Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches

Drug Discovery Today

Volumn 12, Issue 5-6, 2007, Pages 225-233

  Eckert, Hanna ^a   Bajorath, Jürgen ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EFAVIRENZ; NEVIRAPINE; RNA DIRECTED DNA POLYMERASE INHIBITOR;

ALGORITHM; LIGAND BINDING; MATHEMATICAL COMPUTING; MOLECULAR DYNAMICS; REVIEW; STRUCTURE ACTIVITY RELATION;

ALGORITHMS; COMPUTER-AIDED DESIGN; DRUG DELIVERY SYSTEMS; DRUG DESIGN; LIGANDS; MODELS, MOLECULAR; MOLECULAR STRUCTURE; STRUCTURE-ACTIVITY RELATIONSHIP; USER-COMPUTER INTERFACE;

EID: 33847207834     PISSN: 13596446     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.drudis.2007.01.011     Document Type: Review

References (53)

1. Pharm. Des. 7, 567-597
2. Esposito E.X., et al. Methods for applying the quantitative structure-activity relationship paradigm. Methods Mol. Biol. 275 (2004) 131-214
3. In: Johnson M., and Maggiora G.M. (Eds). Concepts and Applications of Molecular Similarity (1990), John Wiley & Sons
4. Kubinyi H. Similarity and dissimilarity - a medicinal chemist's view. Perspect. Drug Discov. Des. 11 (1998) 225-252
5. Maggiora G.M. On outliers and activity cliffs - why QSAR often disappoints. J. Chem. Inf. Model. 46 (2006) 1535
6. Bajorath J. Integration of virtual and high-throughput screening. Nat. Rev. Drug Discov. 1 (2002) 882-894
7. Bender A., and Glen R.C. Molecular similarity: a key technique in molecular informatics. Org. Biomol. Chem. 2 (2004) 3204-3218
8. Boström J., et al. Do structurally similar ligands bind in a similar fashion?. J. Med. Chem. 49 (2006) 6716-6725
9. Sheridan R.P., and Kearsley S.K. Why do we need so many chemical similarity search methods?. Drug Discov. Today 7 (2002) 903-911
10. Shanmugasundaram V., et al. Hit-directed nearest neighbour searching. J. Med. Chem. 48 (2005) 240-248
11. Pearlman R.S., and Smith K.M. Novel software tools for chemical diversity. Perspect. Drug Discov. Des. 9 (1998) 339-353
12. Agrafiotis D.K., et al. Combinatorial informatics in the post-genomics era. Nat. Rev. Drug Discov. 1 (2002) 337-346
13. Warmuth M.K., et al. Active learning with support vector machines in the drug discovery process. J. Chem. Inf. Comput. Sci. 43 (2003) 667-673
14. Jorissen R.N., and Gilson M.K. Virtual screening of molecular databases using a support vector machine. J. Chem. Inf. Model. 45 (2005) 549-561
15. Godden J.W., and Bajorath J. A distance function for retrieval of active molecules from complex chemical space representations. J. Chem. Inf. Model. 46 (2006) 1094-1097
16. Vogt, M. et al. Bayesian interpretation of a distance function for navigating high-dimensional descriptor spaces. J. Chem. Inf. Model. DOI:10.1021/ci600280b (http://pubs.acs.org/journals/jcisd8/index.html)
17. Godden J.W., et al. Molecular similarity analysis and virtual screening in binary-transformed chemical descriptor spaces with variable dimensionality. J. Chem. Inf. Comput. Sci. 44 (2004) 21-29
18. Godden J.W., et al. POT-DMC: a virtual screening method for the identification of potent hits. J. Med. Chem. 47 (2004) 5608-5611
19. Eckert H., and Bajorath J. Determination and mapping of activity-specific descriptor value ranges (MAD) for the identification of active compounds. J. Med. Chem. 49 (2006) 2284-2293
20. Eckert H., et al. Mapping algorithms for molecular similarity analysis and ligand-based virtual screening: design of DynaMAD and comparison with MAD and DMC. J. Chem. Inf. Model. 46 (2006) 1623-1634
21. Brown R.D., and Martin Y.C. Use of structure-activity data to compare structure-based clustering methods and descriptors for use in compound selection. J. Chem. Inf. Comput. Sci. 36 (1996) 572-584
22. Zhang Q., and Muegge I. Scaffold hopping through virtual screening using 2D and 3D similarity descriptors: ranking, voting, and consensus scoring. J. Med. Chem. 49 (2006) 1536-1548
23. Nettles J.H., et al. Bridging chemical and biological space: 'target fishing' using 2D and 3D molecular descriptors. J. Med. Chem. 49 (2006) 6802-6810
24. Wang N., et al. Fast small molecule similarity searching with multiple alignment profiles of molecules represented in one-dimension. J. Med. Chem. 48 (2005) 6980-6990
25. Bender A., and Glen R.C. A discussion of measures of enrichment in virtual screening: comparing the information content of descriptors with increasing levels of sophistication. J. Chem. Inf. Model. 45 (2005) 1369-1375
26. James, C.A. and Weininger, D. (2006). Daylight theory manual, chapter 6. Daylight Chemical Information Systems
27. Barnard J.M., and Downs G.M. Chemical fragment generation and clustering software. J. Chem. Inf. Comput. Sci. 37 (1997) 141-142
28. Bender A., et al. Similarity searching of chemical databases using atom environment descriptors (MOLPRINT 2D): evaluation of performance. J. Chem. Inf. Comput. Sci. 44 (2004) 1708-1718
29. Willett P. Searching techniques for databases of two- and three-dimensional chemical structures. J. Med. Chem. 48 (2005) 4183-4199
30. Hert J., et al. Enhancing the effectiveness of similarity-based virtual screening using nearest-neighbour information. J. Med. Chem. 48 (2005) 7049-7054
31. Xue L., et al. Profile scaling increases the similarity search performance of molecular fingerprints containing numerical descriptors and structural keys. J. Chem. Inf. Comput. Sci. 43 (2003) 1218-1225
32. Schuffenhauer A., et al. Similarity metrics for ligands reflecting the similarity of the target protein. J. Chem. Inf. Comput. Sci. 43 (2003) 391-405
33. Hert J., et al. Comparison of fingerprint-based methods for virtual screening using multiple bioactive reference structures. J. Chem. Inf. Comput. Sci. 44 (2004) 1177-1185
34. Tovar, A. et al. Comparison of 2D fingerprint methods for multiple-template similarity searching on compound classes of increasing structural diversity. ChemMedChem. 10.1002/cmdc.200600225 (http://www3.interscience.wiley.com/cgi-bin/jhome/110485305)
35. Willett P. Similarity-based virtual screening using 2D fingerprints. Drug Discov. Today 11 (2006) 1046-1053
36. Harper G., et al. Prediction of biological activity for high-throughput screening using binary kernel discrimination. J. Chem. Inf. Comput. Sci. 41 (2001) 1295-1300
37. Kauvar L.M., et al. Predicting ligand binding to proteins by affinity fingerprinting. Chem. Biol. 2 (1995) 107-118
38. Briem H., and Lessel U. In vitro and in silico affinity fingerprints: finding similarities beyond structural classes. Perspect. Drug Discov. Des. 20 (2000) 231-244
39. Bender A., et al. 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. 46 (2006) 2445-2456
40. Eckert H., and Bajorath J. Design and evaluation of a novel class-directed 2D fingerprint to search for structurally diverse active compounds. J. Chem. Inf. Model. 46 (2006) 2515-2526
41. Rush III T.S., et al. A shape-based 3D scaffold hopping method and its application to a bacterial protein-protein interaction. J. Med. Chem. 48 (2005) 1489-1495
42. Haigh J.A., et al. Small molecule shape-fingerprints. J. Chem. Inf. Model. 45 (2005) 673-684
43. Jenkins J.L., et al. A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes. J. Med. Chem. 47 (2004) 6144-6159
44. Cheeseright T., et al. Molecular field extrema as descriptors of biological activity: definition and validation. J. Chem. Inf. Model. 46 (2006) 665-676
45. Saeh J.C., et al. Lead hopping using SVM and 3D pharmacophore fingerprints. J. Chem. Inf. Model. 45 (2005) 1122-1133
46. Grant J.A., et al. Lingos, finite state machines, and fast similarity searching. J. Chem. Inf. Model. 46 (2006) 1912-1918
47. Gillet V.J., et al. Similarity searching using reduced graphs. J. Chem. Inf. Comput. Sci. 43 (2003) 338-345
48. Batista J., et al. Assessment of molecular similarity from the analysis of randomly generated structural fragment populations. J. Chem. Inf. Model. 46 (2006) 1937-1944
49. Batista J., and Bajorath J. Chemical database mining through entropy-based molecular similarity assessment of randomly generated structural fragment populations. J. Chem. Inf. Model (2007). http://pubs.acs.org/journals/jcisd8/index.html 10.1021/ci600377m
50. Lang P.T., et al. Evaluating the high-throughput screening competitions. J. Biomol. Screen. 10 (2005) 649-652
51. Schreyer S.K., et al. Data shaving: a focused screening approach. J. Chem. Inf. Comput. Sci. 44 (2004) 470-479
52. Parker C.N., and Bajorath J. Towards unified compound screening strategies: a critical evaluation of error sources in experimental and virtual high-throughput screening. QSAR Comb. Sci. 12 (2006) 1153-1161
53. Das K., et al. Roles of conformational and positional adaptability in structure-based design of TMC125-R165335 (etravirine) and related non-nucleoside reverse transcriptase inhibitors that are highly potent and effective against wild-type and drug-resistant HIV-1 variants. J. Med. Chem. 47 (2004) 2550-2560