opin. Chem. Biol. 2001, 5, 464-470
16. Bredel, M.; Jacoby, E. Chemogenomics: An emerging strategy for rapid target and drug discovery Nat. Rev. Genet. 2004, 5, 262-275 (Pubitemid 38435622)
17. Bajorath, J. Computational approaches in chemogenomics and chemical biology: Current and future impact on drug discovery Expert Opin. Drug Discovery 2008, 3, 1371-1376
18. ter Haar, E.; Walters, W. P.; Pazhanisamy, S.; Taslimi, P.; Pierce, A. C.; Bemis, G. W.; Salituro, F. G.; Harbeson, S. L. Kinase chemogenomics: Targeting the human kinome for target validation and drug discovery Mini-Rev. Med. Chem. 2004, 4, 235-253 (Pubitemid 38854869)
19. Sutherland, J. J.; Higgs, R. E.; Watson, I.; Vieth, M. Chemical fragments as foundations for understanding target space and activity prediction J. Med. Chem. 2008, 51, 2689-2700 (Pubitemid 351620791)
20. Vieth, M.; Higgs, R. E.; Robertson, D. H.; Shapiro, M.; Gragg, E. A.; Hemmerle, H. Kinomics-structural biology and chemogenomics of kinase inhibitors and targets Biochim. Biophys. Acta, Proteins Proteomics 2004, 1697, 243-257 (Pubitemid 38326776)
21. Vieth, M.; Sutherland, J. J.; Robertson, D. H.; Campbell, R. M. Kinomics: Characterizing the therapeutically validated kinase space Drug Discov Today 2005, 10, 839-846 (Pubitemid 40824738)
22. Vieth, M.; Erickson, J.; Wang, J.; Webster, Y.; Mader, M.; Higgs, R.; Watson, I. Kinase inhibitor data modeling and de novo inhibitor design with fragment approaches J. Med. Chem. 2009, 52, 6456-6466
23. Muegge, I.; Enyedy, I. J. Virtual screening for kinase targets Curr. Med. Chem. 2004, 11, 693-707 (Pubitemid 38380044)
24. 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
25. Aronov, A. M.; McClain, B.; Stuver Moody, C.; Murcko, M. A. Kinase-likeness and kinase-privileged fragments: Toward virtual polypharmacology J. Med. Chem. 2008, 51, 1214-1222 (Pubitemid 351480383)
26. Fernandez, A.; Maddipati, S. A priori inference of cross reactivity for drug-targeted kinases J. Med. Chem. 2006, 49, 3092-3100 (Pubitemid 43830509)
27. 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
28. Bajorath, J. Affinity fingerprints: Leading the way? Drug Discov Today 2002, 7, 1035
29. Dixon, S. L.; Villar, H. O. Bioactive diversity and screening library selection via affinity fingerprinting J. Chem. Inf. Comput. Sci. 1998, 38, 1192-1203 (Pubitemid 128591285)
30. Beroza, P.; Damodaran, K.; Lum, R. T. Target-related affinity profiling: Telik's lead discovery technology Curr. Top. Med. Chem. (Sharjah, United Arab Emirates) 2005, 5, 371-381 (Pubitemid 40753874)
31. Kauvar, L. M.; Higgins, D. L.; Villar, H. O.; Sportsman, J. R.; Engqvist-Goldstein, A.; Bukar, R.; Bauer, K. E.; Dilley, H.; Rocke, D. M. Predicting ligand binding to proteins by affinity fingerprinting Chem. Biol. 1995, 2, 107-118
32. Bender, A.; Jenkins, J. L.; Glick, M.; Deng, Z.; Nettles, J. H.; Davies, J. W. "Bayes Affinity Fingerprints" Improve retrieval rates in virtual screening and define orthogonal bioactivity space: When are multitarget drugs a feasible concept? J. Chem. Inf. Model. 2006, 46, 2445-2456 (Pubitemid 46008117)
33. Lessel, U. F.; Briem, H. Flexsim-X: A method for the detection of molecules with similar biological activity J. Chem. Inf. Comput. Sci. 2000, 40, 246-253
34. Warren, G. L.; Andrews, C. W.; Capelli, A. M.; Clarke, B.; LaLonde, J.; Lambert, M. H.; Lindvall, M.; Nevins, N.; Semus, S. F.; Senger, S.; Tedesco, G.; Wall, I. D.; Woolven, J. M.; Peishoff, C. E.; Head, M. S. A Critical assessment of docking programs and scoring functions J. Med. Chem. 2006, 49, 5912-5931 (Pubitemid 44484938)
35. Manning, G.; Whyte, D. B.; Martinez, R.; Hunter, T.; Sudarsanam, S. The protein kinase complement of the human genome Science 2002, 298, 1912-1916
36. Naive Bayes classifier. http://en.wikipedia.org/wiki/Naive-Bayes- classifier (accessed March 1, 2011).
37. The R Project for Statistical Computing. www.r-project.org (accessed March 1, 2011.
38. Shokat, K. M. Tyrosine kinases: Modular signaling enzymes with tunable specificities Chem. Biol. 1995, 2, 509-514
39. Pipeline Pilot 8.0 Data Modeling User Guide; Accelrys, Inc.: San Diego, CA, 2011.
40. Agarwal, A.; Pearson, P. P.; Taylor, E. W.; Li, H. B.; Dahlgren, T.; Herslof, M.; Yang, Y.; Lambert, G.; Nelson, D. L. Three-dimensional quantitative structure-activity relationships of 5-HT receptor binding data for tetrahydropyridinylindole derivatives: A comparison of the Hansch and CoMFA methods J. Med. Chem. 1993, 36, 4006-4014 (Pubitemid 24024672)
41. Thomas, B. F.; Compton, D. R.; Martin, B. R.; Semus, S. F. Modeling the cannabinoid receptor: A three-dimensional quantitative structure-activity analysis Mol. Pharmacol. 1991, 40, 656-665
42. Goodwin, J. T.; Conradi, R. A.; Ho, N. F. H.; Burton, P. S. Physicochemical determinants of passive membrane permeability: Role of solute hydrogen-bonding potential and volume J. Med. Chem. 2001, 44, 3721-3729 (Pubitemid 33026680)
43. Murphy, E. A.; Shields, D. J.; Stoletov, K.; Dneprovskaia, E.; McElroy, M.; Greenberg, J., I; Lindquist, J.; Acevedo, L. M.; Anand, S.; Majeti, B. K.; Tsigelny, I.; Saldanha, A.; Walsh, B.; Hoffman, R. M.; Bouvet, M.; Klemke, R. L.; Vogt, P. K.; Arnold, L.; Wrasidlo, W.; Cheresh, D. A. Disruption of angiogenesis and tumor growth with an orally active drug that stabilizes the inactive state of PDGFRbeta/B-RAF Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 4299-4304
44. Nazarian, R.; Shi, H.; Wang, Q.; Kong, X.; Koya, R. C.; Lee, H.; Chen, Z.; Lee, M. K.; Attar, N.; Sazegar, H.; Chodon, T.; Nelson, S. F.; McArthur, G.; Sosman, J. A.; Ribas, A.; Lo, R. S. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation Nature (London, U. K.) 2010, 468, 973-977
45. Solit, D. B.; Rosen, N. Resistance to BRAF inhibition in melanomas N. Engl. J. Med. 2011, 364, 772-774
46. Nicholls, A. Information Theory and QSAR. 18th European Symposium on Quantitative Structure Activity Relationships, Rhodes, Greece, September 19-24, 2010.
47. Mestres, J.; Gregori-Puigjane, E. Conciliating binding efficiency and polypharmacology Trends Pharmacol. Sci. 2009, 30, 470-474
48. Keiser, M. J.; Roth, B. L.; Armbruster, B. N.; Ernsberger, P.; Irwin, J. J.; Shoichet, B. K. Relating protein pharmacology by ligand chemistry Nat. Biotechnol. 2007, 25, 197-206 (Pubitemid 46227119)