Modeling Steric and Electronic Effects in 3D- and 4D-QSAR Schemes: Predicting Benzoic pKa Values and Steroid CBG Binding Affinities

Journal of Chemical Information and Computer Sciences

Volumn 43, Issue 6, 2003, Pages 2081-2092

  Polanski, Jaroslaw ^a   Bak, Andrzej ^a  

^a UNIVERSITY OF SILESIA   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

BINDING AFFINITIES; ELECTRONIC EFFECTS; STERIC EFFECTS;

ALGORITHMS; CARBOXYLIC ACIDS; COMPUTER SIMULATION; CONFORMATIONS; HAMILTONIANS; SELF ORGANIZING MAPS; VECTORS;

MOLECULAR DYNAMICS;

EID: 0346318486     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci034118l     Document Type: Article

References (35)

1. Kubinyi, H. QSAR and 3D QSAR in drug design. Part 1: Methodology. Drug Discovery Today 1997, 2, 457-467.
2. Kubinyi, H. QSAR and 3D QSAR in drug design. Part 2: Applications and problems. Drug Discovery Today 1997, 2, 538-546.
3. Kubinyi, H. QSAR: Hansch analysis and related approach. In Methods and principles in medicinal chemistry; Mannhold, R., Krokgsgaard-Larsen, P., Timmerman, H., Eds.; VCH: Weinheim, 1993.
4. Katrizky, A. R.; Maran, U.; Labanov, V. S.; Karelson, M. Structurally diverse quantitative structure-property relationship correlations of technology relevant physical properties. J. Chem. Inf. Comput. Sci. 2000, 40, 1-18.
5. Kim, K. H.; Greco, G.; Novellino, E. A critical review of the recent CoMFA applications. Perspect. Drug Discov. Des. 1998, 12/13/14, 257-315.
6. Kroemer, R. T.; Hecht, P.; Guessregen, S.; Liedl, K. R. Improving the quality of CoMFA models. Perspect. Drug Discov. Des. 1998, 12/13/14, 41-56.
7. Martin, Y. C. 3D QSAR: Current state, scope and limitations. Perspect. Drug Discov. Des. 1998, 12/13/14, 3-23.
8. Norinder, U. Recent progress in CoMFA methodology and related techniques. Perspect. Drug Discov. Des. 1998, 12/13/14, 25-39.
9. Vedani, A.; Dobler, M. 5D-QSAR: The key for simulating induced fit? J. Med. Chem. 2002, 45, 2139-2149.
10. Hopfinger, A. J.; Wang, S.; Tokarski, J. S.; Jin, B.; Albuquerque, M.; Madhav, P. J.; Duraiswami, C. Construction of 3D-QSAR models using the 4D-QSAR analysis formalism. J. Am. Chem. Soc. 1997, 119, 10509-10524.
11. Hopfinger, A. J. A QSAR investigation of dihydrofolate reductase by Baker triazines based upon molecular shape analysis. J. Am. Chem. Soc. 1980, 102, 7196-7206.
12. Polanski, J. Molecular Shape Analysis. In Handbook of chemoinformatics From data to knowledge; Gasteiger, J., Ed.; Wiley-VCH: Weinheim, BRD, 2003; pp 302-319.
13. Motoc. J. Molecular shape descriptors. In Steric effects in drug design; Charton, M., Motoc, J., Eds.; Akademie Verlage: Berlin, 1983; pp 93-105.
14. Jain, A. N.; Koile, K.; Chapman, D. Compass-predicting biological activities from molecular-surface properties-performance comparisons on a steroid benchmark. J. Med. Chem. 1994, 37, 2315.
15. Manallack, D. T.; Livingstone, D. J. Neural networks in drug discovery- have they lived up to their promise. Eur. J. Med. Chem. 1999, 34, 195-208.
16. Polanski, J. Self-organizing neural networks for pharmacophore mapping. Adv. Drug Delivery Rev. 2003, 55, 1149-1162.
17. Anzali, S.; Gasteiger, J.; Holzgrabe, U.; Polanski, J.; Sadowski, J.; Teckentrup, A.; Wagener, M. The use of self-organizing neural network in drug design. Perspect. Drug Discov. Des. 1998, 9/10/11, 273-299.
18. Zupan, J.; Gasteiger, J. Neural network and drug design for Chemists, 2nd ed.; VCH: Weinheim, 1999.
19. Physical and chemical data compendium. Poradnik fizykochemiczny; WNT: Warsaw, 1974; pp 347-351.
20. Polanski, J.; Walczak, B. The comparative molecular surface analysis (CoMSA): a novel tool for molecular design. Comput. Chem. 2000, 24, 615-625.
21. Ravi, M.; Hopfinger, A. J.; Hormann, R. E.; Dinan, L. 4D-QSAR analysis of a set ecdysteroids and a comparison to CoMFA modeling. J. Chem. Inf. Comput. Sci. 2001, 41, 1587-1604.
22. A receptor. J. Med. Chem. 2002, 45, 3210-3221.
23. A receptor site using 4D-QSAR analysis. J. Chem. Inf. Comput. Sci. 2003, 43, 324-336.
24. Polanski, J.; Gieleciak, R. The comparative surface analysis (CoMSA) with modified uninformative variable elimination -PLS (UVE-PLS) method: application to the steroids binding the aromatase enzyme. J. Chem. Inf. Comput. Sci. 2002, 43, 656-666.
25. Polanski, J.; Gasteiger, J.; Jarzembek, K.; Self-organizing neural networks for screening and development of novel artificial sweetener candidates. Comb. Chem. High Throughput Screening 2000, 3, 553-561.
26. Anzali, S.; Barnickel, G.; Krug, M.; Sadowski, J.; Wagener, M.; Gasteiger, J.; Polanski, J. The comparison of geometric and electronic properties of molecular surfaces by neural networks. Applications to the analysis of corticosteroid globulin activity of steroids. J. Comput. Aided Mol. Des. 1996, 10, 521-540.
27. a's) of Clonidine-like Imidazolines, 2-Substituted Imidazoles, and l-Methyl-2-substituted-imidazoles from 3D Structures Using a Comparative Molecular Field (CoMFA) Approach. J. Med. Chem. 1991, 34, 2056-2060.
28. Kim, K. H.; Martin, Y. C. Direct prediction of linear free energy substituent effects from 3D structures using comparative molecular field analysis.1. Electronic effects of substitued benzoic acids. J. Org. Chem. 1991, 56, 2723-2729.
29. Martin, Y. C.; Lin, T. C.; Hetti, Ch.; DeLazzer, J. PLS analysis of distance matrices to detect nonlinear relationships between biological potency and molecular properties. J. Med. Chem. 1995, 38, 3009-3015.
30. a values for benzoic and alkanoic acids. J. Chem. Inf. Comput. Sci. 2002, 42, 184-191.
31. Polanski, J. The receptor-like neural network for modeling corticosteroid and testosterone binding globulins. J. Chem. Inf. Comput. Sci. 1997, 37, 553-561.
32. Coats, E. U. The CoMFA steroids as a benchmark dataset for development of 3D QSAR methods. Prospect. Drug Discov. Des. 1998, 12/13/14, 199-213.
33. Robinson, D. D.; Winn, P. J.; Lyne, P. D.; Richards, W. G. Self-organizing molecular field analysis (SOMFA): a tool for structure-activity studies. J. Med. Chem. 1999, 42, 573-583.
34. Hansch, C.; Leo, A. Exploring QSAR Fundamentals and Applications in Chemistry and Biology; American Chemical Society: Washington, DC, 1995; pp 88-93.
35. Fujita, T. Nishioka, T. The analysis of the ortho effect. Prog. Phys. Org. Chem. 1976, 12, 49-89.