Skip to main content
Log in

Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

Numerous methods are available for use as part of a virtual screening strategy but, as yet, no single method is able to guarantee both a level of confidence comparable to experimental screening and a level of computing efficiency that could drastically cut the costs of early phase drug discovery campaigns. Here, we present VSM-G (virtual screening manager for computational grids), a virtual screening platform that combines several structure-based drug design tools. VSM-G aims to be as user-friendly as possible while retaining enough flexibility to accommodate other in silico techniques as they are developed. In order to illustrate VSM-G concepts, we present a proof-of-concept study of a fast geometrical matching method based on spherical harmonics expansions surfaces. This technique is implemented in VSM-G as the first module of a multiple-step sequence tailored for high-throughput experiments. We show that, using this protocol, notable enrichment of the input molecular database can be achieved against a specific target, here the liver-X nuclear receptor. The benefits, limitations and applicability of the VSM-G approach are discussed. Possible improvements of both the geometrical matching technique and its implementation within VSM-G are suggested.

Basic principle of the virtual screening funnel process.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

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

Similar content being viewed by others

Notes

  1. Redocking experiments of LXRβ reference ligands present in the X-ray structures back up this hypothesis. Using GOLD, the 1PQ6 ligand redocked in the 1PQ6 binding pocket conformation yields a significantly higher score than the 1PQ9 ligand redocked in the 1PQ9 conformation. However, according to experimental data, the 1PQ9 ligand is indeed clearly more potent on LXRβ than the 1PQ6 ligand, further indicating that the protein–ligand interaction could not be the dominant term in the free energy of binding

References

  1. DiMasi JA, Hansen RW, Grabowski HG (2003) J Health Econ 22:151–185

    Article  Google Scholar 

  2. Shoichet BK (2004) Nature 432:862–865

    Article  CAS  Google Scholar 

  3. Stahura FL, Bajorath J (2004) Comb Chem High Throughput Screening 7:259–269

    CAS  Google Scholar 

  4. Perola E, Xu K, Kollmeyer TM, Kaufmann SH, Prendergast FG, Pang YP (2000) J Med Chem 43:401–408

    Article  CAS  Google Scholar 

  5. Grüneberg S, Stubbs MT, Klebe G (2002) J Med Chem 45:3588–3602

    Article  CAS  Google Scholar 

  6. Vangrevelinghe E, Zimmermann K, Schoepfer J, Portmann R, Fabbro D, Furet P (2003) J Med Chem 46:2656–2662

    Article  CAS  Google Scholar 

  7. Kraemer O, Hazemann I, Podjarny AD, Klebe G (2004) Proteins: Struct Funct Bioinf 55:814–823

    Article  CAS  Google Scholar 

  8. Doman TN, McGovern SL, Witherbee BJ, Kasten TP, Kurumbail R, Stallings WC, Conolly DT, Shoichet BK (2002) J Med Chem 45:2213–2221

    Article  CAS  Google Scholar 

  9. Bajorath J (2002) Nat Rev Drug Discov 1:882–894

    Article  CAS  Google Scholar 

  10. Abagyan R, Totrov M (2001) Curr Opin Chem Biol 5:375–382

    Article  CAS  Google Scholar 

  11. Xu H, Agrafiotis DK (2002) Curr Top Med Chem 2:1305–1320

    Article  CAS  Google Scholar 

  12. Krovat EM, Langer T (2004) J Chem Inf Comput Sci 44:1123–1129

    Article  CAS  Google Scholar 

  13. Huo S, Wang J, Cieplak P, Kollman PA, Kuntz ID (2002) J Med Chem 45:1412–1419

    Article  CAS  Google Scholar 

  14. Jenwitheesuk E, Samudrala R (2003) BMC Struct Biol 3

  15. Alonso H, Bliznyuk AA, Gready JE (2006) Med Res Rev 26:531–568

    Article  CAS  Google Scholar 

  16. Waszkowycz B, Perkins TDJ, Sykes RA, Li J (2001) IBM Syst J 40:360–376

    Article  Google Scholar 

  17. Bleicher KH, Böhm H-J, Müller K, Alanine AI (2003) Nat Rev Drug Discov 2:369–378

    Article  CAS  Google Scholar 

  18. Veselovsky AV, Ivanov AS (2003) Curr Drug Targets: Infect Disord 3:33–40

    Article  CAS  Google Scholar 

  19. Jain AN (2004) Curr Opin Drug Discov Dev 7:396–403

    CAS  Google Scholar 

  20. Ofran Y, Punta M, Schneider R, Rost B (2005) Drug Discov Today 10:1475–1482

    Article  CAS  Google Scholar 

  21. Dobson CM (2004) Nature 432:824–828

    Article  CAS  Google Scholar 

  22. Oprea TI, Gottfries J (2001) J Comb Chem 3:157–166

    Article  CAS  Google Scholar 

  23. MDL, SD file format. http://www.mdl.com/solutions/white_papers/ctfile_formats.jsp

  24. Tripos, Mol2 file format. http://www.tripos.com/data/support/mol2.pdf

  25. Open Babel project. http://www.openbabel.sourceforge.net

  26. ChemAxon Ltd., Budapest, Hungary. http://www.chemaxon.com/products.html

  27. OpenEye Science Software: Santa Fe, NM. http://www.eyesopen.com

  28. Weininger D (1988) J Chem Inf Comput Sci 28:31–36

    Article  CAS  Google Scholar 

  29. Liao Q, Yao JH, Li F, Yuan SG, Doucet J-P, Panaye A, Fan BT (2004) SAR QSAR Environ Res 15:217–235

    Article  CAS  Google Scholar 

  30. Sadowski J (1993) Chem Rev 93:2567–2581

    Article  CAS  Google Scholar 

  31. PDB file format. http://www.rcsb.org/pdb/static.do?p=file_formats/pdb/index.html

  32. Davis IW, Leaver-Fay A, Chen VB, Block JN, Kapral GJ, Wang X, Murray LW, Arendall III WB, Snoeyink J, Richardson JS, Richardson DC (2007) Nucleic Acids Res 35: W375–W383

  33. Gordon JC, Myers JB, Folta T, Shoja V, Heath LS, Onufriev A (2005) Nucleic Acids Res 33:W368–W371

    Article  CAS  Google Scholar 

  34. Neshich G, Mancini AL, Yamagishi ME, Kuser PR, Fileto R, Pinto IP, Palandrani JF, Krauchenco JN, Baudet C, Montagner AJ, Higa RH (2005) Nucleic Acids Res 33:D269–D274

    Article  CAS  Google Scholar 

  35. Cai W, Zhang M, Maigret B (1998) J Comput Chem 19:1805–1815

    Article  CAS  Google Scholar 

  36. Cai W, Shao X, Maigret B (2002) J Mol Graph Model 20:313–328

    Article  CAS  Google Scholar 

  37. Humphrey W, Dalke A, Schulten K (1996) J Mol Graph 14:33–38

    Article  CAS  Google Scholar 

  38. Verdonk ML, Chessari G, Cole JC, Hartshorn MJ, Murray CW, Nissink JWM, Taylor RD, Taylor R (2005) J Med Chem 48:6504–6515

    Article  CAS  Google Scholar 

  39. Wong CF, Kua J, Zhang Y, Straatsma TP, McCammon JA (2005) Proteins: Struct Funct Bioinf 61:850–858

    Article  CAS  Google Scholar 

  40. Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kalé L, Schulten K (2005) J Comput Chem 26:1781–1802

    Article  CAS  Google Scholar 

  41. So S-S, Karplus M (2001) J Comput Aided Mol Des 15:613–647

    Article  CAS  Google Scholar 

  42. Lyne PD (2002) Drug Discov Today 7:1047–1055

    Article  CAS  Google Scholar 

  43. Wang J, Kollman PA, Kuntz ID (1999) Proteins: Struct Funct Genet 36:1–19

    Article  CAS  Google Scholar 

  44. Miteva MA, Lee WH, Montes MO, Villoutreix BO (2005) J Med Chem 48:6012–6022

    Article  CAS  Google Scholar 

  45. Leroux V, Maigret B (2007) Comput Appl Chem 24:1–10

    CAS  Google Scholar 

  46. Yamagishi MEB, Martins NF, Neshich G, Cai W, Shao X, Beautrait A, Maigret B (2006) J Mol Model 12:965–972

    Article  CAS  Google Scholar 

  47. Singh J, Chuaqui CE, Boriack-Sjodin PA, Lee WC, Pontz T, Corbley MJ, Cheung H-K, Arduini RM, Mead JN, Newman MN, Papadatos JL, Bowes S, Josiah S, Ling LE (2003) Bioorg Med Chem Lett 13:4355–4359

    Article  CAS  Google Scholar 

  48. Ritchie DW, Kemp GJL (1999) J Comput Chem 20:383–395

    Article  CAS  Google Scholar 

  49. Jones G, Willett P, Glen RC (1995) J Mol Biol 245:43–43

    Article  CAS  Google Scholar 

  50. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) J Mol Biol 267:727–748

    Article  CAS  Google Scholar 

  51. Lala DS (2005) Curr Opin Investig Drugs 6:934–943

    CAS  Google Scholar 

  52. Collins JL (2004) Curr Opin Drug Discov Dev 7:692–702

    CAS  Google Scholar 

  53. Färnegårdh M, Bonn T, Sun S, Ljunggren J, Ahola H, Wilhelmsson A, Gustafsson J-Å, Carlquist M (2003) J Biol Chem 278:38821–38828

    Article  CAS  Google Scholar 

  54. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) Nucleic Acids Res 28:235–242

    Article  CAS  Google Scholar 

  55. Williams S, Bledsoe RK, Collins JL, Boggs S, Lambert MH, Miller AB, Moore J, McKee DD, Moore L, Nichols J, Parks D, Watson M, Wisely B, Willson TM (2003) J Biol Chem 278:27138–27143

    Article  CAS  Google Scholar 

  56. Steiner T, Koellner G (1997) Chem Commun (Cambridge, UK) 13:1207–1208

    Article  Google Scholar 

  57. ChemDiv - The chemistry of cures. http://www.chemdiv.com

  58. Enamine - Smart chemistry solutions. http://www.enamine.net

  59. Albany Molecular Research - AMRIDirect chemical compound database. http://www.amridirect.com

  60. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Adv Drug Delivery Rev 23:3–25

    Article  CAS  Google Scholar 

  61. Monge A, Arrault A, Marot C, Morin-Allory L (2006) Mol Divers 10:389–403

    Article  CAS  Google Scholar 

  62. Xue L, Godden J, Bajorath J (1999) J Chem Inf Comput Sci 39:881–886

    Article  CAS  Google Scholar 

  63. Tanimoto TT (1961) Trans NY Acad Sci 2:576–580

    Google Scholar 

  64. Hibert M, Haiech J (2000) M S Méd Sci 16:1332–1339

    Google Scholar 

  65. Chimiothèque Nationale. http://chimiotheque-nationale.enscm.fr/

  66. GOLD CCDC/Astex validation test set results. http://www.ccdc.cam.ac.uk/products/life_sciences/validate/gold_validation/

  67. Koshland D Jr (1994) Angew Chem, Int Ed Engl 33:2375–2378

    Article  Google Scholar 

  68. Spearman C (1904) Am J Psychol 15:72–101

    Article  Google Scholar 

  69. Kendall M (1938) Biometrika 30:81–89

    Google Scholar 

  70. Mavridis L, Hudson BD, Ritchie DW (2007) J Chem Inf Model 47:1787–1796

    Article  CAS  Google Scholar 

  71. Massova I, Kollman PA (2000) Perspect Drug Discov Des 18:113–135

    Article  CAS  Google Scholar 

  72. Gilson MK, Zhou H-X (2007) Annu Rev Biophys Biomol Struct 36:21–42

    Article  CAS  Google Scholar 

  73. Marcou G, Rognan D (2007) J Chem Inf Model 47:195–207

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank Yesmine Asses, Safia Kellou and Amel Maouche for their feedback. Alexandre Beautrait was supported by grants from INRIA (Institut National de Recherche en Informatique et en Automatique), Région Lorraine, and ARC (Association pour la Recherche sur le Cancer); Vincent Leroux by a post-doctoral fellowship from the INCa (Institut National du Cancer); Matthieu Chavent by a joint fellowship between CNRS (Centre National pour la Recherche Scientifique) and Région Lorraine. We thank Openeye for providing free access to OMEGA and VIDA software according to an academic license, Chemaxon for supplying MarvinBeans Java library, CCDC for the trial version of the GOLD program, and the laboratory of chemoinformatics at the Orléans University for the ScreeningAssistant program.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bernard Maigret.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Beautrait, A., Leroux, V., Chavent, M. et al. Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment. J Mol Model 14, 135–148 (2008). https://doi.org/10.1007/s00894-007-0257-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00894-007-0257-9

Keywords

Navigation