Skip to main content
SpringerLink
Log in

Knowing when to give up: early-rejection stratagems in ligand docking

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

Virtual screening is an important resource in the drug discovery community, of which protein–ligand docking is a significant part. Much software has been developed for this purpose, largely by biochemists and those in related disciplines, who pursue ever more accurate representations of molecular interactions. The resulting tools, however, are very processor-intensive. This paper describes some initial results from a project to review computational chemistry techniques for docking from a non-chemistry standpoint. An abstract blueprint for protein–ligand docking using empirical scoring functions is suggested, and this is used to discuss potential improvements. By introducing computer science tactics such as lazy function evaluation, dramatic increases to throughput can and have been realized using a real-world docking program. Naturally, they can be extended to any system that approximately corresponds to the architecture outlined.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Kitchen DB, Decornez H, Furr JR, Bajorath J et al (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3:935–949

    Article  CAS  Google Scholar 

  2. McGaughey GB, Sheridan RP, Bayly CI, Culberson JC, Kreatsoulas C, Lindsley S, Maiorov V, Truchon J-F, Cornell WD et al (2007) Comparison of topological, shape, and docking methods in virtual screening. J Chem Inf Model 47:1504–1519

    Article  CAS  Google Scholar 

  3. Warren GL, Webster Andrews C, Capelli A-M, Clarke B, LaLonde J, Lambert MH, Lindvall M, Nevins N, Semus SF, Senger S, Tedesco G, Wall ID, Woolven JM, Peishoff CE, Head MS et al (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49:5912–5931

    Article  CAS  Google Scholar 

  4. Wang R, Lu Y, Wang S et al (2003) Comparative evaluation of 11 scoring functions for molecular docking. J Med Chem 46:2287–2303

    Article  CAS  Google Scholar 

  5. Böhm H-J (1994) 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 8:243–256

    Article  Google Scholar 

  6. Taylor RD, Jewsbury PJ, Essex JW et al (2002) A review of protein–small molecule docking methods. J Comput Aided Mol Des 16:151–166

    Article  CAS  Google Scholar 

  7. Campbell SJ, Gold ND, Jackson RM, Westheady DR et al (2003) Ligand binding: functional site location, similarity and docking. Curr Opin Struct Biol 13:389–395

    Article  CAS  Google Scholar 

  8. Halperin I, Ma B, Wolfson H, Nussinov R et al (2002) Principles of docking: an overview of search algorithms and a guide to scoring functions. Proteins 47:409–443

    Article  CAS  Google Scholar 

  9. Hart WE (1994) Adaptive global optimization with local search. PhD thesis, University of California, San Diego

  10. Hart WE, Kammeyer TE, Belew RK et al (1994) The role of development in genetic algorithms. Foundations of genetic algorithms III, pp 315–332. Morgan Kauffman, San Mateo, CA

  11. Nelder JA, Mead R (1965) A simplex method for function minimization. Comput J 7:308–313

    Google Scholar 

  12. Gehlhaar DK, Verkhivker GM, Rejto PA, Sherman CJ, Fogel DB, Fogel LJ, Freer ST et al (1995) Molecular recognition of the inhibitor AC-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming. Chem Biol 2:317–324

    Article  CAS  Google Scholar 

  13. Böhm H-J, Stahl M (2000) Structure-based library design: molecular modelling merges with combinatorial chemistry. Curr Opin Chem Biol 4:283–286

    Article  Google Scholar 

  14. Wang R, Lai L, Wang S et al (2002) Further development and validation of empirical scoring functions for structure-based binding affinity prediction. J Comput Aided Mol Des 16:11–26

    Article  CAS  Google Scholar 

  15. Hartshorn MJ, Verdonk ML, Chessari G, Brewerton SC, Mooij WTM, Mortenson PN, Murray CW et al (2007) Diverse, high-quality test set for the validation of protein-ligand docking performance. J Med Chem 50:726–741

    Article  CAS  Google Scholar 

  16. Bohme Leite T, Gomes D, Miteva MA, Chomilier J, Villoutreix BO, Tufféry P et al (2007) Frog: a FRee Online druG 3D conformation generator. Nucleic Acids Res 35:W568–W572

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by InhibOx Ltd. (http://www.inhibox.com, 2009). The authors thank Daniel Robinson, Romesh Ranawana, and Garrett Morris for several helpful conversations there, and for the use of their source code as a foundation project.

Author information

Authors and Affiliations

  1. Oxford University Computing Laboratory, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK

    Gwyn Skone, Irina Voiculescu & Stephen Cameron

Authors
  1. Gwyn Skone
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Irina Voiculescu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stephen Cameron
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gwyn Skone.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Skone, G., Voiculescu, I. & Cameron, S. Knowing when to give up: early-rejection stratagems in ligand docking. J Comput Aided Mol Des 23, 715–724 (2009). https://doi.org/10.1007/s10822-009-9296-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-009-9296-x

Keywords

Search

Navigation