Structure-Based Chemogenomics: Analysis of Protein Family Landscapes

Methods in Molecular Biology

Volumn 575, Issue , 2009, Pages 281-296

  Pirard, Bernard ^a  

^a NONE

Author keywords

Binding site mapping; Classification of protein structures; Database mining; GRID CPCA; Hit finding; Pharmacophore; Structural biology

Indexed keywords

LIGAND; PROTEIN; PROTEIN KINASE; PROTEIN KINASE INHIBITOR;

CHEMISTRY; DRUG DEVELOPMENT; GENETICS; GENOMICS; METHODOLOGY; MOLECULAR BIOLOGY; PROTEIN DATABASE; REVIEW; SEQUENCE ALIGNMENT; STATISTICS;

DATABASES, PROTEIN; DRUG DISCOVERY; GENOMICS; LIGANDS; MOLECULAR BIOLOGY; PROTEIN KINASE INHIBITORS; PROTEIN KINASES; PROTEINS; SEQUENCE ALIGNMENT;

MLCS; MLOWN;

EID: 75549090596     PISSN: 10643745     EISSN: 19406029     Source Type: Book Series    
DOI: 10.1007/978-1-60761-274-2_12     Document Type: Chapter

References (65)

1. Caron, P. R., Mullican, M. D., Mashal, R. D., Wilson, K. P., Su, M. S., and Murcko, M. A. (2001) Chemogenomic approaches to drug discovery. Curr. Opin. Chem. Biol. 5, 464–470.
2. Bleicher, K. H. (2002) Chemogenomics: bridging a drug discovery gap. Curr. Med. Chem. 9, 2077–2084.
3. Bredel, M. and Jacoby, E. (2004) Chemogenomics: an emerging strategy for rapid target and drug discovery. Nat. Rev. Genet. 5, 262–275.
4. Shuttleworth, S. J., Connors, R. V., Fu, J., Liu, J., Lizarzaburu, M. E., Qiu, W., Sharma, R., Wanska, M., Malgorzata, Z., and Alex, J. (2005) Design and synthesis of protein superfamily-targeted chemical libraries for lead identification and optimization. Curr. Med. Chem. 12, 1239–1281.
5. Klabunde, T. (2007) Chemogenomic approaches to drug discovery: similar receptors bind similar ligands. Br. J. Pharmacol. 152, 5–7.
6. Rognan, D. (2007) Chemogenomic approaches to rational drug design. Br. J. Pharmacol. 152, 38–52.
7. Bergner, A. and Günther, J. (2004) Structural aspects of binding site similarity: a 3D upgrade for chemogenomics. Methods Principles Med. Chem. 22, 97–135.
8. Berman, H. M., Westbrook, J., Feng, Z., Gililand, G., Bhat, T. N., Weissig, H., Shindy-aloy, I. N., and Bourne, P. E. (2000) The protein data bank. Nucleic Acids Res. 28, 235–242.
9. Hendlich, M., Bergner, A., Günther, J., and Klebe, G. (2003) Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions. J. Mol. Biol. 326, 607–620.
10. Chalk, A. J., Worth, C. L., Overington, J. P., and Chan, A. W. (2004) PDBLIG: classification of small molecular protein binding in the protein data bank. J. Med. Chem. 47, 3807–3816.
11. Wang, R., Fang, X., Lu, Y., Yang, C. Y., and Wang, S. (2005) The PDBbind database: methodologies and updates. J. Med. Chem. 48, 4111–4119.
12. Wang, R., Fang, X., Lu, Y., and Wang, S. (2004) The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. J. Med. Chem. 47, 2977–2980.
13. Kellenberger, E., Muller, P., Schalon, C., Bret, G., Foata, N., and Rognan, D. (2006) sc-PDB: an annotated database of drugga-ble binding sites from the protein databank. J. Chem. Inf. Model. 46, 717–727.
14. Gold, N. D. and Jackson, R. M. (2006) A searchable database for comparing protein-ligand binding sites for the analysis of struc-ture-function relationships. J. Chem. Inf. Model. 46, 736–742.
15. Günther, J., Bergner, A., Hendlich, M., and Klebe, G. (2003) Utilising structural knowledge in drug design strategies: applications using Relibase. J. Mol. Biol. 326, 621–636.
16. Nicolotti, O., Miscioscia, T. F., Leo-netti, F., Muncipinto, G., and Carotti, A. (2007) Screening of matrix metalloproteinases available from the protein data bank: insights into biological functions, domain organization, and zinc binding groups. J. Chem. Inf. Model. 46, 2439–2448.
17. Jacobs, M. D., Caron, P. R., and Hare, B. J. (2008) Classifying protein kinase structures guides use of ligand-selectivity profiles to predict inactive conformations: structure of lck/imatinib complex. Proteins 70, 1451–1460.
18. Wolber, G., Seidel, T., Bendix, F., and Langer, T. (2008) Molecule-pharmacoph-ore superpositioning and pattern matching in computational drug design. Drug Discov. Today 13, 23–29.
19. Wolber, G. and Langer, T. (2005) Ligand-Scout: 3D-pharmacophores derived from protein bound ligands and their use as virtual screening filters. J. Chem. Inf. Model. 45, 160–169.
20. Liao, J. J. L. (2007) Molecular recognition of protein kinase binding pockets for designing potent and selective kinase inhibitors. J. Med. Chem. 50, 409–424.
21. Aronov, A. M. and Murcko, M. A. (2004) Toward a pharmacophore for kinase frequent hitters. J. Med. Chem. 47, 5616– 5619.
22. McGregor, M. J. (2007) A pharmacophore map for small molecule protein kinase inhibitors. J. Chem. Inf. Model. 47, 2374– 2382.
23. Martin, E. J. and Sullivan, D. C. (2008) Surrogate AutoShim: predocking into a universal ensemble kinase receptor for three dimensional activity prediction, very quickly without a crystal structure. J. Chem. Inf. Model. 48, 873–881.
24. Martin, E. J. and Sullivan, D. C. (2008) AutoShim: empirically corrected scoring functions for quantitative docking with a crystal structure and IC50 training data. J. Chem. Inf. Model. 48, 861–872.
25. Liu, Y. and Gray, N. S. (2006) Rational design of inhibitors that bind to inactive kinase conformations. Nat. Chem. Biol. 7, 358–364.
26. Okram, B., Nagle, A., Adrian, F. J., Lee, C., Ren, P., Wang, X., Sim, T., Xie, Y., Wang, X., Xia, G., Spraggon, G., Warmuth, M., Liu, Y., and Gray, N. S. (2006) A general strategy for creating “inactive-conformation” abl inhibitors. Chem. Biol. 13, 779–786.
27. Sotriffer, C. and Klebe, G. (2002) Identification and mapping of small-molecule binding sites in proteins: computational tools for structure-based drug design. Far-maco 57, 243–251.
28. Goodford, P. (2006) The basic principles of GRID. Methods Principles Med. Chem. 27, 3–26.
29. Gohlke, H., Hendlich, M., and Klebe, G. (2000) Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol. 295, 337–356.
30. Gohlke, H., Hendlich, M., and Klebe, G. (2000) Predicting binding modes, binding affinities and “hot spots” for protein-ligand complexes using a knowledge-based scoring function. Perspect. Drug Discov. Design 20, 115–144.
31. Cruciani, G. and Goodford, P. J. (1994) A search for specificity in DNA-drug interactions. J. Mol. Graph. 12, 116–129.
32. Pastor, M. and Cruciani, G. (1995) A novel strategy for improving ligand selectivity in receptor-based drug design. J. Med. Chem. 38, 4637–4647.
33. Matter, H. and Schwab, W. (1999) Affinity and selectivity of matrix metalloproteinase inhibitors: a chemometrical study from the perspective of ligands and proteins. J. Med. Chem. 42, 4506–4523.
34. Filipponi, E., Cecchetti, V., Tabarrini, O., Bonelli, D., and Fravolini, A. (2000) Che-mometric rationalization of the structural and physicochemical basis for selective cyclooxy-genase-2 inhibition: toward more specific ligands. J. Comput.Aided Mol. Des. 14, 277–291.
35. Kastenholz, M. A., Pastor, M., Cruciani, G., Haaksma, E. E. J., and Fox, T. (2000) GRID/CPCA: a new computational tool to design selective ligands. J. Med. Chem. 43, 3033–3044.
36. Wold, S., Esbensen, K., and Geladi, P. (1987) Principal component analysis. Chemom. Intell. Lab. Syst. 2, 37–52.
37. Westerhuis, J. A., Kourti, T., and Macgre-gor, J. F. (1998) Analysis of multiblock and hierarchical PCA and PLS models. J. Chemom. 12, 301–321.
38. Baroni, M., Costantino, G., Cruciani, G., Riganelli, D., Valigi, R., and Clementi, S. (1993) Generating optimal linear PLS estimations (GOLPE): an advanced chem-ometric tool for handling 3D-QSAR problems. Quant. Struct.-Act. Relat. 12, 9–20.
39. Ridderström, M., Zamora, I., Fjellström, O., and Andersson, T. B. (2001) Analysis of selective regions in the active sites of human cytochromes P450, 2C8, 2C9, 2C18, and 2C19 homology models using GRID/ CPCA. J. Med. Chem. 44, 4072–4081.
40. Naumann, T. and Matter, H. (2002) Structural classification of protein kinases using 3D molecular interaction field analysis of their ligand binding sites: target family landscapes. J. Med. Chem. 45, 2366–2378.
41. Terp, G. E., Cruciani, G., Christensen, I. T., and Jørgensen, F. S. (2002) Structural differences of matrix metalloproteinases with potential implications for inhibitor selectivity examined by the GRID/CPCA approach. J. Med. Chem. 45, 2675–2684.
42. Kurz, M., Brachvogel, V., Matter, H., Stenge-lin, S., Thuring, H., and Kramer, W. (2003) Insights into the bile acid transportation system: the human ileal lipid-binding pro-tein-cholyltaurine complex and its comparison with homologous structures. Proteins 50, 312–328.
43. Myshkin, E. and Wang, B. (2003) Chemometrical classification of ephrin ligands and Eph kinases using GRID/CPCA approach. J. Chem. Inf. Comput. Sci. 43, 1004–1010.
44. Ji, H., Li, H., Flinspach, M., Poulos, T., and Silverman, R. B. (2003) Computer modeling of selective regions in the active site of nitric oxide synthases: implications for the design of iso-form selective inhibitors. J. Med. Chem. 46, 5700–5711.
45. Pirard, B. (2003) Peroxisome proliferator-activated receptors target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis. J. Comput. Aided Mol. Des. 17, 785–796.
46. Matter, H., Kumar, H. S. A., Fedorov, R., Frey, A., Kotsonis, P., Hartmann, E., Froeh-lich, L. G., Reif, A., Pfeiderer, W., Scheu-rer, P., Ghosh, D. K., Schlichting, I., and Schmidt, H. H. (2005) Structural analysis of isoform-specific inhibitors targeting the tetrahydrobiopterin binding site of human nitric oxide synthases. J. Med. Chem. 48, 4783–4792.
47. Vulpetti, A., Crivori, P., Cameron, A., Bertrand, J., Brasca, M. G., D’Alessio, R., and Pevarello, P. (2005) Structure-based approaches to improve selectivity: CDK2-GSK3b binding site analysis. J. Chem. Inf. Model. 45, 1282–1290.
48. Pirard, B. and Matter, H. (2006) Matrix metalloproteinase target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis. J. Med. Chem. 49, 51–69.
49. Fox, T. (2006) Protein selectivity studies using GRID-MIFs. Methods Principles Med. Chem. 27, 45–82.
50. Sheridan, R. P., Holloway, M. K., McGaughey, G., Mosley, R. T., and Singh, S. B. (2002) A simple method for visualizing the differences between related receptor sites. J. Mol. Graph. Model. 21, 217–225.
51. Miller, M. D., Kearsley, S. K., Underwood, D. J., and Sheridan, R. P. (1994) FLOG: a system to select quasi-flexible ligands complementary to a receptor of known three-dimensional structure. J. Comput. Aided Mol. Des. 8, 153–174.
52. Cahart, R. E., Smith, D. H., and Venkatara-ghavan, R. (1985) Atom pairs as molecular features in structure–activity studies: definition and application. J. Chem. Inf. Comput. Sci. 25, 64–73.
53. Sheridan, R. P., Nachbar, R. B., and Bush, B. L. (1994) Extending the trend vector: the trend matrix and sample-based partial-least-squares. J. Comput. Aided Mol. Des. 8, 323–340.
54. Hoppe, C., Steinbeck, C. K., and Wohl-fahrt, G. (2006) Classification and comparison of ligand-binding sites derived from grid-mapped knowledge-based potentials. J. Mol. Graph. Model. 24, 328–340.
55. 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 cleecoxib: new pharmacological opportunities due to related binding site recognition. J. Med. Chem. 47, 550–557.
56. Davis, A. M., Teague, S. J., and Kleywegt, G. (2003) Application and limitations of X-ray crystallographic data in structure-based ligand and drug design. Angew. Chem. Int. Ed. Engl. 42, 2718–2736.
57. Boehm, H. J., and Klebe, G. (1996) What can we learn from molecular recognition in protein-ligand complexes for the design of new drugs? Angew. Chem. Int. Ed. Engl. 35, 2588–2614.
58. Hartshorn, M. J., Verdonk, M. L., Ches-sari, G., Brewerton, S. C., Mooij, W. T. M., Mor tenson, P. N., and Murray, C. W. (2007) Diverse, high-quality test set for the validation of protein-ligand docking performance. J. Med. Chem. 50, 726–741.
59. Pastor, M., Cruciani, G., McLay, I., Pickett, S., and Clementi, S. (2000) Grid-Independ-ent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors. J. Med. Chem. 43, 3233–3243.
60. Baroni, M., Cruciani, G., Sciabola, S., Perruccio, F., and Mason, J. S. (2007) A common reference framework for analyzing/ comparing proteins and ligands. Fingerprints for ligands and proteins (FLAP): theory and application. J. Chem. Inf. Model. 47, 279–294.
61. Schmitt, S., Hendlich, M., and Klebe, G. (2001) From structure to function: a new approach to detect functional similarity among proteins independent from sequence and fold homology. Angew. Chem. Int. Ed. Engl. 40, 3141–3144.
62. Schmitt, S., Kuhn, D., and Klebe, G. (2002) A new method to detect related function among proteins independent of sequence and fold homology. J. Mol. Biol. 323, 387–406.
63. Kuhn, D., Weskamp, N., Schmitt, S., Hüllermeier, E., and Klebe, G. (2006) From the similarity analysis of protein cavities to the functional classification of protein families using cavbase. J. Mol. Biol. 359, 1023– 1044.
64. Kuhn, D., Weskamp, N., Hüllermeier, E., and Klebe, G. (2007) Functional classification of protein kinase binding sites using cavbase. ChemMedChem. 2, 1432–1447.
65. Gerlach, C., Münzel, C., Baum, B., Gerber, H. D., Craan, T., Diederich, W. E., and Klebe, G. (2007) KNOBLE: a knowledge-based approach for the design and synthesis of readily accessible small-molecule chemical probes to test protein binding. Angew. Chem. Int. Ed. Engl. 46, 9105–9109.