Systematic statistical comparison of comparative molecular similarity indices analysis molecular fields for computer-aided lead optimization

Journal of Chemical Information and Modeling

Volumn 46, Issue 5, 2006, Pages 2015-2021

  Dias, Mafalda M ^a   Mittal, Ruchi R ^a   McKinnon, Ross A ^a   Sorich, Michael J ^a  

^a UNIVERSITY OF SOUTH AUSTRALIA   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROSTATICS; HYDROGEN BONDS; MATHEMATICAL MODELS; MOLECULAR STRUCTURE; OPTIMIZATION; STATISTICAL METHODS;

BIOLOGICAL ACTIVITIES; COMPARATIVE MOLECULAR SIMILARITY INDICES ANALYSIS (COMSIA); PREDICTIVE MODELS;

MOLECULAR BIOLOGY;

ARTICLE; COMPARATIVE STUDY; COMPUTER AIDED DESIGN; DRUG DESIGN; HYDROGEN BOND;

COMPUTER-AIDED DESIGN; DRUG DESIGN; HYDROGEN BONDING;

EID: 33750343811     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci600214b     Document Type: Article

References (40)

1. Spellmeyer, D. C; Blaney, J. M.; Martin, E. In Practical Application of Computer-Aided Drug Design; Charifson, P. S., Ed.; Marcel Dekker: New York. 1997; pp 165-193.
2. Williams, M.; Gordon, E. M. In A Textbook of Drug Design and Development, 2nd ed.; Krogsgaard-Larsen, P., Liljefors, T., Madsen, U., Eds.; Harwood Academic Publishers; Sydney, Australia, 1996; pp 1-33.
3. Giersiefen, H.; Hilgenfeld, R.; Hillisch, A. In Modern Methods of Drug Discovery; Hilgenfeld, R., Hillisch, A., Eds.; Birkhäuser Verlag: Basel, Switzerland, 2003; pp 1-18.
4. Charifson, P. S.; Kuntz, I. D. In Practical Application of ComputerAided Drug Design; Charifson, P. S., Ed.; Marcel Dekker: New York, 1997;pp 1-37.
5. Cramer, R. D.. III; Patterson, D. E.: Bunce, J. D. Comparative Molecular Field Analysis (CoMFA). 1. Effect of Shape on Binding of Steroids to Carrier Proteins. J. Am. Chem. Soc. 1988, 110, 5959-5967.
6. Klebe, G.; Abraham, U.: Mietzner, T. Molecular Similarity Indexes in a Comparative-Analysis (CoMSIA) of Drug Molecules to Correlate and Predict Their Biological-Activity. J. Med. Chem. 1994, 37, 41304146.
7. Kim, K. H. In Molecular Similarity in Drug Design; Dean, P., Ed.; Blackie Academic & Professional:' London, 1995; pp 291-331.
8. Cramer, R. D. Topomer CoMFA: A Design Methodology for Rapid Lead Optimization. J. Med. Chem. 2003, 46, 374-388.
9. Bang, S. J.; Cho, S. J. Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) Study of Mutagen X. Bull. Korean Chem. Soc. 2004, 25, 1525-1530.
10. Tervo, A. J.; Nyronen, T. H.; Ronkko, T.; Poso, A. Comparing the Quality and Predictiveness between 3D QSAR Models Obtained from Manual and Automated Alignment. J. Chem. Inf. Comput. Sci. 2004, 44, 807-816.
11. Wang, R. X.; Gao, Y.; Liu. L.; Lai, L. H. All-Orientation Search and All-Placement Search in Comparative Molecular Field Analysis. J. Mol. Model. 1998, 4, 276-283.
12. Depriest, S. A.: Mayer, D.; Naylor, C. B.; Marshall, G. R. 3D-QSAR of Angiotensin-Converting Enzyme and Thermolysin Inhibitors. A Comparison of CoMFA Models Based on Deduced and Experimentally Determined Active-Site Geometries. J. Am. Chem. Soc. 1993, 115, 5372-5384.
13. Rahnasto, M.; Raunio, H.; Poso, A.; Wittekindt, C.; Juvonen, R. O. Quantitative Structure-Activity Relationship Analysis of Inhibitors of the Nicotine Metabolizing CYP2A6 Enzyme. J. Med. Chem. 2005, 48, 440-449.
14. Sutherland, J. J.; O'Brien, L. A.; Weaver, D. F. A Comparison of Methods for Modeling Quantitative Structure-Activity Relationships. J. Med. Chem. 2004, 47, 5541-5554.
15. Sulea, T.: Oprea, T. I.; Muresan, S.; Chan, S. L. A Different Method for Steric Field Evaluation in CoMFA Improves Model Robustness. J. Chem. Inf. Comput. Sci. 1997, 37, 1162-1170.
16. Belvisi, L.; Bravi, G.; Catalane, G.; Mabilia, M.; Salimbeni, A.; Scolastico, C. A 3D QSAR CoMFA Study of Non-Peptide Angiotensin II Receptor Antagonists. J. Comput.-Aided Mol. Des. 1996, 10, 567-582.
17. Maddalena, D. J.; Johnston, G. A. Prediction of Receptor Properties and Binding Affinity of Ligands to Benzodiazepine/GABAA Receptors Using Artificial Neural Networks. J. Med. Chem. 1995, 38, 715-24.
18. Melville, J. L.; Lovelock, K. R. J.; Wilson, C.; Allbutt, B.; Burke, E. K.; Lygo, B.; Hirst, J. D. Exploring Phase-Transfer Catalysis with Molecular Dynamics and 3D/4D Quantitative Structure-Selectivity Relationships. J. Chem. Inf. Model. 2005, 45, 971-981.
19. Tervo, A. J.; Nyronen, T. H.; Ronkko, T.; Poso, A. A Structure-Activity Relationship Study of Catechol-O-methyltransferase Inhibitors Combining Molecular Docking and 3D QSAR Methods. J. Comput.Aided Mol. Des. 2003, 17, 797-810.
20. Chavatte, P.; Yous, S.; Marot, C.; Baurin, N.; Lesieur, D. Three-Dimensional Quantitative Structure-Activity Relationships of Cyclooxygenase-2 (COX-2) Inhibitors: A Comparative Molecular Field Analysis. J. Med. Chem. 2001, 44, 3223-30.
21. Yuan, H. B.; Kozikowski, A. P.; Petukhov, P. A. CoMFA Study of Piperidine Analogues of Cocaine at the Dopamine Transporter: Exploring the Binding Mode of the 3 Alpha-Substituent of the Piperidine Ring Using Pharmacophore-Based Flexible Alignment. J. Med. Chem. 2004, 47, 6137-6143.
22. Sutherland, J. J.; Weaver, D. F. Three-Dimensional Quantitative Structure-Activity and Structure-Selectivity Relationships of Dihydrofolate Reductase Inhibitors. J. Comput.-Aided Mol. Des. 2004, 18. 309-331.
23. Mattioni, B. E.; Jurs, P. C. Prediction of Dihydrofolate Reductase Inhibition and Selectivity Using Computational Neural Networks and Linear Discriminant Analysis. J. Mol. Graphics Modell. 2003, 21. 391-419.
24. Melville, J. L.; Hirst, J. D. On the Stability of CoMFA Models. J. Chem. Inf. Comput. Sci. 2004, 44, 1294-1300.
25. Bostrom, J.I Bohm, M.; Gundertofte, K.; Klebe, G. A 3D QSAR Study on a Set of Dopamine D4 Receptor Antagonists. J. Chem. Inf. Comput. Sci. 2003, 43, 1020-7.
26. Nakagawa, Y.; Takahashi, K.; Kishikawa, H.; Ogura, T.; Minakuchi, C.; Miyagawa, H. Classical and Three-Dimensional QSAR for the Inhibition of [H-3]Ponasterone A Binding by Diacylhydrazine-Type Ecdysone Agonists to Insect Sf-9 Cells. Bioorg. Med. Chem. 2005, 13, 1333-1340.
27. Gohlke, R; 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.
28. Hannongbua, S.; Lawtrakul, L.; Sotriffer, C. A.; Rode, B. M. Comparative Molecular Field Analysis of HTV-1 Reverse Transcriptase Inhibitors in the Class of 1[(2-Hydroxyethoxy)-methyl]-6(phenylthio)thymine. Quant. Struct.-Act. Relat. 1996, 15, 389-394.
29. Luco, J. M.; Ferretti, F. H. QSAR Based on Multiple Linear Regression and PLS Methods for the Anti-HIV Activity of a Large Group of HEPT Derivatives. J. Chem. Inf. Comput. Sci. 1997, 37, 392-401.
30. Tripos Bookshelf 7.1; Tripos Inc.: St. Louis, Missouri, 2005.
31. Schevitz, R. W.; Bach, N. J.; Carlson, D. C.; Chirgadze, N. Y.; Clawson, D. K.; Dillard, R. D.; Draheim, S. E.; Hartley, L. W.; Jones, N. D.; Mihelich, E. D.; Olkowski, J. L.; Snyder, D. W.; Sommers, C.; Wery, J. P. Structure-Based Design of the First Potent and Selective Inhibitor of Human Nonpancreatic Secretory Phospholipase-a(2). Nat. Struct. Biol. 1995, 2, 458-465.
32. Welch, W.; Ahmad, S.; Airey, J. A.; Gerzon, K.; Humerickhouse, R. A.; Besch, H. R.; Ruest, L.; Deslongchamps, P.; Sutko, J. L. Structural Determinants of high-Affinity Binding of Ryanoids to the Vertebrate Skeletal-Muscle Ryanodine Receptor-A Comparative Molecular-Field Analysis. Biochemistry (Moscow, Russ. Fed.) 1994, 33, 6074-6085.
33. Bohm, M.; Sturzebecher, J.; Klebe, G. Three-Dimensional Quantitative Structure-Activity Relationship Analyses Using Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis to Elucidate Selectivity Differences of Inhibitors Binding to Trypsin, Thrombin, and Factor Xa. J. Med. Chem. 1999, 42, 458477.
34. Hu, X.; Stebbins, C. E. Molecular Docking and 3D-QSAR Studies of Yersinia Protein Tyrosine Phosphatase YopH Inhibitors. Bioorg. Med. Chem. 2005, 13, 1101-1109.
35. Viswanadhan, V. N.; Ghose, A. K.; Revankar, G. R.; Robins, R. K. Atomic Physicochemical Parameters for Three-Dimensional Structure Directed Quantitative Structure-Activity Relationships. 4. Additional Parameters for Hydrophobie and Dispersive Interactions and Their Application for an Automated Superposition of Certain Naturally Occurring Nucleoside Antibiotics. J. Chem. Inf. Comput. Sci. 1989, 29, 163-172.
36. Hawkins, D. M.; Basak, S. C.; Mills, D. Assessing model fit by cross-validation. J. Chem. Inf. Comput. Sci. 2003, 43, 579-586.
37. R Development Core Team, R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2005
38. Dixit, A.; Kashaw, S. K.; Gaur, S.; Saxena, A. K. Development of CoMFA, Advance CoMFA and CoMSIA Models in Pyrroloquinazo-lines as Thrombin Receptor Antagonist. Bioorg. Med. Chem. 2004, 12, 3591-3598.
39. Prathipati, P.; Pandey, G.; Saxena, A. K. CoMFA and Docking Studies on Glycogen Phosphorylase A Inhibitors as Antidiabetic Agents. J. Chem. Inf. Model. 2005, 45, 136-145.
40. Chakraborti, A. K.; Gopalakrishnan, B.; Sobhia, M. E.; Malde, A. 3D-QSAR Studies of Indole Derivatives as Phosphodiesterase IV Inhibitors. Eur. J. Med. Chem. 2003, 38, 975-982.