Novel method for mining QSPR-Relevant conformations

Chemical Engineering Communications

Volumn 195, Issue 11, 2008, Pages 1396-1423

  Bhonsle, Jayendra B ^a   Huddler, Donald ^a  

^a WALTER REED ARMY INSTITUTE OF RESEARCH   (United States)

Author keywords

Conformation mining; FabI; MFA; QSPR

Indexed keywords

COMPUTATIONAL GEOMETRY; ERROR ANALYSIS; MINING;

INHIBITION ACTIVITIES; NON-LINEAR QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS (QSPR) MODEL; NOVEL METHODOLOGY; NOVEL METHODS; S. AUREUS;

THREE DIMENSIONAL;

EID: 47349107465     PISSN: 00986445     EISSN: 15635201     Source Type: Journal    
DOI: 10.1080/00986440801963808     Document Type: Conference Paper

References (45)

1. (2005) Cerius2 Version 4.10L Manual
2. Balaban, A. T. (1982) Highly discriminating distance-based topological index. Chem. Phys. Lett., 89, p. 399.
3. Basak, S. C. and Mills, D. (2001) Quantitative structure-property relationships (QSPRs) for the estimation of vapor pressure: A hierarchical approach using mathematical structural descriptors. J. Chem. Inf. Comput. Sci., 41, p. 692.
4. Bhonsle, J. B. (2005)
5. Bhonsle, J. B. (2005)
6. Bhonsle, J. B., Bhattacharjee, A. K. and Gupta, R. K. (2007) Novel semi-automated methodology for developing highly predictive QSAR models: Application for development of QSAR models for insect repellent amides. J. Mol. Model., 13, p. 179.
7. Bhonsle, J. B., Wang, Z. -X., Tamamura, H., Fujii, N., Peiper, S. C. and Trent, J. O. (2005) A simple, automated quasi-4D-QSAR, quasi-multi way PLS approach to develop highly predictive QSAR models for highly flexible CXCR4 inhibitor cyclic pentapeptide ligands using scripted common molecular modeling tools. QSAR Comb. Sci., 24, p. 620.
8. Bro, R. (1996) Multiway calibration. Multilinear PLS. J. Chemom., 10, p. 47.
9. Brown, W. M., Martin, S., Rintoul, M. D. and Faulon, J. -L. (2006) Designing novel polymers with targeted properties using the signature molecular descriptor. J. Chem. Inf. Model., 46, p. 826.
10. Cramer, R. D., Patterson, D. E. and Bunce, J. D. (1988) Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc., 110, p. 5959.
11. Dewar, M. J. S. and Thiel, W. (1977) Ground states of molecules. 39: MNDO results for molecules containing hydrogen, carbon, nitrogen, and oxygen. J. Am. Chem. Soc., 99, p. 4907.
12. Ghose, A. K. and Crippen, G. M. (1986) Atomic physicochemical parameters for three-dimensional structure-directed quantitative structure-activity relationships. 1. Partition coefficients as a measure of hydrophobicity. J. Comput. Chem., 7, p. 565.
13. Ghose, A. K. and Crippen, G. M. (1987) Atomic physicochemical parameters for three-dimensional-structure-directed quantitative structure-activity relationships. 2. Modeling dispersive and hydrophobic interactions. J. Chem. Inf. Comput. Sci., 27, p. 21.
14. Golbraikh, A. and Tropsha, A. (2002) Predictive QSAR modeling based on diversity sampling of experimental datasets of the training and test set selection. Mol. Divers., 5, p. 231.
15. Hall, L. H. and Kier, L. B. (1991) The molecular connectivity chi indexes and kappa shape indexes in structure-property modeling. Rev. Comput. Chem., 2, p. 367.
16. Hansch, C. (1969) Quantitative approach to biochemical structure-activity relationships. Acc. Chem. Res., 2, p. 232.
17. Hasegawa, K., Arakawa, M. and Funatsu, K. (1999) 3D-QSAR study of insecticidal neonicotinoid compounds based on 3-way partial least squares model. Chemom. Intell. Lab. Syst., 47, p. 33.
18. Hasegawa, K., Arakawa, M. and Funatsu, K. (2000) Rational choice of bioactive conformations through use of conformation analysis and 3-way partial least squares. Chemom. Intell. Lab. Syst., 50, p. 253.
19. Hill, T. L. (1960) An Introduction to Statistical Thermodynamics, Addison-Wesley, Reading, Mass
20. Ivanciuc, O., Ivanciuc, T. and Klein, D. J. (2001) Quantitative structure-property relationships generated with optimizable even/odd Wiener polynomial descriptors. SAR QSAR Environ. Res., 12, p. 1.
21. Jain, A. N., Dietterich, T. G., Lathrop, R. H., Chapman, D., Critchlow, R. E., Bauer, B. E., Webster, T. A. and Lozano-Perez, T. (1994) Compass: A shape-based machine learning tool for drug design. J. Comput. Aided Mol. Des., 8, p. 635.
22. Katritzky, A. R., Petrukhin, R., Jain, R. and Karelson, M. (2001) QSPR analysis of flash points. J. Chem. Inf. Comput. Sci., 41, p. 1521.
23. Katritzky, A. R., Kuanar, M., Fara, D. C., Oliferenko, A., Oliferenko, P., Huddleston, J. G. and Rogers, R. D. (2004) Aqueous biphasic systems. Partitioning of organic molecules: A QSPR treatment. J. Chem. Inf. Comput. Sci., 44, p. 136.
24. Kier, L. B. (1985) A shape index from molecular graphs. Quant. Struct. Act. Relat., 4, p. 109.
25. Kier, L. B. and Hall, L. H. (1992) The Electrotopological State Index: An Atom-Centered Index for QSAR, Academic Press, London
26. Klebe, G. (1998) Comparative molecular similarity indices analysis: CoMSIA. Prospect. Drug Discov. Des., 12, p. 87.
27. L'Heureux, P. -J., Carreau, J., Bengio, Y., Delalleau, O. and Yue, S. Y. (2004) Locally linear embedding for dimensionality reduction in QSAR. J. Comput. Aided Mol. Des., 18, p. 475.
28. Marsali, M. and Gasteiger, J. (1980) Charge distribution from molecular topology and orbital electronegativity. Croatica Chim. Acta, 53, p. 601.
29. Melagraki, G., Afantitis, A., Sarimveis, H., Koutentis, P. A., Markopoulos, J. and Igglessi-Markopoulou, O. (2007) A novel QSPR model for predicting theta (lower critical solution temperature) in polymer solutions using molecular descriptors. J. Mol. Model., 13, p. 55.
30. Metivier-Pignon, H., Faur, C. and Cloirec, P. L. (2007) Adsorption of dyes onto activated carbon cloth: Using QSPRs as tools to approach adsorption mechanisms. Chemosphere, 66, p. 887.
31. Modarresi, H., Dearden, J. C. and Modarress, H. (2006) QSPR correlation of melting point for drug compounds based on different sources of molecular descriptors. J. Chem. Inf. Model., 46, p. 930.
32. Modarresi, H., Modarress, H. and Dearden, J. C. (2005) Henry's law constant of hydrocarbons in air-water system: The cavity ovality effect on the non-electrostatic contribution term of solvation free energy. SAR QSAR Environ. Res., 16, p. 461.
33. Olah, M., Bologa, C. and Oprea, T. I. (2004) An automated PLS search for biologically relevant QSAR descriptors. J. Comput. Aided Mol. Des., 18, p. 437.
34. Patel, H. C., Tokarski, J. S. and Hopfinger, A. J. (1997) Molecular modeling of polymers. 16. Gaseous diffusion in polymers: A quantitative structure-property relationship (QSPR) analysis. Pharm Res., 14, p. 1349.
35. Puri, S., Chickos, J. S. and Welsh, W. J. (2002) Three-dimensional quantitative structure-property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): Enthalpy of sublimation. J. Chem. Inf. Comput. Sci., 42, p. 109.
36. Ren, B. (2003) New atom-type-based AI topological indices: Application to QSPR studies of aldehydes and ketones. J. Comput. Aided Mol. Des., 17, p. 607.
37. Ren, Y., Liu, H., Yao, X., Liu, M., Hu, Z. and Fan, B. (2006) The accurate QSPR models for the prediction of nonionic surfactant cloud point. J. Colloid Interface Sci., 302, p. 669.
38. Rohrbaugh, R. H. and Jurs, P. C. (1987) Descriptions of molecular shape applied in studies of structure/activity and structure/property relationships. Anal. Chim. Acta, 199, p. 99.
39. Seefeld, M. A., Miller, W. H., Newlander, K. A., Burgess, W. J., Payne, D. J., Rittenhouse, S. F., Moore, T. D., DeWolf Jr., W. E., Keller, P. M., Qiu, X., Janson, C. A., Vaidya, K., Fosberry, A. P., Smyth, M. G., Jaworski, D. D., Slater-Radosti, C. and Huffman, W. F. (2001) Inhibitors of bacterial enoyl acyl carrier protein reductase (FabI): 2,9-disubstituted 1,2,3,4-tetrahydropyrido[3,4-b]indoles as potential antibacterial agents. Bioorg. Med. Chem. Lett., 11, p. 2241.
40. Stanton, D. T. and Jurs, P. C. (1990) Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies. Anal. Chem., 62, p. 2323.
41. Sutter, J. M., Dixon, S. L. and Jurs, P. C. (1995) Automated descriptor selection for quantitative structure-activity relationships using generalized simulated annealing. J. Chem. Inf. Comput. Sci., 35, p. 77.
42. Tabaraki, R., Khayamian, T. and Ensafi, A. A. (2006) Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide. J. Mol. Graph. Model., 25, p. 46.
43. Xu, J., Guo, B., Chen, B. and Zhang, Q. (2005) A QSPR treatment for the thermal stabilities of second-order NLO chromophore molecules. J. Mol. Model., 12, p. 65.
44. Yao, S. W., Lopes, V. H. C., Fernandez, F., Garcia-Mera, X., Morales, M., Rodriguez-Borges, J. E. and Cordeiro, M. N. D. (2003) Synthesis and QSAR study of the anticancer activity of some novel indane carbocyclic nucleosides. Bioorg. Med. Chem., 11, p. 4999.
45. Zheng, W. and Tropsha, A. (2000) Novel variable selection quantitative structure-property relationship approach based on the K-nearest-neighbor principle. J. Chem. Inf. Comput. Sci., 40, p. 185.