Skip to main content
Springer Nature Link
Log in

The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA

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

Abstract

Principles of fragment-based molecular design are presented and discussed in the context of de novo drug design. The underlying idea is to dissect known drug molecules in fragments by straightforward pseudo-retro-synthesis. The resulting building blocks are then used for automated assembly of new molecules. A particular question has been whether this approach is actually able to perform scaffold-hopping. A prospective case study illustrates the usefulness of fragment-based de novo design for finding new scaffolds. We were able to identify a novel ligand disrupting the interaction between the Tat peptide and TAR RNA, which is part of the human immunodeficiency virus (HIV-1) mRNA. Using a single template structure (acetylpromazine) as reference molecule and a topological pharmacophore descriptor (CATS), new chemotypes were automatically generated by our de novo design software Flux. Flux features an evolutionary algorithm for fragment-based compound assembly and optimization. Pharmacophore superimposition and docking into the target RNA suggest perfect matching between the template molecule and the designed compound. Chemical synthesis was straightforward, and bioactivity of the designed molecule was confirmed in a FRET assay. This study demonstrates the practicability of de novo design to generating RNA ligands containing novel molecular scaffolds.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Scheme 1

Similar content being viewed by others

References

  1. Lowrie JF, Delisle RK, Hobbs DW, Diller DJ (2004) Comb Chem High Throughput Screen 7:495

    CAS  Google Scholar 

  2. Fontaine B, Plassart-Schiess E, Nicole S (1997) Mol Aspects Med 18:415

    Article  CAS  Google Scholar 

  3. Oh SJ, Ha H-J, Chi DY, Lee HK (2001) Curr Med Chem 8:999

    CAS  Google Scholar 

  4. Schneider G, Fechner U (2005) Nat Rev Drug Discov 4:649

    Article  CAS  Google Scholar 

  5. Walters WP, Stahl MT, Murcko MA (1998) Drug Disc Today 3:160

    Article  CAS  Google Scholar 

  6. Lipinski C, Hopkins A (2004) Nature 432:855

    Article  CAS  Google Scholar 

  7. Danziger DJ, Dean PM (1989) Proc R Soc Lond B 236:101

    Article  CAS  Google Scholar 

  8. Lewis RA (1990) J Comput Aided Mol Des 4:205

    Article  CAS  Google Scholar 

  9. Nishibata Y, Itai A (1991) Tetrahedron 47:8985

    Article  CAS  Google Scholar 

  10. Bleicher KH, Böhm H-J, Müller K, Alanine AI (2003) Nat Rev Drug Disc 2:369

    Article  CAS  Google Scholar 

  11. Keseru GM, Makara GM (2006) Drug Discov Today 11:741

    Article  Google Scholar 

  12. Matsumoto C, Hamasaki K, Mihara A, Ueno A (2000) Bioorg Med Chem Lett 10:1857

    Article  CAS  Google Scholar 

  13. Carabateas PM, Schodack NY (1971) Chem Abstr EN. US patent no. 3679690; 77:151966

  14. Schneider P, Schneider G (2003) QSAR Comb Sci 22:713

    Article  CAS  Google Scholar 

  15. Pearlman DA, Murcko MA (1993) J Comput Chem 14:1184

    Article  CAS  Google Scholar 

  16. Clark DE, Frenkel D, Levy SA, Li J, Murray CW, Robson B, Waszkowycz B, Westhead DR (1995) J Comput Aided Mol Des 9:13

    Article  CAS  Google Scholar 

  17. Gillett VJ, Myatt G, Zsoldos Z, Johnson AP (1995) Perspect Drug Discov Des 3:34

    Article  Google Scholar 

  18. Todorov NP, Dean PM (1997) J Comput Aided Mol Des 11:175

    Article  CAS  Google Scholar 

  19. Mauser H, Stahl M (2007) J Chem Inf Model 47:318

    Article  CAS  Google Scholar 

  20. Leach AR, Bryce RA, Robinson AJ (2000) J Mol Graph Model 18:358

    Article  CAS  Google Scholar 

  21. Leach AR, Lewis RA (1994) J Comput Chem 15:233

    Article  CAS  Google Scholar 

  22. Leach AR, Kilvington SR (1994) J Comput Aided Mol Des 8:283

    Article  CAS  Google Scholar 

  23. Böhm H-J (1992) J Comput Aided Mol Des 6:61

    Article  Google Scholar 

  24. Böhm H-J (1992) J Comput Aided Mol Des 6:593

    Article  Google Scholar 

  25. Rotstein SH, Murcko MA (1993) J Med Chem 36:1700

    Article  CAS  Google Scholar 

  26. Murray CW, Clark DE, Auton TR, Firth MA, Li J, Sykes RA, Waszkowycz B, Westhead DR, Young SC (1997) J Comp Aided Mol Des 11:193

    Article  CAS  Google Scholar 

  27. Eksterowicz JE, Evensen E, Lemmen C, Brady GP, Lanctot JK, Bradley EK, Saiah E, Robinson LA, Grootenhuis PD, Blaney JM (2002) J Mol Graph Model 20:469

    Article  CAS  Google Scholar 

  28. Lewis RA (1990) J Comput Aided Mol Des 4:205

    Article  CAS  Google Scholar 

  29. Lewis RA, Roe DC, Huang C, Ferrin TE, Langridge R, Kuntz ID (1992) J Mol Graph 10:66

    Article  CAS  Google Scholar 

  30. Roe DC, Kuntz ID (1995) J Comput Aided Mol Des 9:269

    Article  CAS  Google Scholar 

  31. Gehlhaar DK, Moerder KE, Zichi D, Sherman CJ, Ogden RC, Freer ST (1995) J Med Chem 38:466

    Article  CAS  Google Scholar 

  32. Miranker A, Karplus M (1995) Proteins 23:472

    Article  CAS  Google Scholar 

  33. Jorgensen WL, Ruiz-Caro J, Tirado-Rives J, Basavapathruni A, Anderson KS, Hamilton AD (2006) Bioorg Med Chem Lett 16:663

    Article  CAS  Google Scholar 

  34. Fechner U, Schneider G (2006) J Chem Inf Model 46:699

    Article  CAS  Google Scholar 

  35. Fechner U, Schneider G (2007) J Chem Inf Model 47:656

    Article  CAS  Google Scholar 

  36. Lewell XO, Budd DB, Watson SP, Hann MM (1998) J Chem Inf Comput Sci 38:511

    Article  CAS  Google Scholar 

  37. Schneider G, Lee M-L, Stahl M, Schneider P (2000) J Comput Aided Mol Des 14:487

    Article  CAS  Google Scholar 

  38. Rechenberg I (1994) Evolutionsstrategie ’94. Frommann-Holzboog, Stuttgart

    Google Scholar 

  39. Schneider G, Schuchhardt J, Wrede P (1994) Comput Appl Biosci 10:635

    CAS  Google Scholar 

  40. Schneider G, Schuchhardt J, Wrede P (1996) Biol Cybern 74:203

    Article  Google Scholar 

  41. Gohlke H, Hendlich M, Klebe G (2000) J Mol Biol 295:337

    Article  CAS  Google Scholar 

  42. Schneider G, Böhm H-J (2002) Drug Discov Today 7:64

    CAS  Google Scholar 

  43. Joseph-McCarthy D, Baber JC, Feyfant E, Thompson DC, Humblet C (2007) Curr Opin Drug Discov Devel 10:264

    CAS  Google Scholar 

  44. Waszkowycz B, Clark DE, Frenkel D, Li J, Murray CW, Robson B, Westhead DR (1994) J Med Chem 37:3994

    Article  CAS  Google Scholar 

  45. Nachbar RB (2000) Genet Programming Evolvable Machines 1:57

    Article  Google Scholar 

  46. Pellegrini E, Field MJ (2003) J Comp Aided Mol Des 17:621

    Article  CAS  Google Scholar 

  47. Douguet D, Thoreau E, Grassy G (2000) J Comput Aided Mol Des 14:449

    Article  CAS  Google Scholar 

  48. Globus A, Lawton J, Wipke WT (1999) Nanotechnology 10:290

    Article  Google Scholar 

  49. Schneider G, Chomienne-Clement O, Hilfiger L, Kirsch S, Böhm H-J, Schneider P, Neidhart W (2000) Angew Chemie Int Ed 39:4130

    Article  CAS  Google Scholar 

  50. Brown N, McKay B, Gilardoni F, Gasteiger J (2004) J Chem Inf Comput Sci 44:1079

    Article  CAS  Google Scholar 

  51. Gillet VJ, Khatib W, Willett P, Fleming PJ, Green DVS (2002) J Chem Inf Comput Sci 42:375

    Article  CAS  Google Scholar 

  52. Schneider G, Neidhart W, Giller T, Schmid G (1999) Angew Chemie Int Ed 38:2894

    Article  CAS  Google Scholar 

  53. Böhm H-J (1993) J Mol Recog 6:131

    Article  Google Scholar 

  54. Barnum D, Greene J, Smellie A, Sprague P (1996) J Chem Inf Comput Sci 36:563

    Article  CAS  Google Scholar 

  55. Bush BL, Sheridan RP (1993) J Chem Inf Comput Sci 33:756

    Article  CAS  Google Scholar 

  56. Cormen TH, Leiserson CE, Rivest RL, Stein C (2001) Introduction to algorithms (2nd edn). MIT Press, Cambridge, pp 531–539

    Google Scholar 

  57. Fechner U, Schneider G (2004) QSAR Comb Sci 23:19

    Article  CAS  Google Scholar 

  58. Fechner U, Schneider G (2004) ChemBioChem 5:538

    Article  CAS  Google Scholar 

  59. Rogers-Evans M, Alanine AI, Bleicher KH, Kube D, Schneider G (2004) QSAR Comb Sci 23:426

    Article  CAS  Google Scholar 

  60. Schneider G, Schneider P, Renner S (2006) QSAR Comb Sci 25:1162

    Article  CAS  Google Scholar 

  61. Bannwarth S, Gatignol A (2005) Curr HIV Res 3:61

    Article  CAS  Google Scholar 

  62. Karn J (1999) J Mol Biol 293:235

    Article  CAS  Google Scholar 

  63. Du Z, Lind KE, James TL (2002) Chem Biol 9:707

    Article  CAS  Google Scholar 

  64. Mu Y, Stock G (2006) Biophys J 90:391

    Article  CAS  Google Scholar 

  65. Lind K, Du Z, Fujinaga K, Peterlin B, James T (2002) Chem Biol 9:185

    Article  CAS  Google Scholar 

  66. Tanrikulu Y, Nietert M, Proschak E, Grabowski K, Schneider P, Scheffer U, Göbel M, Schneider G (2007) Chembiochem 8:1932

    Article  CAS  Google Scholar 

  67. Jones G, Willet P, Glen R, Leach A, Taylor R (1997) J Mol Biol 267:727

    Article  CAS  Google Scholar 

  68. Renner S, Ludwig V, Boden O, Scheffer U, Göbel M, Schneider G (2005) Chembiochem 6:1119

    Article  CAS  Google Scholar 

  69. Asachi M, Sasakura K, Sugasawa T (1985) Chem Pharm Bull 33:1826

    Google Scholar 

  70. Mayer M, James TL (2004) J Am Chem Soc 126:4453

    Article  CAS  Google Scholar 

  71. (a) SciFinder Scholar 2006, Chemical Abstracts Service, Columbus, Ohio, USA, excessed Oct. 2007 (b) Somerville AN (1998) J Chem Inf Comput Sci 38:1024

  72. Noeske T, Sasse BC, Stark H, Parsons CG, Weil T, Schneider G (2006) ChemMedChem 1:1066

    Article  CAS  Google Scholar 

  73. Kolb HC, Finn MG, Sharpless KB (2001) Angew Chem Int Ed 40:2004

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Steffi Becker for technical assistance. M.S. is grateful for a predoctoral fellowship from the Dr. Hilmer Foundation. This work was supported by the Beilstein-Institut zur Förderung der Chemischen Wissenschaften, Frankfurt am Main, and the Deutsche Forschungsgemeinschaft (SFB 579 “RNA-Ligand Interactions”, projects A3 and A11).

Author information

Authors and Affiliations

  1. Institute of Organic Chemistry and Chemical Biology, Johann Wolfgang Goethe-University, Max-von-Laue-Straβe 7, Chair for Chem- and Bioinformatics Siesmayerstr. 70, 60323, Frankfurt am Main, Germany

    Andreas Schüller, Marcel Suhartono, Uli Fechner, Yusuf Tanrikulu, Sven Breitung, Ute Scheffer, Michael W. Göbel & Gisbert Schneider

Authors
  1. Andreas Schüller
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Marcel Suhartono
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Uli Fechner
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Yusuf Tanrikulu
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Sven Breitung
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Ute Scheffer
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Michael W. Göbel
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Gisbert Schneider
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Gisbert Schneider.

Additional information

Andreas Schüller and Marcel Suhartono contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schüller, A., Suhartono, M., Fechner, U. et al. The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA. J Comput Aided Mol Des 22, 59–68 (2008). https://doi.org/10.1007/s10822-007-9157-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-007-9157-4

Keywords