Combinatorial QSAR modeling of P-glycoprotein substrates

Journal of Chemical Information and Modeling

Volumn 46, Issue 3, 2006, Pages 1245-1254

  De Cerqueira Lima, Patricia ^a   Golbraikh, Alexander ^a   Oloff, Scott ^a   Xiao, Yunde ^b   Tropsha, Alexander ^a  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b TARGACEPT INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL COMPOUNDS; COMPUTER SIMULATION; DATABASE SYSTEMS; MATHEMATICAL MODELS; MOLECULAR DYNAMICS; OPTIMIZATION;

AMBERGRIS FRAGRANCE; DECISION TREE; K-NEAREST NEIGHBORS CLASSIFICATION; STRUCTURE-ACTIVITY;

CHEMICAL ANALYSIS;

GLYCOPROTEIN P;

ARTICLE; CHEMICAL STRUCTURE; COMBINATORIAL CHEMISTRY; DECISION TREE; METABOLISM; PROTEIN BINDING; QUANTITATIVE STRUCTURE ACTIVITY RELATION; VALIDATION STUDY;

COMBINATORIAL CHEMISTRY TECHNIQUES; DECISION TREES; MODELS, MOLECULAR; P-GLYCOPROTEIN; PROTEIN BINDING; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 33745341752     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci0504317     Document Type: Article

References (57)

1. Sharom, F. J. The P-Glycoprotein Efflux Pump: How Does It Transport Drugs? J. Membr. Biol. 1997, 160, 161-175.
2. Thiebaut, F.; Tsuruo, T.; Hamada, H.; Gottesman, M. M.; Pastan, I.; Willingham, M. C. Cellular Localization of the Multidrug-Resistance Gene Product P-Glycoprotein in Normal Human Tissues. Proc. Natl. Acad. Sci. U.S.A. 1987, 84, 7735-7738.
3. Eisenblatter, T.; Huwel, S.; Galla, H. J. Characterization of the Brain Multidrug Resistance Protein (BMDP/ABCG2/BCRP) Expressed at the Blood-Brain Barrier. Brain Res. 2003, 971, 221-231.
4. Thomas, H.; Coley, H. M. Overcoming Multidrug Resistance in Cancer: An Update on the Clinical Strategy of Inhibiting P-Glycoprotein. Cancer Control 2003, 10, 159-165.
5. Persidis, A. Cancer Multidrug Resistance. Nat. Biotechnol. 1999, 1, 94-95.
6. Lin, J. H. Drug-Drug Interaction Mediated by Inhibition and Induction of P-glycoprotein. Adv. Drug Delivery Rev. 2003, 55, 53-81.
7. Bodo, A.; Bakos, E.; Szeri, F.; Varadi, A.; Sarkadi, B. The Role of Multidrug Transporters in Drug Availability, Metabolism and Toxicity. Toxicol. Lett. 2003, 140-141, 133-143.
8. Pajeva, I.; Wiese, M. Pharmacophore Model of Drugs Involved in P-Glycoprotein Multidrug Resistance: Explanation of Structural Variety (Hypothesis). J. Med. Chem. 2002, 45, 5671-5686.
9. Masuda, S.; Uemoto, S.; Hashida, T.; Inomata, Y.; Tanaka, K.; Inui, K. Effect of Intestinal P-Glycoprotein on Daily Tacromilus through Level in a Living-Donor Small Bowel Recipient. Clin. Pharmacol. Ther. 2000, 68, 98-103.
10. Seelig, A. A General Pattern for Substrate Recognition by P-Glycoprotein. Eur. J. Biochem. 1998, 257, 252-261.
11. Penzotti, J. E.; Lamb, M. L.; Evensen, E.; Grootenhuis, P. D. J. A Computational Ensemble Pharmacophore Model for Identifying Substrates of P-Glycoprotein. J. Med. Chem. 2002, 45, 1737-1740.
12. Slouch, T. R.; Gudmundsson, O. Progress in Understanding the Structure-Activity Relationships of P-Glycoprotein. Adv. Drug Delivery Rev. 2002, 54, 315-328.
13. 1-Adrenergic Antagonists. J. Med. Chem. 2000, 43, 2770-2774.
14. McGregor, M. J.; Muskal, S. M. Pharmacophore Fingerprinting. 1. Application to QSAR and Focused Library Design. J. Chem. Inf. Comput. Sci. 1999, 39, 569-574.
15. Van Drie, J. H.; Nugent, R. A. Addressing the Challenges of Combinatorial Chemistry: 3D Databases, Pharmacophore Recognition and Beyond. SAR QSAR Environ. Res. 1998, 9, 1-21.
16. Mason, J. S.; Morize, I.; Menard, I. R.; Cheney, D. L.; Hulme, C.; Labaudiniere, R. F. New 4-Point Pharmacophore Method for Molecular Similarity and Diversity Applications: Overview of the Method and Applications, Including a Novel Approach to the Design of Combinatorial Libraries Containing Privileged Substructures. J. Med. Chem. 1999, 42, 3251-3264.
17. Smellie, A.; Stanton, R.; Henne, R.; Teig, S. Conformational Analysis by Intersection: CONAN. J. Comput. Chem. 2003, 24, 10-20.
18. Tropsha, A.; Gramatica, P.; Gombar, V. K. The Importance of Being Earnest: Validation Is the Absolute Essential for Successful Application and Interpretation of QSPR Models. QSAR Comb. Sci. 2003, 22, 69-77.
19. Kovatcheva, A.; Golbraikh, A.; Oloff, S.; Xiao, Y.-D.: Zheng, W.; Wolschann, P.; Buchbauer, G.; Tropsha, A. Combinatorial QSAR of Ambergris Fragrance Compounds. J. Chem. Inf. Comput. Sci. 2004, 44, 582-595.
20. Chemical Computing Group. http://www.chemcomp.com/software.htm (accessed Feb 2006).
21. Stanford School of Medicine. http://helix-web.stanford.edu/psb99/Labute. pdf (accessed Feb 2006).
22. Vapnik, V. N. In The Nature of Statistical Learning Theory; Springer: New York, 2000.
23. http://www.edusoft-lc.com/molconn/manuals/400 (accessed Feb 2006).
24. Carhart, R. E.; Smith, D. H.; Venkataraghavan, R. Atom Pairs as Molecular Features in Structure-Activity Studies: Definition and Applications. J. Chem. Inf. Comput. Sci. 1985, 25, 64-73.
25. Shen, M.; LeTiran, A.; Xiao, Y.; Golbraikh, A.; Kohn, H.; Tropsha, A. Quantitative Structure-Activity Relationship Analysis of Functionalized Amino Acid Anticonvulsant Agents Using k Nearest Neighbor and Simulated Annealing PLS Methods. J. Med. Chem. 2002, 45, 2811-2823.
26. Cruciani, G.; Crivori, P.; Carrupt, P.-A.; Testa, B. Molecular Fields in Quantitative Structure-Permeation Relationships: the VolSurf Approach. THEOCHEM 2000, 503, 17-30.
27. Willett, P.; Winterman, V. A. Comparison of Some Measures for the Determination of Intermolecular Structural Similarities. Quant. Struct.-Act. Relat. 1986, 5, 18-25.
28. Daylight Theory: Fingerprints. http://www.daylight.com/dayhtml/doc/ theory/theory.finger.html (accessed Feb 2006).
29. Weininger, D. SMILES. 1. Introduction and Encoding Rules. J. Chem. Inf. Comput. Sci. 1988, 28, 31-36.
30. Syracuse Research Corporation - Environmental Science. http://esc.syrres.com/esc/docsmile.htm (accessed Feb 2006).
31. http://www.tripos.com (accessed Feb 2006).
32. Randić, M. On Characterization on Molecular Branching. J. Am. Chem. Soc. 1975, 97, 6609-6615.
33. Kier, L. B.; Hall, L. H. Molecular Connectivity in Chemistry and Drug Research; Academic Press: New York, 1976.
34. Kier, L. B.; Hall, L. H. Molecular Connectivity in Structure-Activity- Analysis; Wiley: New York, 1986.
35. Kier, L. B. A Shape Index from Molecular Graphs. Quant. Struct.-Act. Relat. 1985, 4, 109-116.
36. Kier, L. B. Inclusion of Symmetry as a Shape Attribute in Kappa-Index Analysis. Quant. Struct-Act. Relat. 1987, 6, 8-12.
37. Hall, L. H.; Kier, L. B. Determination of Topological Equivalence in Molecular Graphs from the Topological State. Quant. Struct.-Act. Relat. 1990, 9, 115-131.
38. Hall, L. H.; Mohney, B. K.: Kier, L. B. The Electrotopological State: An Atom Index for QSAR. Quant. Struct.-Act. Relat. 1991, 10, 43-51.
39. Hall, L. H.; Mohney, B. K.; Kier, L. B. The Electrotopological State: Structure Information at the Atomic Level for Molecular Graphs. J. Chem. Inf. Comput. Sci. 1991, 31, 76-82.
40. Kier, L. B.; Hall, L. H. Molecular Structure Description: The Electrotopological State; Academic Press: New York, 1999.
41. Kellogg, G. E.; Kier, L. B.; Gaillard, P.; Hall, L. H. The E-State Fields. Applications to 3D QSAR. J. Comput.-Aided Mol. Des. 1996, 10, 513-520.
42. Kier, L. B.; Hall, L. H. A Differential Molecular Connectivity Index. Quant. Struct.-Act. Relat. 1991, 10, 134-140.
43. Petitjean, M. Applications of the Radius-Diameter Diagram to the Classification of Topological and Geometrical Shapes of Chemical Compounds. J. Chem. Inf. Comput. Sci. 1992, 32, 331-337.
44. Wiener, H. J. Structural Determination of Paraffin Boiling Points. J. Am. Chem. Soc. 1947, 69, 17-20.
45. Platt, J. R. Influence of Neighbor Bonds on Additive Bond Properties in Paraffins. J. Chem. Phys. 1947, 15, 419-420.
46. Shannon, C.; Weaver, W. In Mathematical Theory of Communication; University of Illinois: Urbana, Illinois, 1949.
47. Bonchev, D.; Mekenyan, O.; Trinajstic, N. Isomer Discrimination by Topological Information Approach. J. Comput. Chem. 1981, 2, 127-148.
48. Balaban, A. T. Five New Topological Indices for the Branching of Tree-Like Graphs. Theor. Chim. Acta 1979, 53, 355-375.
49. Balaban, A. T. Highly Discriminating Distance-Based Topological Index. Chem. Phys. Lett. 1982, 89, 399-404.
50. Gasteiger, J.; Marsili, M. Iterative Partial Equalization of Orbital Electronegativity - A Rapid Access to Atomic Charges. Tetrahedron 1980, 36, 3219-3228.
51. Golbraikh, A.; Shen, M.; Tropsha, A. Enrichment: A New Estimator of Classification Accuracy of QSAR Models. Abstracts of papers of the American Chemical Society 223: 206-COMP; American Chemical Society: Washington, DC, 2002; Part 1.
52. Zheng, W.; Tropsha, A. A Novel Variable Selection QSAR Approach Based on the k-Nearest Neighbor Principle. J. Chem. Inf. Comput. Sci. 2000, 40, 185-194.
53. Breiman, L.; Friedman, J.; Olshen, R.; Stone, C. Classification and Regression Trees; Wadsworth International Group: Belmont, CA, 1984.
54. Schölkopf, B.; Smola, J. A. Learning with Kernels. In Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning); MIT Press: Cambridge, MA, 2002.
55. Wold, S.; Eriksson, L. Statistical Validation of QSAR Results. In Chemometrics Methods in Molecular Design; van de Waterbeemd, H., Ed.; VCH: New York, 1995; pp 309-318.
56. Kubinyi, H.; Hamprecht, F. A.; Mietzner, T. Three-Dimensional Quantitative Similarity-Activity Relationships (3D QSiAR) from SEAL Similarity Matrices. J. Med. Chem. 1998, 41, 2553-2564.
57. 2! J. Mol. Graphics Modell. 2002, 20, 269-276.