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Comparative Data On Docking Algorithms: Keeping the Update in the Field Knowledge

Hioual K.S, Chikhi A, Bensegueni A, Merzoug A, Boucherit H Published in Algorithms

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
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  1. Merzoug A, Hioual K.s, Chikhi A, Bensegueni A and Boucherit H. Article: Comparative Data On Docking Algorithms: Keeping the Update in the Field Knowledge. International Journal of Applied Information Systems 2(7):27-31, May 2012. BibTeX

    	author = "Merzoug A and Hioual K.s and Chikhi A and Bensegueni A and Boucherit H",
    	title = "Article: Comparative Data On Docking Algorithms: Keeping the Update in the Field Knowledge",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 2,
    	number = 7,
    	pages = "27-31",
    	month = "May",
    	note = "Published by Foundation of Computer Science, New York, USA"


Two docking programs FlexX and GOLD that can be used for either single-ligand docking or database screening have been compared for their propensity to recover the X-ray pose of 153 pharmaceutically relevant protein-ligand complexes and for their capacity to discriminate known inhibitors of an enzyme from randomly chosen "druglike" molecules. Unfortunately, both properties are not found to be correlated since GOLD showing the best docking accuracy is the less successful in ranking known inhibitors in docking experiment. A speed comparison demonstrated that FlexX was thefastest. On the other hand, the best known docking algorithms often fail to position the ligand in anorientation close to the experimental binding mode this is what we call false positives, GOLD was shown to be the worst in ranking the top ten solutions. Moreover, the current study pinpoints one physicochemical descriptor of the ligand which is flexibility that generally lead to docking/scoring inaccuracies.


  1. Brooijmans N, Kuntz ID. 2003, Molecular recognition and docking algorithms. Annu Rev Biophys Biomol Struct; 32:335–373.
  2. Zavodszky MI, Sanschagrin PC, Korde RS, Kuhn LA. 2002, Distilling the essential features of a protein surface for improving protein– igand docking, scoring, and virtual screening. J Comput Aided Mol Des; 16:883–902.
  3. Kellenberger E. , Rodrigo J. , Muller P. , Rognan D. , 2004, Comparative evaluation of eight docking tools for docking and virtual screening accuracy, Proteins, 57(2), 225–242.
  4. Kramer B, Rarey M, Lengauer T. 1999, Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking. Proteins; 37:228–241.
  5. Morris, G. M. , Goodsell, D. S. , Halliday, R. S. , Huey, R. , Hart, W. E. , Belew, R. K. and Olson, A. J. , 1998, J. Comput. Chem. , 19; 1639.
  6. Berman HM, Battistuz T, Bhat TN, Bluhm WF, Bourne PE, Burkhardt K, Feng Z, Gilliland GL, Iype L, Jain S, Fagan P, Marvin J, Padilla D, Ravichandran V, Schneider B, Thanki N, Weissig H, Westbrook JD, Zardecki C. 2002, The Protein Data Bank. Acta Crystallogr D Biol Crystallogr ;58:899 –907.
  7. Badry D. B. , Maxim T. , Ruben A. , Brooks III. C. L. 2003, Comparative study of several algorithms for flexible ligand docking. J. Comput-Aided. Mol. Des, 17, 755–763.
  8. Verdonk M. L. , Cole J. C. , Hartshorn M. J. , Murray C. W. , Taylor R. D. , 2003, Improved protein–ligand docking using GOLD. Proteins, 52, 609–623.
  9. Nissink JWM, Murray CW, Hartshorn MJ, Verdonk ML, Cole JC, Taylor R. 2002, A new test set for validating predictions of protein– ligand interaction. Proteins; 49:457–471.
  10. Zaheer U. H. , Sobia A. H, Reaz U. , Jeffry D. , Madurab B. , 2010, Benchmarking docking and scoring protocol for the identification of potential acetyl cholinesterase inhibitors, J. Mol. Graph. Model, 28, 870–882.
  11. Michael L. , Christopher E. , Stefan P, 2010, Comparison of current docking tools for the simulation of inhibitor binding by the transmembrane domain of the sarco/endoplasmic reticulum calcium ATPase. Biophys. Chem, 150, 88-97.
  12. Chikhi A. , Bensegueni A, 2008, Docking Efficiency Comparison of Surflex, a Commercial Package and Arguslab, a Licensable Freeware. J Comput Sci Syst Biol, 1, 081-086.
  13. Kontoyianni M. , McClellan L. M. , Sokol G. S, 2004, Evaluation of docking performance: comparative data on docking algorithms, J. Med. Chem, 47, 558–565.
  14. Jones G. , Willett P. , Glen R. C. , Leach A. R. , Taylor R, 1997, Development and validation of genetic algorithm for flexible docking. J. Mol. Biol, 267, 727-748.
  15. Becue A. , Meurice N. , Leherte L. , Vercauteren D. P. 2008, Protein-Protein Docking Using Three-Dimensional Reduced Representations and Based on a Genetic Algorithm. . Boeyens J. C. A and Ogilvie J. F. Models, Mysteries, and Magic of Molecules, Springer: Guildford, 301-324.
  16. Verkhivker G. M. , Bouzida D. , Gehlhaar D. K. , Rejto P. A, Arthurs S. , Colson A. B. , Freer S. T. , Larson V. , Luty B. A. , Marrone T. , Rose P. W. , 2000 , Deciphering common failures in molecular docking of ligand–protein complexes, J. Comput. -Aided. Mol. Des,14, 731–751.
  17. Roberts B. C. , Mancera R. L, 2008, Ligand-protein docking with water molecules, J. Chem. Inf. Model, 48, 397–408.


Docking Programs,flexx; Gold Database Screening, Compared, Druglike, Docking Accuracy, Speed, Docking/scoring