Skip to main content

The Role and Application of In Silico Docking in Chemical Genomics Research

  • Protocol
Chemical Genomics

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 310))

Abstract

In silico docking techniques are being used to investigate the complementarity at the molecular level of a ligand and a protein target. As such, docking studies can be used to identify the structural features that are important for binding and for in silico screening efforts in which suitable binding partners can be identified. Here we describe a practical approach for setting up docking simulations using different docking programs. We also cover the analysis and rescoring of the obtained docking poses. Possible pitfalls in the docking studies are discussed and hints are provided to resolve commonly occurring problems.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Hou, T. J. and Xu, X. J. (2004) Recent development and application of virtual screening in drug discovery: an overview. Curr. Pharm. Des. 10, 1011–1033.

    Article  PubMed  CAS  Google Scholar 

  2. Taylor, R. D., Jewsbury, P. J., and Essex, J. W. (2002) A review of protein-small molecule docking methods. J. Comput. Aided Mol. Des. 16, 151–166.

    Article  PubMed  CAS  Google Scholar 

  3. Bohm, H. J. and Stahl, M. (2002) The use of scoring functions in drug discovery applications. Rev. Comp. Chem. 18, 41–87.

    Google Scholar 

  4. Bissantz, C., Folkers, G., and Rognan, D. (2000) Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. J. Med. Chem. 43, 4759–4767.

    Article  PubMed  CAS  Google Scholar 

  5. Paul, N. and Rognan, D. (2002) ConsDock: a new program for the consensus analysis of protein-ligand interactions. Proteins: Struct. Funct. Gen. 47, 521–533.

    Article  CAS  Google Scholar 

  6. Carlson, H. A. and McCammon, J. A. (2000) Accommodating protein flexibility in computational drug design. Mol. Pharmacol. 57, 213–218.

    PubMed  CAS  Google Scholar 

  7. McConkey, B. J., Sobolev, V., and Edelman, M. (2002) The performance of current methods in ligand-protein docking. Curr. Sci. 83, 845–856.

    CAS  Google Scholar 

  8. Bernstein, F. C., Koetzle, T. F., Williams, G. J. B., et al. (1997) The protein data bank: a computer-based archival for macromolecular structures. J. Mol. Biol. 112, 535–542.

    Article  Google Scholar 

  9. Laskowski, R. A., MacArthur, M. W., Moss, D. S., and Thornton, J. M. (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl. Crystallogr. 26, 283–291.

    Article  CAS  Google Scholar 

  10. Hooft, R. W. W., Vriend, G., Sander, C., and Abola, E. E. (1996) Errors in protein structures. Nature 381, 272–272.

    Article  PubMed  CAS  Google Scholar 

  11. Colovos, C. and Yeates, T. O. (1993) Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci. 2, 1511–1519.

    Article  PubMed  CAS  Google Scholar 

  12. Engh, R. A. and Huber, R. (1991) Accurate bond and angle parameters for X-ray protein structure refinement. Acta Cryst. A47, 392–400.

    CAS  Google Scholar 

  13. Hooft, R. W. W., Sander, C., and Vriend, G. (1996) Positioning hydrogen atoms by optimizing hydrogen-bond networks in protein structures. Proteins 26, 363–376.

    Article  PubMed  CAS  Google Scholar 

  14. Glick, M. and Goldblum, A. (2000) A novel energy-based stochastic method for positioning polar protons in protein structures from X-rays. Proteins: Struct. Func. Gen. 38, 273–287.

    Article  CAS  Google Scholar 

  15. Nielsen, J. E. and Vriend, G. (2001) Optimizing the hydrogen-bond network in Poisson-Boltzmann equation-based pKa calculations. Proteins 43, 403–412.

    Article  PubMed  CAS  Google Scholar 

  16. Word, J. M., Lovell, S. C., Richardson, J. S., and Richardson, D. C. (1999) Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. J. Mol. Biol. 285, 1735–1747.

    Article  PubMed  CAS  Google Scholar 

  17. Nielsen, J. E., Andersen, K. V., Honig, B., et al. (1999) Improving macromolecular electrostatics calculations. Prot. Engin. 12, 657–662.

    Article  CAS  Google Scholar 

  18. Kramer, B., Rarey, M., and Lengauer, T. (1999) Evaluation of the FLEXX incremental construction algorithm for protein-ligand docking. Proteins 37, 228–241.

    Article  PubMed  CAS  Google Scholar 

  19. Morris, G. M., Goodsell, D. S., Halliday, R. S., et al. (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J. Comp. Chem. 19, 1639–1662.

    Article  CAS  Google Scholar 

  20. Bohm, 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  PubMed  CAS  Google Scholar 

  21. Wang, R. X., Liu, L., Lai, L. H., and Tang, Y. Q. (1998) SCORE: a new empirical method for estimating the binding affinity of a protein-ligand complex. J. Mol. Mod. 4, 379–394.

    Article  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  23. Poornima, C. S. and Dean, P. M. (1995) Hydration in drug design. 1. Multiple hydrogen-bonding features of water molecules in mediating protein-ligand interactions. J. Comput. Aided Mol. Des. 9, 500–512.

    Article  PubMed  CAS  Google Scholar 

  24. Poornima, C. S. and Dean, P. M. (1995) Hydration in drug design. 2. Influence of local site surface shape on water binding. J. Comput. Aided Mol. Des. 9, 513–520.

    Article  PubMed  CAS  Google Scholar 

  25. Poornima, C. S. and Dean, P. M. (1995) Hydration in drug design. 3. Conserved water molecules at the ligand-binding sites of homologous proteins. J. Comput. Aided Mol. Des. 9, 521–531.

    Article  PubMed  CAS  Google Scholar 

  26. Babine, R. E. and Bender, S. L. (1997) Molecular recognition of protein-ligand complexes: applications to drug design. Chem. Rev. 97, 1359–1472.

    Article  PubMed  CAS  Google Scholar 

  27. Brady, G. P. and Stouten, P. F. W. (2000) Fast prediction and visualization of protein binding pockets with PASS. J. Comput. Aided Mol. Des. 14, 383–401.

    Article  PubMed  CAS  Google Scholar 

  28. Zhang, L. and Hermans, J. (1996) Hydrophilicity of cavities in proteins. Proteins: Struct. Funct. Gen. 24, 433–438.

    Article  CAS  Google Scholar 

  29. Goodford, P. J. (1985) A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J. Med. Chem. 28, 849–857.

    Article  PubMed  CAS  Google Scholar 

  30. Friesner, R. A., Banks, J. L., Murphy, R. B., et al. (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem. 47, 1739–1749.

    Article  PubMed  CAS  Google Scholar 

  31. Schnecke, V. and Kuhn, L. A. (2000) Virtual screening with solvation and ligandinduced complementarity. Perspect. Drug Discovery Des. 20, 171–190.

    Article  CAS  Google Scholar 

  32. Osterberg, F., Morris, G. M., Sanner, M. F., Olson, A. J., and Goodsell, D. S. (2002) Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock. Proteins 46, 34–40.

    Article  PubMed  CAS  Google Scholar 

  33. Rarey, M., Kramer, B., and Lengauer, T. (1999) The particle concept: placing discrete water molecules during protein-ligand docking predictions. Proteins 34, 17–28.

    Article  PubMed  CAS  Google Scholar 

  34. Minke, W. E., Diller, D. J., Hol, W. G. J., and Verlinde, C. (1999) The role of waters in docking strategies with incremental flexibility for carbohydrate derivatives: heat-labile enterotoxin, a multivalent test case. J. Med. Chem. 42, 1778–1788.

    Article  PubMed  CAS  Google Scholar 

  35. de Graaf, C., Pospisil, P., Pos, W., Folkers, G., Vermeulen, N. P. E. (2005) Binding mode prediction of cytochrome P450 and thymidine kinase protein-ligand complexes by consideration of water and rescoring in automated docking. J. Med. Chem. 48, 2308–2318.

    Article  PubMed  Google Scholar 

  36. Pospisil, P., Ballmer, P., Scapozza, L., and Folkers, G. (2003) Tautomerism in computer-aided drug design. J. Rec. Signal Transduction 23, 361–371.

    Article  CAS  Google Scholar 

  37. Rarey, M., Kramer, B., Lengauer, T., and Klebe, G. (1996) A Fast Flexible Docking Method using an Incremental Construction Algorithm. J. Mol. Biol. 261, 470–489.

    Article  PubMed  CAS  Google Scholar 

  38. Jones, G., Willett, P., Glen, R. C., Leach, A. R., and Taylor, R. (1997) Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol. 267, 727–748.

    Article  PubMed  CAS  Google Scholar 

  39. Goodsell, D. S. and Olson, A. J. (1990) Automated docking of substrates to proteins using simulated annealing. Proteins: Struct. Func. Gen. 8, 195–202.

    Article  CAS  Google Scholar 

  40. Klebe, G. (1994) The use of composite crystal-field environments in molecular recognition and the de novo design of protein ligands. J. Mol. Biol. 237, 221–235.

    Article  Google Scholar 

  41. Rarey, M., Kramer, B., and Lengauer, T. (1999) Docking of hydrophobic ligands with interaction-based matching algorithms. Bioinformatics 15, 243–250.

    Article  PubMed  CAS  Google Scholar 

  42. Birch, L., Murray, C. W., Hartshorn, M. J., Tickle, I. J., and Verdonk, M. L. (2002) Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase. J. Comput. Aided Mol. Des. 16, 855–869.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  44. Claussen, H., Buning, C., Rarey, M., and Lengauer, T. (2001) FlexE: efficient molecular docking considering protein structure variations. J. Mol. Biol. 308, 377–395.

    Article  PubMed  CAS  Google Scholar 

  45. Schaffer, L. and Verkhivker, G. M. (1998) Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization. Proteins: Struct. Funct. Gen. 33, 295–310.

    Article  CAS  Google Scholar 

  46. Vigers, G. P. A. and Rizzi, J. P. (2004) Multiple active site corrections for docking and virtual screening. J. Med. Chem. 47, 80–89.

    Article  PubMed  CAS  Google Scholar 

  47. Taylor, R. D., Jewsbury, P. J., and Essex, J. W. (2003) FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function. J. Comput. Chem. 24, 1637–1656.

    Article  PubMed  CAS  Google Scholar 

  48. Lin, J. H., Perryman, A. L., Schames, J. R., and McCammon, J. A. (2003) The relaxed complex method: accommodating receptor flexibility for drug design with an improved scoring scheme. Biopolymers 68, 47–62.

    Article  PubMed  CAS  Google Scholar 

  49. Kairys, V. and Gilson, M. K. (2002) Enhanced docking with the mining minima optimizer: acceleration and side-chain flexibility. J. Comp. Chem. 23, 1656–1670.

    Article  CAS  Google Scholar 

  50. Rarey, M., Kramer, B., Lengauer, T., and Klebe, G. (1996) A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol. 261, 470–489.

    Article  PubMed  CAS  Google Scholar 

  51. Muegge, I. and Martin, Y. C. (1999) A general and fast-scoring function for protein-ligand interactions: a simplified potential approach. J. Med. Chem. 42, 791–804.

    Article  PubMed  CAS  Google Scholar 

  52. Ewing, T. J. A. and Kuntz, I. D. (1997) Critical evaluation of search algorithms for automated molecular docking and database screening. J. Comput. Chem. 18, 1175–1189.

    Article  CAS  Google Scholar 

  53. Eldridge, M. D., Murray, C. W., Auton, T. R., Paoloinine, G. V., and Mee, R. P. (1997) Empirical scoring functions: I. The development of a fast, fully empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J. Comput. Aided Mol. Design 11, 425–445.

    Article  CAS  Google Scholar 

  54. Gohlke, H., Hendlich, M., and Klebe, G. (2000) Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol. 295, 337–356.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Humana Press Inc.

About this protocol

Cite this protocol

Jongejan, A., de Graaf, C., Vermeulen, N.P.E., Leurs, R., de Esch, I.J.P. (2005). The Role and Application of In Silico Docking in Chemical Genomics Research. In: Zanders, E.D. (eds) Chemical Genomics. Methods in Molecular Biology™, vol 310. Humana Press. https://doi.org/10.1007/978-1-59259-948-6_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-59259-948-6_5

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-399-2

  • Online ISBN: 978-1-59259-948-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics