ParaDockS: A framework for molecular docking with population-based metaheuristics

Journal of Chemical Information and Modeling

Volumn 50, Issue 5, 2010, Pages 879-889

  Meier, René ^a,b   Pippel, Martin ^a   Brandt, Frank ^c   Sippl, Wolfgang ^a   Baldauf, Carsten ^c,d,e  

^a MARTIN LUTHER UNIVERSITY HALLE WITTENBERG   (Germany)

^b RESEARCH CENTER PHARMACEUTICAL ENGINEERING GMBH   (Austria)

^c DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^d Shanghai Jiao Tong University Affiliated Sixth People s Hospital   (China)

^e HEIDELBERG INSTITUTE FOR THEORETICAL STUDIES   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BINDING ENERGY; DIGITAL LIBRARIES; INDUSTRIAL RESEARCH; KNOWLEDGE BASED SYSTEMS; LIGANDS; MOLECULAR MODELING; RESEARCH AND DEVELOPMENT MANAGEMENT;

COMMERCIAL SOFTWARE; CONTINUOUS OPTIMIZATION PROBLEMS; LARGE COMPOUND LIBRARIES; OBJECTIVE FUNCTIONS; OPTIMIZATION ALGORITHMS; PARTICLE SWARM OPTIMIZERS; RESEARCH AND DEVELOPMENT; SIMULATION TECHNIQUE;

PARTICLE SWARM OPTIMIZATION (PSO);

LIGAND; PROTEIN; RNA DIRECTED DNA POLYMERASE;

ALGORITHM; ARTICLE; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER PROGRAM; COMPUTER SIMULATION; DRUG DESIGN; ENZYMOLOGY; HUMAN IMMUNODEFICIENCY VIRUS; METABOLISM; PROTEIN BINDING;

ALGORITHMS; COMPUTER SIMULATION; DRUG DESIGN; HIV; HIV REVERSE TRANSCRIPTASE; LIGANDS; MODELS, MOLECULAR; PROTEIN BINDING; PROTEINS; SOFTWARE;

EID: 77952754227     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci900467x     Document Type: Article

References (53)

1. Bajorath, F. Integration of virtual and high-throughput screening Nat. Rev. Drug Discovery 2002, 1, 882-894
2. Klebe, G. Virtual ligand screening: strategies, perspectives and limitations Drug Discovery Today 2006, 11, 580-594
3. Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. A fast flexible docking method using an incremental construction algorithm J. Mol. Biol. 1996, 261, 470-489
4. Jain, A. N. Surflex: Fully automatic flexible molecular docking using a molecular similaritybased search engine J. Med. Chem. 2003, 46, 499-511
5. Zsoldos, Z.; Reid, D.; Simon, A.; Sadjad, B. S.; Johnson, A. P. eHiTS: an innovative approach to the docking and scoring function problems Curr. Protein Pept. Sci. 2006, 7, 421-435
6. McGann, M. R.; Almond, H. R.; Nicholls, A.; Grant, J. A.; Brown, F. K. Gaussian docking functions Biopolymers 2003, 68, 76-90
7. 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, 269-288
8. Shoichet, B. K.; Kuntz, I. D. Matching chemistry and shape in molecular docking Protein Eng. 1993, 6, 723-732
9. Jones, G.; Willett, P.; Glen, R. C.; Leach, A. R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking J. Mol. Biol. 1997, 267, 727-748
10. Morris, G. M.; Goodsell, D. S.; Halliday, R. S.; Huey, R.; Hart, W. E.; Belew, R. K.; Olson, A. J. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function J. Comput. Chem. 1998, 19, 1639-1662
11. Korb, O.; Stützle, T.; Exner, T. E. An ant colony optimization approach to flexible proteinligand docking Swarm Intelligence 2007, 1, 115-134
12. Korb, O.; Stützle, T.; Exner, T. E. Empirical Scoring Functions for Advanced Protein-Ligand Docking with PLANTS J. Chem Inf. Model. 2009, 49, 84-96
13. Janson, S.; Merkle, D.; Middendorf, M. Molecular docking with multi-objective particle swarm optimization Appl. Soft. Comput. 2008, 8, 666-675
14. Chen, H. M.; Liu, B. F.; Huang, H. L.; Hwang, S. F.; Ho, S. Y. SODOCK: Swarm optimization for highly flexible protein-ligand docking J. Comput. Chem. 2007, 28, 612-623
15. Namasivayam, V.; Günther, R. PSO@AUTODOCK: A fast flexible molecular docking program based on swarm intelligence Chem. Biol. Drug Des. 2007, 70, 475-484
16. Kennedy, J.; Eberhart, R. Particle swarm optimization Proc. IEEE Int. Conf. Neural Networks 1995, 4, 1942-1948
17. Muegge, I.; Rarey, M. Small Molecule Docking and Scoring Rev. Comput. Chem. 2001, 17, 1-60
18. Böhm, H. J.; Stahl, M. The Use of Scoring Functions in Drug Discovery Applications Rev. Comput. Chem. 2002, 18, 41-87
19. Weiner, S. J.; Kollman, P. A.; Case, D. A.; Singh, U. C.; Ghio, C.; Alagona, G.; Profeta, S.; Weiner, P. A new force field for molecular mechanical simulation of nucleic acids and proteins J. Am. Chem. Soc. 1984, 106, 765-784
20. Böhm, H. J. The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure J. Comput.-Aided Mol. Des. 1994, 8, 243-256
21. Wang, R. X.; Lai, L. H.; Wang, S. M. Further development and validation of empirical scoring functions for structure-based binding affinity prediction J. Comput.-Aided Mol. Des. 2002, 16, 11-26
22. Mitchell, J. B. O.; Laskowski, R. A.; Alex, A.; Thornton, J. M. BLEEP-potential of mean force describing protein-ligand interactions: I. Generating potential J. Comput. Chem. 1999, 20, 1165-1176
23. Mitchell, J. B. O.; Laskowski, R. A.; Alex, A.; Forster, M. J.; Thornton, J. M. BLEEP-potential of mean force describing protein-ligand interactions: II. Calculation of binding energies and comparison with experimental data J. Comput. Chem. 1999, 20, 1177-1185
24. Muegge, I.; Martin, Y. C. A general and fast scoring function for protein-ligand interactions: a simplified potential approach J. Med. Chem. 1999, 42, 791-804
25. Muegge, I. PMF scoring revisited J. Med. Chem. 2006, 49, 5895-5902
26. Gohlke, H.; Hendlich, M.; Klebe, G. Knowledge-based scoring function to predict proteinligand interactions J. Mol. Biol. 2000, 295, 337-356
27. Shoemake, K. Animating rotation with quaternion curves Proc. 12th Annu. Conf. Comput. Graphics Interactive Tech. 1985, 245-254
28. Tripos, L. P. Tripos Mol2 File Format; Tripos: St. Louis, MO, 2007; http://www.tripos.com/tripos-resources/fileroot/mol2-format-Dec07.pdf (accessed November 30, 2009).
29. GNU General Public License, version 2; Free Software Foundation, Inc.: Boston, MA, 1991; http://www.gnu.org/licenses/gpl-2.0.txt (accessed November 6, 2009).
30. Doxygen - Source code documentation generator tool. http://www.stack.nl/ ~dimitri/doxygen (accessed October 3, 2009).
31. SMARTS - A language for describing molecular patterns. http://www.daylight.com/dayhtml/doc/theory/theory.smarts.html (accessed October 3, 2009).
32. ISO/IEC 14977 Information technology - Syntactic metalanguage - Extended BNF. http://standards.iso.org/ittf/PubliclyAvailableStandards/s026153-ISO-IEC- 14977-1996(E).zip (accessed October 3, 2009).
33. Shi, Y.; Eberhart, R. Parameter selection in particle swarm optimization. LNCS Proc. 7th Annu. Conf. Evol. Program., San Diego, CA 1998, 1447, 591-600 (Pubitemid 128118969)
34. Bytheway, I.; Kepert, D. L. The mathematical modelling of cluster geometry J. Math. Chem. 1992, 9, 161-181
35. Ferrari, A. M.; Wei, B. Q.; Costantino, L.; Shoichet, B. K. Soft docking and multiple receptor conformations in virtual screening J. Med. Chem. 2004, 47, 5076-5084
36. Muegge, I.; Martin, Y. C.; Hajduk, P. J.; Fesik, S. W. Evaluation of PMF scoring in docking weak ligands to the FK506 binding protein J. Med. Chem. 1999, 42, 2498-503
37. Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.; Repasky, M. P.; Knoll, E. H.; Shelley, M.; Perry, J. K.; Shaw, D. E.; Francis, P.; Shenkin, P. S. Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy J. Med. Chem. 2004, 47, 1739-1749
38. Kellenberger, E.; Rodrigo, J.; Muller, P.; Rognan, D. Comparative evaluation of eight docking tools for docking and virtual screening accuracy Proteins 2004, 57, 225-242
39. Moitessier, N.; Englebienne, P.; Lee, D.; Lawandi, J.; Corbeil, C. R. Towards the development of universal, fast and highly accurate docking/scoring methods: A long way to go Br. J. Pharmacol. 2007, 153, 7-26
40. Hartshorn, M. J.; Verdonk, M. L.; Chessari, G.; Brewerton, S. C.; Mooij, W. T.; Mortenson, P. N.; Murray, C. W. Diverse, high-quality test set for the validation of protein-ligand docking performance J. Med. Chem. 2007, 50, 726-741
41. 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, 2977-2980
42. Huang, N.; Shoichet, B. K.; Irwin, J. J. Benchmarking sets for molecular docking J. Med. Chem. 2006, 49, 6789-6801
43. MOE 2007.09; Chemical Computing Group Inc.: Montreal, PQ, Canada, 2009.
44. Ren, J.; Nichols, C.; Bird, L.; Chamberlain, P.; Weaver, K.; Short, S.; Stuart, D. I.; Stammers, D. K. Structural mechanisms of drug resistance for mutations at codons 181 and 188 in HIV-1 reverse transcriptase and the improved resilience of second generation non-nucleoside inhibitors J. Mol. Biol. 2001, 312, 795-805
45. World Drug Index; Thomson Scientific: Philadelphia, PA, 2001.
46. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings Adv. Drug Delivery Rev. 1997, 23, 3-25
47. Veber, D. F.; Johnson, S. R.; Cheng, H. Y.; Smith, B. R.; Ward, K. W.; Kopple, K. D. Molecular properties that influence the oral bioavailability of drug candidates J. Med. Chem. 2002, 45, 2615-2623
48. Cheeseright, T. J.; Mackey, M. D.; Melville, J. L.; Vinter, J. G. FieldScreen: Virtual screening using molecular fields. Application to the DUD data set J. Chem. Inf. Model. 2008, 48, 2108-2117
49. DUD A Directory of Useful Decoys; University of California; San Francisco, CA, 2006; http://dud.docking.org/r2 (release date October 22, 2006).
50. Eldridge, M. D.; Murray, C. W.; Auton, T. R.; Paolini, G. V.; Mee, R. P. Empirical scoring functions 1: 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, 425-445
51. Mooij, W. T. M.; Verdonk, M. L. General and targeted statistical potentials for protein-ligand interactions Proteins 2005, 61, 272-287
52. Nicholls, A. What do we know and when do we know it J. Comput.-Aided Mol. Des. 2008, 22, 239-255
53. Brandt, F. A Parallel Framework for High-Throughput Automated Docking. Diploma thesis, TU Dresden, 2007.