Using molecular docking, 3D-QSAR, and cluster analysis for screening structurally diverse data sets of pharmacological interest

Journal of Chemical Information and Modeling

Volumn 48, Issue 10, 2008, Pages 2054-2065

  Santos Filho, Osvaldo A ^a   Cherkasov, Artem ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; DISEASES; LIGANDS;

COMPUTATIONAL COSTS; DIHYDROFOLATE REDUCTASE; HIV-1 REVERSE TRANSCRIPTASE; INTERMOLECULAR INTERACTIONS; MOLECULAR DOCKING; MOLECULAR FINGERPRINT; MOLECULAR TARGETS; STATISTICAL SIGNIFICANCE;

COMPUTATIONAL CHEMISTRY;

DRUG RECEPTOR; LIGAND;

ALGORITHM; ARTICLE; CHEMICAL STRUCTURE; CHEMISTRY; CLUSTER ANALYSIS; DRUG SCREENING; FACTUAL DATABASE; GENETICS; METHODOLOGY; PEPTIDE MAPPING; PROTEIN BINDING; PROTEIN CONFORMATION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICS;

ALGORITHMS; CLUSTER ANALYSIS; DATABASES, FACTUAL; DRUG EVALUATION, PRECLINICAL; GENETICS; LIGANDS; MODELS, MOLECULAR; PEPTIDE MAPPING; PROTEIN BINDING; PROTEIN CONFORMATION; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RECEPTORS, DRUG;

EID: 56449109358     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci8001952     Document Type: Article

References (44)

1. Eposito, E. X.; Hopfinger, A. J.; Madura, J. D. Methods for applying the quantitative structure-activity relationship paradigm. Methods Mol. Biol. 2004, 275, 131-213.
2. Cramer, R. D., III; Patterson, D. E.; Bunce, J. Comparative Molecular Field Analysis (CoMFA). 1. Effect of Shape on Binding of Steroids to Carrier Proteins. J. Am. Chem. Soc. 1988, 110, 5959-5967.
3. Klebe, G.; Abraham, U.; Mietzner, T. Molecular Similarity Indices in a Comparative Analysis (CoMSIA) of Drug Molecules to Correlate and Predict their Biological Activity. J. Med. Chem. 1994, 37, 4130-4146.
4. Robinsin, D. D.; Winn, P. J.; Lyne, P. D.; Richards, W. G. Self organizing molecular field analysis: a tool for structure-activity studies. J. Med. Chem. 1999, 42, 573-583.
5. Glen, W. G.; Dunn, W. J., III; Scot, D. R. Principal components analysis and partial least squares regression. Tetrahedron Comput. Meth. 1989, 2, 349-376.
6. 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.
7. Vedani, A.; Dobler, M.; Lill, M. A. Combining protein and 6D-QSAR. Simulating the binding of structurally diverse ligands to estrogen receptor. J. Med. Chem. 2005, 48, 3700-3703.
8. Tokarki, J. S.; Hopfinger, A. J. Prediction of ligand-receptor thermodynamics by free energy force field (FEFF) 3D-QSAR analysis: application to a set of peptidometic rennin inhibitors. J. Chem. Inf. Comput. Sci. 1997, 37, 792-811.
9. Lili, M. A.; Vedani, A.; Dobler, M. Raptor: Combining Dual-Shell Representation, Induced-Fit Simulation, and Hydrophobicity Scoring in Receptor Modeling: Application toward the Simulation of Structurally Diverse Ligand Sets. J. Med. Chem. 2004, 47, 6174-6186.
10. Gohlke, H.; Klebe, G. DrugScore Meets CoMFA: Adaptation of Fields for Molecular Comparison (AFMoC) or How to Tailor Knowledge-Based Pair-Potentials to a Particular Protein. J. Med. Chem. 2002, 45, 4153-4170.
11. Liu, T.; Lin, Y.; Wen, X.; Jorissen, R. N.; Gilson, M. K. Binding DB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 2006, 00(Database issue), D1-D4 http://www.bindingdb.org/bind/index.jsp (accessed month year).
12. Cherkasov, A.; Shi, Z.; Fallahi, M.; Hammond, G. L. Successful in Silico Discovery of Novel Non-Steroidal Ligands for Human Sex Hormone Binding Globulin (SHBG). J. Med. Chem. 2005, 48, 3203-3213.
13. Cherkasov, A.; Li, Y.; Fallahi, M.; Hammond, G. L. 'Progressive docking': A Hybrid QSAR/Docking Approach for Accelerating in silico High Throughput Screening. J. Med. Chem. 2006, 49, 7466-7478.
14. Cherkasov, A.; Shi, Z.; Li, Y.; Jones, S. J. M.; Fallahi, M.; Hammond, G. L. Inductive' Charges on Atoms in Proteins: Comparative Docking with the Extended Steroid Benchmark Set and Discovery of a Novel SHBG Ligand. J. Chem. Inf. Model. 2005, 45, 1842-1853.
15. Sutherland, J. J.; O'Brien, L. A.; Weaver, D. F. Spline-Fitting with a Genetic Algorithm: A Method for Developing Classification Structure-Activity Relationships. J. Chem. Inf. Comput. Sci. 2003, 43, 1906-1915.
16. Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, P. E. The protein data bank. Nucleic Acids Res. 2000, 28, 235-242; http://www.pdb.org (accessed month year).
17. Maestro 8.5; Schrödinger Inc.: San Diego, CA, 2007.
18. Glide; Version 4.5; Schrödinger Inc.: San Diego, CA, 2007.
19. Cherkasov, A. 'Inductive' Descriptors. 10 Successful Years in QSAR. Curr. Comput.-Aided Drug Des. 2005, 1, 21-42.
20. Cherkasov, A.; Galkin, V. I.; Cherkasov, R. A. The problem of the quantitative evaluation of the inductive effect: correlation analysis. Russ. Chem. Rev. 1996, 65, 641-656.
21. Cherkasov, A.; Shi, Z.; Fallahi, M.; Hammond, G. L. Successful in Silico Discovery of Novel Non-Steroidal Ligands for Human Sex Hormone Binding Globulin (SHBG). J. Med. Chem. 2005, 48, 3203-3213.
22. Cherkasov, A.; Li, Y.; Fallahi, M.; Hammond, G. L. 'Progressive docking': A Hybrid QSAR/Docking Approach for Accelerating in silico High Throughput Screening. J. Med. Chem. 2006, 49, 7466-7478.
23. Cherkasov, A.; Shi, Z.; Li, Y.; Jones, S. J. M.; Fallahi, M.; Hammond, G. L. Inductive' Charges on Atoms in Proteins: Comparative Docking with the Extended Steroid Benchmark Set and Discovery of a Novel SHBG Ligand. J. Chem. Inf. Model. 2005, 45, 1842-1853.
24. Karakoc, A.; Cherkasov, A.; Sahinalp, S. C. Distance Based Algorithms for Small Biomolecule Classification and Structural Similarity Search. Bioinformatics 2006, 22, e243-251.
25. Karakoc, A.; Sahinalp, S. C.; Cherkasov, A. Comparative QSAR- and Fragments Distribution Analysis of Drugs, Drug-likes, Metabolic Substances and Antimicrobial Compounds. J. Chem. Inf. Model. 2006, 46, 2167-2182.
26. Cherkasov, A. Can 'Bacterial-Metabolite-Likeness' Model Improve Odds of in silico Antibiotic Discovery. J. Chem. Inf. Model. 2006, 46, 1214-1222.
27. Jarvis, R. A.; Patrick, E. A. Clustering using a similarity measure based on shared near neighbors. IEEE Trans. Comput. 1973, C-22, 1025-1034.
28. SVL exchange, http://svl.chemcomp.com/viewcat.php (accessed month year).
29. Rogers, D; Hopfinger, A. J. Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships. J. Chem. Inf. Comput. Sci. 1994, 34, 854-866.
30. Holland J. H. Adaptation in Natural and Artificial Systems; Ann Arbor, MI, 1975.
31. Rogers D. G/SPLINES: A Hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) Algorithm with Holland's Genetic Algorithm. The Proceedings of the Fourth International Conference on Genetic Algorithms; San Diego, July 1991.
32. Rogers D. Data Analysis using G/SPLINES. Advances in Neural Processing Systems 4; Kaufmann: San Mateo, CA, 1992.
33. Grishkovskaya, I.; Avvakumov, G. V.; Sklenar, G.; Dales, D.; Hammond, G. L.; Muller, Y. A. Crystal structure of human sex hormone-binding globulin: steroid transport by a laminin G-like domain. EMBO J. 2000, 19, 504-512.
34. Gagjee, A.; Yu, J.; McGuire, J. J.; Cody, V.; Galitsky, N.; Kisliuk, R. L.; Queener, S. F. Design, synthesis, and X-ray crystal structure of a potent dual inhibitor of thymydilate synthase and dihydrofolate reductase as an antitumor agent. J. Med. Chem. 2000, 43, 3837-3851.
35. Panchal, R. G.; Hermone, A. R.; Nguyen, T. L.; Wong, T. Y.; Schwarzenbacher, R.; Schmidt, J.; Lane, D.; McGrath, C.; Turk, B. E.; Burnett, J.; Aman, M. J.; Little, S.; Sausville, E. A.; Zaharevitz, D. W.; Cantley, L. C.; Liddington, R. C.; Gussio, R.; Bavari, S. Identification of small molecule inhibitors of anthrax lethal factor. Nat. Struct. Biol. 2004, 11, 67-72.
36. Ren, J.; Esnouf, R. M.; Hopkins, A. L.; Stuart, D. I.; Stammers, D. K. Crystallographic analysis of the binding modes of thiazoloisoindolinine non-nucleoside inhibitors to HIV-1 reverse transcriptase and comparison with modeling studies. J. Med. Chem. 1999, 42, 3845-3851.
37. Lou, M. Antiviral drugs fit for a purpose. Nature 2006, 443, 37-38.
38. Qiu, X.; Padmanabhan, K. P.; Carperos, V. E.; Tulinsky, A.; Kline, T.; Maraganore, J. M.; Fenton, J. W., II. Structure of the hirulog 3-thrombin complex and nature of the S' subsites of substrates and inhibitors. Biochemistry 1992, 31, 11689-11697.
39. Maignan, S.; Guilloteau, J.-P.; Pouzieux, S.; Choi-Sledeski, Y. M.; Becker, M. R.; Klein, S. I.; Ewing, W. R.; Pauls, H. W.; Spada, A. P.; Mikol, V. Crystal structures of human factor Xa complexed with potent inhibitors. J. Med. Chem. 2000, 43, 3226-3232.
40. MacroModel 9.5; Schrödinger Inc.: San Diego, CA, 2007.
41. MOE: Molecular Operational Environment; Version 2004.03; Chemical Computation Group Inc.: Montreal, Canada, 2004.
42. Edelsbrunner, H.; Facello, M.; Fu, R.; Liang, J. Measuring Proteins and Voids in Proteins Proceedings of the 28th Hawaii International Conference on Systems Science; 1995; pp 256-264.
43. Klein, C. D. P.; Muller, M. K.; Schellinski, C.; Landmann, S.; Hauschild, S.; Heber, D.; Mohr, K.; Hopfinger, A. J. Synthesis, Pharmacological and Biophysical Characterization, and Membrane-Interaction QSAR Analysis of cationic amphiphilic model compounds. J. Med. Chem. 1999, 42, 3874-3888.
44. Kulkarni, A.; Han, Y.; Hopfinger, A. J. Predicting Caco-2 cell permeation coefficients of organic molecules using membraneinteraction QSAR analysis. J. Chem. Inf. Comput. Sci. 2002, 42, 331-342.