Exploring the potential of protein-based pharmacophore models in ligand pose prediction and ranking

Journal of Chemical Information and Modeling

Volumn 53, Issue 5, 2013, Pages 1179-1190

  Hu, Bingjie ^a   Lill, Markus A ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOCHEMISTRY; COMPLEXATION; FORECASTING; LIGANDS; PHARMACODYNAMICS;

GENERATION PROCESS; PHARMACOPHORE MODELS; POSE PREDICTIONS; PROTEIN LIGANDS; PROTEIN-BINDING SITES; PROTEIN-LIGAND COMPLEXES; PROTEIN-LIGAND INTERACTIONS; VIRTUAL SCREENING;

PROTEINS;

LIGAND; PROTEIN; PROTEIN BINDING;

BINDING SITE; CHEMICAL STRUCTURE; CHEMISTRY; DRUG DEVELOPMENT; METABOLISM; PROCEDURES; PROTEIN CONFORMATION; THERMODYNAMICS; ARTICLE; METHODOLOGY; PROTEIN BINDING;

BINDING SITES; DRUG DISCOVERY; LIGANDS; MODELS, MOLECULAR; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEINS; THERMODYNAMICS;

EID: 84878177958     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci400143r     Document Type: Article

References (31)

1. Martin, Y. C. Distance Comparisons: A New Strategy for Examining Three-Dimensional Structure-Activity Relationships. In Classical and Three-Dimensional QSAR in Agrochemistry; Hansch, C., Fujita, T., Eds.; American Chemical Society: Washington, DC: 1995; Chapter 24, pp 318-329.
2. Barnum, D.; Greene, J.; Smellie, A.; Sprague, P. Identification of common functional configurations among molecules J. Chem. Inf. Comput. Sci. 1996, 36 (3) 563-571 (Pubitemid 126539357)
3. Dixon, S. L.; Smondyrev, A. M.; Knoll, E. H.; Rao, S. N.; Shaw, D. E.; Friesner, R. A. PHASE: A new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results J. Comput.-Aided Mol. Des. 2006, 20 (10) 647-671 (Pubitemid 46023928)
4. Richmond, N. J.; Abrams, C. A.; Wolohan, P. R. N.; Abrahamian, E.; Willett, P.; Clark, R. D. GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D J. Comput.-Aided Mol. Des. 2006, 20 (9) 567-587 (Pubitemid 44823892)
5. Chen, X.; Rusinko, A., III; Tropsha, A.; Young, S. S. Automated pharmacophore identification for large chemical data sets J. Chem. Inf. Comput. Sci. 1999, 39 (5) 887-896
6. Wolber, G.; Langer, T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters J. Chem. Inf. Model 2005, 45 (1) 160-169 (Pubitemid 40736968)
7. Kirchhoff, P. D.; Brown, R.; Kahn, S.; Waldman, M.; Venkatachalam, C. Application of structure-based focusing to the estrogen receptor J. Comput. Chem. 2001, 22 (10) 993-1003 (Pubitemid 32614371)
8. Barillari, C.; Marcou, G.; Rognan, D. Hot-spots-guided receptor-based pharmacophores (HS-Pharm): A knowledge-based approach to identify ligand-anchoring atoms in protein cavities and prioritize structure-based pharmacophores J. Chem. Inf. Model 2008, 48 (7) 1396-1410
9. Tintori, C.; Corradi, V.; Magnani, M.; Manetti, F.; Botta, M. Targets looking for drugs: A multistep computational protocol for the development of structure-based pharmacophores and their applications for hit discovery J. Chem. Inf. Model. 2008, 48 (11) 2166-2179
10. Cross, S.; Cruciani, G. Grid-derived structure-based 3D pharmacophores and their performance compared to docking Drug Discovery Today: Technol. 2011, 7 (4) e213-e219
11. Böhm, H. J. The computer program LUDI: A new method for the de novo design of enzyme inhibitors J. Comput.-Aided Mol. Des. 1992, 6 (1) 61-78
12. Wang, R.; Fang, X.; Lu, Y.; Wang, S. The PDBbind database: Collection of binding affinities for protein-ligand complexes with known three-dimensional structures J. Med. Chem. 2004, 47 (12) 2977-80 (Pubitemid 38702694)
13. Wang, R.; Fang, X.; Lu, Y.; Yang, C. Y.; Wang, S. The PDBbind database: Methodologies and updates J. Med. Chem. 2005, 48 (12) 4111-4119 (Pubitemid 40800619)
14. Eldridge, M. D.; Murray, C. W.; Auton, T. R.; Paolini, G. V.; Mee, R. P. Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes J. Comput.-Aided Mol. Des. 1997, 11 (5) 425-45 (Pubitemid 127505895)
15. Baxter, C. A.; Murray, C. W.; Clark, D. E.; Westhead, D. R.; Eldridge, M. D. Flexible docking using tabu search and an empirical estimate of binding affinity Proteins: Struct., Funct., Bioinf. 1998, 33 (3) 367-382 (Pubitemid 28516342)
16. OMEGA, version 2.2.0; OpenEye Scientific Software: Santa Fe, NM. www.eyesopen.com.
17. Bron, C.; Kerbosch, J. Algorithm 457: Finding all cliques of an undirected graph Commun. ACM 1973, 16 (9) 575-577
18. Harley, E. R. Graph Algorithms for Assembling Integrated Genome Maps; University of Toronto: Toronto, Ontario, Canada, 2003.
19. Kabsch, W. A solution for the best rotation to relate two sets of vectors Acta Crystallogr., A 1976, 32 (5) 922-923
20. Wang, R.; Lai, L.; Wang, S. Further development and validation of empirical scoring functions for structure-based binding affinity prediction J. Comput.-Aided Mol. Des. 2002, 16 (1) 11-26 (Pubitemid 34855041)
21. Hu, B.; Lill, M. A. Protein pharmacophore selection using hydration-site Analysis J. Chem. Inf. Model. 2012, 52 (4) 1046-1060
22. Goodford, P. J. A computational procedure for determining energetically favorable binding sites on biologically important macromolecules J. Med. Chem. 1985, 28 (7) 849-857 (Pubitemid 15012490)
23. Kuntz, I. D.; Blaney, J. M.; Oatley, S. J.; Langridge, R.; Ferrin, T. E. A geometric approach to macromolecule-ligand interactions J. Mol. Biol. 1982, 161 (2) 269-288
24. Ewing, T.; Kuntz, I. Critical evaluation of search algorithms for automated molecular docking and database screening J. Comput. Chem. 1997, 18 (9) 1175-1189 (Pubitemid 127650573)
25. Ruppert, J.; Welch, W.; Jain, A. N. Automatic identification and representation of protein binding sites for molecular docking Protein Sci. 1997, 6 (3) 524-533 (Pubitemid 27120049)
26. Cheng, T.; Li, X.; Li, Y.; Liu, Z.; Wang, R. Comparative assessment of scoring functions on a diverse test set J. Chem. Inf. Model. 2009, 49 (4) 1079-93
27. Li, X.; Li, Y.; Cheng, T.; Liu, Z.; Wang, R. Evaluation of the performance of four molecular docking programs on a diverse set of protein-ligand complexes J. Comput. Chem. 2010, 31 (11) 2109-25
28. Plewczynski, D.; Łaźniewski, M.; Augustyniak, R.; Ginalski, K. Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database J. Comput. Chem. 2011, 32 (4) 742-755
29. Renner, S.; Derksen, S.; Radestock, S.; Mörchen, F. Maximum common binding modes (MCBM): consensus docking scoring using multiple ligand information and interaction fingerprints J. Chem. Inf. Model. 2008, 48 (2) 319-332 (Pubitemid 351473035)
30. Bottegoni, G.; Cavalli, A.; Recanatini, M. A comparative study on the application of hierarchical-agglomerative clustering approaches to organize outputs of reiterated docking runs J. Chem. Inf. Model 2006, 46 (2) 852-862
31. Cole, J. C.; Murray, C. W.; Nissink, J. W. M.; Taylor, R. D.; Taylor, R. Comparing protein-ligand docking programs is difficult Proteins: Struct., Funct., Bioinf. 2005, 60 (3) 325-332 (Pubitemid 41061629)