BRUTUS: Optimization of a grid-based similarity function for rigid-body molecular superposition. 1. Alignment and virtual screening applications

Journal of Medicinal Chemistry

Volumn 48, Issue 12, 2005, Pages 4076-4086

  Tervo, Anu J ^a,b   Rönkkö, Toni ^a   Nyrönen, Tommi H ^b   Poso, Antti ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

^b IT Center for Science   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIVIRUS AGENT; COAT PROTEIN; ELASTASE INHIBITOR; METALLOPROTEINASE INHIBITOR; NEUTROPHIL COLLAGENASE; NEUTROPHIL COLLAGENASE INHIBITOR; PROTEIN INHIBITOR; PROTEINASE INHIBITOR; THERMOLYSIN; THERMOLYSIN INHIBITOR; UNCLASSIFIED DRUG;

ALGORITHM; ARTICLE; BIOLOGICAL ACTIVITY; CHEMICAL STRUCTURE; COMPUTER PROGRAM; COMPUTER SIMULATION; DATA BASE; DRUG STRUCTURE; ELECTRICITY; MOLECULAR MODEL; SCREENING;

ALGORITHMS; COMPUTER SIMULATION; CYCLOOXYGENASE 2; CYCLOOXYGENASE 2 INHIBITORS; CYCLOOXYGENASE INHIBITORS; DATABASES, FACTUAL; DRUG DESIGN; ENZYME INHIBITORS; HIV-1 REVERSE TRANSCRIPTASE; MATRIX METALLOPROTEINASE 8; MODELS, MOLECULAR; MOLECULAR STRUCTURE; PANCREATIC ELASTASE; PROSTAGLANDIN-ENDOPEROXIDE SYNTHASES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; REVERSE TRANSCRIPTASE INHIBITORS; RHINOVIRUS; THERMOLYSIN;

EID: 20444385067     PISSN: 00222623     EISSN: None     Source Type: Journal    
DOI: 10.1021/jm049123a     Document Type: Article

References (75)

1. Böhm, H.-J.; Schneider, G. Virtual Screening for Bioactive Molecules. In Methods and Principles in Medicinal Chemistry; Mannhold, R., Kubinyi, H., Timmerman, H., Eds.; WILEY-VHC Verlag GmbH: Weinheim, Germany, 2000; p 307.
2. Miller, M. A. Chemical database techniques in drug discovery. Nat. Rev. Drug, Discovery 2002, 1, 220-227.
3. Krämer, O.; Hazemann, I.; Podjarny, A. D.; Klebe, G. Virtual screening for inhibitors of human aldose reductase. Proteins 2004, 55, 814-823.
4. Lyne, P. D.; Kenny, P. W.; Cosgrove, D. A.; Deng, C.; Zabludoff, S.; et al. Identification of compounds with nanomolar binding affinity for checkpoint kinase-1 using knowledge-based virtual screening. J. Med. Chem. 2004, 47, 1962-1968.
5. Peukert, S.; Brendel, J.; Pirard, B.; Strubing, C.; Kleemann, H. W.; et al. Pharmacophore-based search, synthesis, and biological evaluation of anthranilic amides as novel blockers of the Kv1.5 channel. Bioorg. Med. Chem. Lett. 2004, 14, 2823-2827.
6. Peng, H.; Huang, N.; Qi, J.; Xie, P.; Xu, C.; et al. Identification of novel inhibitors of BCR-ABL tyrosine kinase via virtual screening. Bioorg. Med. Chem. Lett. 2003, 13, 3693-3699.
7. Singh, J.; Chuaqui, C. E.; Boriack-Sjodin, P. A.; Lee, W. C.; Pontz, T.; et al. Successful shape-based virtual screening: the discovery of a potent inhibitor of the type I TGFbeta receptor kinase (TbetaRI). Bioorg. Med. Chem. Lett. 2003, 13, 4355-4359.
8. Vangrevelinghe, E.; Zimmermann, K.; Schöpfer, J.; Portmann, R.; Fabbro, D.; et al. Discovery of a potent and selective protein kinase CK2 inhibitor by high-throughput docking. J. Med. Chem. 2003, 46, 2656-2662.
9. Grüneberg, S.; Stubbs, M. T.; Klebe, G. Successful virtual screening for novel inhibitors of human carbonic anhydrase: strategy and experimental confirmation. J. Med. Chem. 2002, 45, 3588-3602.
10. Perola, E.; Xu, K.; Kollmeyer, T. M.; Kaufmann, S. H.; Prendergast, F. G.; et al. Successful virtual screening of a chemical database for farnesyltransferase inhibitor leads. J. Med. Chem. 2000, 43, 401-408.
11. Tervo, A. J.; Kyrylenko, S.; Niskanen, P.; Salminen, A.; Leppänen, J.; et al. An In Silica Approach to Discovering Novel Inhibitors of Human Sirtuin Type 2. J. Med. Chem. 2004, 47, 6292-6298.
12. Rönkkö, T.; Tervo, A. J.; Poso, A. BRUTUS: Optimization of a Grid-Based Similarity Function for Rigid-Body Molecular Superposition. II. Description and Characterization., submitted for publication, 2005.
13. Lemmen, C.; Lengauer, T. Computational methods for the structural alignment of molecules. J. Comput.-Aided Mol. Des. 2000, 14, 215-232.
14. Hofbauer, C.; Lohninger, H.; Aszodi, A. SURFCOMP: a novel graph-based approach to molecular surface comparison. J. Chem. Inf. Comput. Sci. 2004, 44, 837-847.
15. Korhonen, S. P.; Tuppurainen, K.; Laatikainen, R.; Peräkylä, M. FLUFF-BALL, a template-based grid-independent superposition and QSAR technique: validation using a benchmark steroid data set. J. Chem. Inf. Comput. Sci. 2003, 43, 1780-1793.
16. Parretti, M. F.; Krömer, R. T.; Rothman, J. H.; Richards, W. G. Alignment of Molecules by the Monte Carlo Optimization of Molecular Similarity Indices. J. Comput. Chem. 1997, 18, 1344-1353.
17. Mestres, J.; Rohrer, D. C.; Maggiora, G. M. MIMIC: A Molecular-Field Matching Program. Exploiting Applicability of Molecular Similarity Approaches. J. Comput. Chem. 1997, 18, 934-954.
18. Kearsley, S. K.; Smith, G. M. An Alternative Method for the Alignment of Molecular Structures: Maximizing Electrostatic and Steric Overlap. Tetrahedron Comput. Methodol. 1990, 3, 615-633.
19. Apaya, R. P.; Lucchese, B.; Price, S. L.; Vinter, J. G. The matching of electrostatic extrema: a useful method in drug design? A study of phosphodiesterase III inhibitors. J. Comput. Aided Mol. Des. 1995, 9, 33-43.
20. Manaut, F.; Sanz, F.; Jose, J.; Milesi, M. Automatic search for maximum similarity between molecular electrostatic potential distributions. J. Comput.-Aided Mol. Des. 1991, 5, 371-380.
21. Burt, C.; Richards, W. G.; Huxley, P. The Application of Molecular Similarity Calculations. J. Comput. Chem. 1990, 11, 1139-1146.
22. Klebe, G. Structural Alignment of Molecules. 3D QSAR In Drug Design: Theory, Methods and Applications; ESCOM: Leiden, The Netherlands. 1993; pp 173-199.
23. Gillet, V. J.; Wild, D. J.; Willett, P.; Bradshaw, J. Similarity and Dissimilarity Methods for Processing Chemical Structure Databases. Comput. J. 1998, 41, 547-558.
24. Willett, P. Chemical Similarity Searching. J. Chem. Inf. Comput. Sci. 1998, 38, 983-996.
25. Lengauer, T.; Lemmen, C.; Rarey, M.; Zimmermann, M. Novel technologies for virtual screening. Drug Discovery Today 2004, 9, 27-34.
26. Krämer, A.; Horn, H. W.; Rice, J. E. Fast 3D molecular superposition and similarity search in databases of flexible molecules. J. Comput.-Aided Mol. Des. 2003, 17, 13-38.
27. Miller, M. D.; Sheridan, R. P.; Kearsley, S. K. SQ: a program for rapidly producing pharmacophorically relevent molecular superpositions. J. Med. Chem. 1999, 42, 1505-1514.
28. Lemmen, C.; Lengauer, T.; Klebe, G. FlexS: a method for fast flexible ligand superposition. J. Med. Chem. 1998, 41, 4502-4520.
29. Zauhar, R. J.; Moyna, G.; Tian, L.; Li, Z.; Welsh, W. J. Shape Signatures: A New Approach to Computer-Aided Ligand- and Receptor-Based Drug Design. J. Med. Chem. 2003, 46, 5674-5690.
30. Goldman, B. B.; Wipke, W. T. Quadratic shape descriptors. 1. Rapid superposition of dissimilar molecules using geometrically invariant surface descriptors. J. Chem. Inf. Comput. Sci. 2000, 40, 644-658.
31. Hahn, M. Three-Dimensional Shape-Based Searching of Conformationally Flexible Compounds. J. Chem. Inf. Comput. Sci. 1997, 37, 80-86.
32. Grant, J. A.; Gallardo, M. A.; Pickup, B. T. A Fast Method of Molecular Shape Comparison: A Simple Application of a Gaussian Description of Molecular Shape. J. Comput. Chem. 1996, 17, 1653-1666.
33. Jain, A. N.; Dietterich, T. G.; Lathrop, R. H.; Chapman, D.; Critchlow, R. E., Jr.; et al. Compass. A shape-based machine learning tool for drug design. J. Comput.-Aided Mol. Des. 1994, 8, 635-652.
34. Kohonen, T. Self-Organizing Maps; Springer: Berlin, Germany, 1995.
35. Wild, D. J.; Willett, P. Similarity Searching in Files of Three-Dimensional Chemical Structures. Alignment of Molecular Electrostatic Potential Fields with a Genetic Algorithm. J. Chem. Inf. Comput. Sci. 1996, 36, 159-167.
36. Thorner, D. A.; Wild, D. J.; Willett, P.; Wright, P. M. Similarity Searching in Files of Three-Dimensional Chemical Structures: Flexible Field-Based Searching of Molecular Electrostatic Potentials. J. Chem. Inf. Comput. Sci. 1996, 36, 900-908.
37. Pitman, M. C.; Huber, W. K.; Horn, H.; Kramer, A.; Rice, J. E.; et al. FLASHFLOOD: a 3D field-based similarity search and alignment method for flexible molecules. J. Comput.-Aided Mol. Des. 2001, 15, 587-612.
38. Thorner, D. A.; Willett, P.; Wright, P. M.; Taylor, R. Similarity searching in files of three-dimensional chemical structures: representation and searching of molecular electrostatic potentials using field-graphs. J. Comput.-Aided Mol. Des. 1997, 11, 163-174.
39. Perry, N. C.; van Geerestein, V. J. Database Searching on the Basis of Three-Dimensional Molecular Similarity Using the SPERM Program. J. Chem. Inf. Comput. Sci. 1992, 32, 607-616.
40. Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; et al. The Protein Data Bank. Nucleic Acid Res. 2000, 28, 235-242.
41. Sybyl, versions 6.8-7.0; Tripos Inc.: St. Louis, MO.
42. Böhm, H. J.; Klebe, G. What Can We Learn from Molecular Recognition in Protein-Ligand Complexes for the Design of New Drugs? Angew. Chem., Int. Ed. Engl. 1996, 35, 2588-2614.
43. Cosgrove, D. A.; Bayada, D. M.; Johnson, A. P. A novel method of aligning molecules by local surface shape similarity. J. Comput.-Aided Mol. Des. 2000, 14, 573-591.
44. Kubinyi, H.; Hamprecht, F. A.; Mietzner, T. Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrixes. J. Med. Chem. 1998, 41, 2553-2564.
45. Cramer, R. D., III; Patterson, D. E.; Bunce, J. D. Comparative Molecular Field Analysis (CoMFA). 1. Effect of Shape on Binding of Steroids to Carrier Proteins. J. Am. Chem. Soc. 1988, 110, 5959-5967.
46. Mattos, C.; Rasmussen, B.; Ding, X.; Petsko, G. A.; Ringe, D. Analogous inhibitors of elastase do not always bind analogously. Nat. Struct. Biol. 1994, 1, 55-58.
47. Maybridge Chemicals Database; Maybridge Chemicals Company Ltd.: Cornwall , U.K.
48. Jadhav, P. K.; Ala, P.; Woerner, F. J.; Chang, C. H.; Garber, S. S.; et al. Cyclic urea amides: HIV-1 protease inhibitors with low nanomolar potency against both wild type and protease inhibitor resistant mutants of HIV. J. Med. Chem. 1997, 40, 181-191.
49. Ringhofer, S.; Kallen, J.; Dutzler, R.; Billich, A.; Visser, A. J.; et al. X-ray structure and conformational dynamics of the HIV-1 protease in complex with the inhibitor SDZ283-910: agreement of time-resolved spectroscopy and molecular dynamics simulations. J. Mol. Biol. 1999, 286, 1147-1159.
50. Kurumbail, R. G.; Stevens, A. M.; Gierse, J. K.; McDonald, J. J.; Stegeman, R. A.; et al. Structural basis for selective inhibition of cyclooxygenase-2 by anti-inflammatory agents. Nature 1996, 384, 644-648.
51. Good, A. C.; Cheney, D. L. Analysis and optimization of structure-based virtual screening protocols (1): exploration of ligand conformational sampling techniques. J. Mol. Graphics Modell. 2003, 22, 23-30.
52. Pearlman, R. S.; Balducci, R. Confort: A Novel Algorithm For Conformational Analysis. National Meeting of the American Chemical Society, New Orleans, LA, 1998.
53. Clark, R. D.; Fox, P. C.; Abrahamian, E. Characterization of Pharmacophore Multiplet Fingerprints as Molecular Descriptors. 3rd Joint Sheffield Conference on Chemoinformatics, Sheffield, U.K., April 21-23, 2004; pp 21-23.
54. Hodgkin, E. E.; Richards, W. G. Molecular Similarity Based on Electrostatic Potential and Electric Field. Int. J. Quantum Chem., Quantum Biol. Symp. 1987, 14, 105-110.
55. Visual Data 3.1.9; Visipoint Oy: Kuopio, Finland.
56. Koikkalainen, P. Progress with the three-structured self-organizing map. Proceedings of the 11th European Conference on Artificial Intelligence (ECAI'94); Cohn, A., Ed.; Wiley & Sons: New York, 1994; pp 211-215.
57. Kolehmainen, M. T. Data exploration with self-organizing maps in environmental informatics and bioinformatics. Ph.D. Thesis, University of Kuopio, Kuopio, Finland, 2004.
58. Clark, R. D. Relative and absolute diversity analysis of combinatorial libraries. In Combinatorial Library Design and Evaluation; Ghose, A. K., Viswanadhan, V. N., Eds.; Marcel Dekker: New York, 2001; pp 337-362.
59. Willett, P. Similarity-based approaches to virtual screening. Biochem. Soc. Trans. 2003, 31, 603-606.
60. Raymond, J. W.; Willett, P. Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases. J. Comput.-Aided Mol. Des. 2002, 16, 59-71.
61. Schuffenhauer, A.; Gillet, V. J.; Willett, P. Similarity searching in files of three-dimensional chemical structures: analysis of the BIOSTER database using two-dimensional fingerprints and molecular field descriptors. J. Chem. Inf. Comput. Sci. 2000, 40, 295-307.
62. Flower, D. R. On the Properties of Bit String-Based Measures of Chemical Similarity. J. Chem. Inf. Comput. Sci. 1998, 38, 379-386.
63. Johnson, M. S.; Lehtonen, J. V. Comparison of protein three-dimensional structures. Bioinformatics: Sequence, Structure and Databanks; Oxford University Press: 2000; pp 15-50.
64. Lehtonen, J. V.; Rantanen, V.-V.; Still, D.-J.; Ekholm, J.; Björklund, D.; et al. BODIL: a molecular modeling environment for structure-function analysis and drug discovery. J. Comput.-Aided Mol. Des. 2004, 18, 401-419.
65. Clark, M.; Cramer, R. D., III; Van Opdenbosch, N. Validation of the General Purpose Tripos 5.2 Force Field. J. Comput. Chem. 1989, 10, 982-1012.
66. Khanna, I. K.; Weier, R. M.; Yu, Y.; Collins, P. W.; Miyashiro, J. M.; et al. 1,2-Diarylpyrroles as potent and selective inhibitors of cyclooxygenase-2. J. Med. Chem. 1997, 40, 1619-1633.
67. Khanna, I. K.; Weier, R. M.; Yu, Y.; Xu, X. D.; Koszyk, F. J.; et al. 1,2-Diarylimidazoles as potent, cyclooxygenase-2 selective, and orally active antiinflammatory agents. J. Med. Chem. 1997, 40, 1634-1647.
68. Khanna, I. K.; Yu, Y.; Huff, R. M.; Weier, R. M.; Xu, X.; et al. Selective cyclooxygenase-2 inhibitors: heteroaryl modified 1,2-diarylimidazoles are potent, orally active antiinflammatory agents. J. Med. Chem. 2000, 43, 3168-3185.
69. Alterman, M.; Björsne, M.; Mühlman, A.; Classon, B.; Kvarnström, I.; et al. Design and synthesis of new potent C2-symmetric HIV-1 protease inhibitors. Use of L-mannaric acid as a peptidomimetic scaffold. J. Med. Chem. 1998, 41, 3782-3792.
70. Krömer, R. T.; Ettmayer, P.; Hecht, P. 3D-quantitative structure-activity relationships of human immunodeficiency virus type-1 proteinase inhibitors: comparative molecular field analysis of 2-heterosubstituted statine derivatives-implications for the design of novel inhibitors. J. Med. Chem. 1995, 38, 4917-4928.
71. Scholz, D.; Billich, A.; Charpiot, B.; Ettmayer, P.; Lehr, P.; et al. Inhibitors of HIV-1 proteinase containing 2-heterosubstituted 4-amino-3-hydroxy-5-phenylpentanoic acid: synthesis, enzyme inhibition, and antiviral activity. J. Med. Chem. 1994, 37, 3079-3089.
72. Alterman, M.; Andersson, H. O.; Garg, N.; Ahlsén, G.; Lövgren, S.; et al. Design and fast synthesis of C-terminal duplicated potent C(2)-symmetric P1/P1′-modified HIV-1 protease inhibitors. J. Med. Chem. 1999, 42, 3835-3844.
73. Tervo, A. J.; Nyronen, T. H.; Rönkkö, T.; Poso, A. Comparing The Quality and Predictiveness Between 3D QSAR Models Obtained from Manual and Automated Alignment. J. Chem. Inf. Comput. Sci. 2004, 44, 807-816.
74. Lin, T. H.; Wang, G. M.; Hsu, Y. H. Classification of some active HIV-1 protease inhibitors and their inactive analogues using some uncorrelated three-dimensional molecular descriptors and a fuzzy c-means algorithm. J. Chem. Inf. Comput. Sci. 2002, 42, 1490-1504.
75. Pearlman, R. S. Rapid Generation of High Quality Approximate 3-Dimension Molecular Structures. Chem. Des. Ant. News 1987, 2, 1/5-6.