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Exploring fragment spaces under multiple physicochemical constraints

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Abstract

We present a new algorithm for the enumeration of chemical fragment spaces under constraints. Fragment spaces consist of a set of molecular fragments and a set of rules that specifies how fragments can be combined. Although fragment spaces typically cover an infinite number of molecules, they can be enumerated in case that a physicochemical profile of the requested compounds is given. By using min–max ranges for a number of corresponding properties, our algorithm is able to enumerate all molecules which obey these properties. To speed up the calculation, the given ranges are used directly during the build-up process to guide the selection of fragments. Furthermore, a topology based fragment filter is used to skip most of the redundant fragment combinations. We applied the algorithm to 40 different target classes. For each of these, we generated tailored fragment spaces from sets of known inhibitors and additionally derived ranges for several physicochemical properties. We characterized the target-specific fragment spaces and were able to enumerate the complete chemical subspaces for most of the targets.

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Abbreviations

ACE:

Angiotensin-converting enzyme

AChE:

Acetylcholinesterase

ADA:

Adenosine deaminase

ALR2:

Aldose reductase

AmpC:

AmpC β-lactamase

AR:

Androgen receptor

CDK2:

Cyclin-dependent kinase 2

COMT:

Catechol O-methyltransferase

COX-1:

Cyclooxygenase-1

COX-2:

Cyclooxygenase-2

DHFR:

Dihydrofolate reductase

EGFr:

Epidermal growth factor receptor

ER:

Estrogen receptor

FGFr1:

Fibroblast growth factor receptor kinase

FXa:

Factor Xa

GART:

Glycinamide ribonucleotide transformylase

GPB:

Glycogen phosphorylase β

GR:

Glucocorticoid receptor

HIVPR:

HIV protease

HIVRT:

HIV reverse transcriptase

HMGR:

Hydroxymethylglutaryl-CoA reductase

HSP90:

Human heat shock protein 90

InhA:

Enoyl ACP reductase

MR:

Mineralocorticoid receptor

NA:

Neuraminidase

P38 MAP:

P38 mitogen activated protein

PARP:

Poly(ADP-ribose) polymerase

PDE5:

Phosphodiesterase 5

PDGFrb:

Platelet derived growth factor receptor kinase

PNP:

Purine nucleoside phosphorylase

PPARg:

Peroxisome proliferator activated receptor γ

PR:

Progesterone receptor

RXRa:

Retinoic X receptor α

SAHH:

S-adenosyl-homocysteine hydrolase

SRC:

Tyrosine kinase SRC

TK:

Thymidine kinase

VEGFr2:

Vascular endothelial growth factor receptor

References

  1. Walters WP, Stahl MT, Murcko MA (1994) Drug Discov Today 4:160

    Google Scholar 

  2. Oprea TI, Gottfries J (2001) J Comb Chem 3:157

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  4. Dobson CM (2004) Nature 432:824

    Article  CAS  Google Scholar 

  5. Rarey M, Degen J, Reulecke I (2007) Docking and scoring for structure-based drug design. Bioinformatics – from genomes to therapies, vol 2. Wiley-VCH Verlag GmbH & Co. KGaA, Weinmheim, p 541

  6. Rarey M, Stahl M (2001) J Comput-Aided Mol Design 15:497

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  8. Lewell XQ, Judd DB, Watson SP, Hann MM (1998) J Chem Inf Comput Sci 38:511

    Article  CAS  Google Scholar 

  9. WDI: World Drug Index, Derwent Information

  10. Rarey M, Dixon JS (1998) J Comput-Aided Mol Design 12:471

    Article  CAS  Google Scholar 

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

    CAS  Google Scholar 

  12. Degen J, Rarey M (2006) ChemMedChem 1:854

    Article  CAS  Google Scholar 

  13. Rarey M, Kramer B, Lengauer T, Klebe G (1996) J Mol Biol 261:470

    Article  CAS  Google Scholar 

  14. Weber L (2005) QSAR Comb Sci 24:809

    Article  CAS  Google Scholar 

  15. Ghose AK, Viswanadhan VN (2001) Combinatorial library design and evaluation. Marcel Dekker Inc

  16. Knuth DE (1968) The Art of computer programming – fundamental algorithms. Addison-Wesley

  17. Weininger D, Weininger A, (1986) J Chem Inf Comput Sci 29:97

    Article  Google Scholar 

  18. Knott GD (1971) ACM 1:175

    Google Scholar 

  19. Bentley JL (1975) Commun ACM 18:509

    Article  Google Scholar 

  20. Huang N, Shoichet BK, Irwin JJ (2006) J Med Chem 49:6789

    Article  CAS  Google Scholar 

  21. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Adv Drug Deliv Rev 23:3

    Article  CAS  Google Scholar 

  22. Wildman SA (1999) J Chem Inf Comput Sci 39:868

    Article  CAS  Google Scholar 

  23. SYBYL mol2 file format. Tripos Inc

  24. Sadowski J, Rudolph C, Gasteiger J (1990) Tetrahedron Comput Methodol 3:537

    Article  Google Scholar 

  25. Sadowski J, Schwab CH, Gasteiger J (2006) Corina, version 3.10, Molecular Networks GmbH Computerchemie. Erlangen

  26. Stahl M, Rarey M (2001) J Med Chem 44:1035

    Article  CAS  Google Scholar 

  27. Fricker P, Gastreich M, Rarey M (2004) J Chem Inf Comput Sci 44:1065

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors thank Andrea Zaliani (Lilly Research Laboratories, Hamburg, Germany) for careful reading of the manuscript and Tora Pommerencke, Christoph Müller and Florian Krull, who developed some useful ideas how to improve the performance of the enumeration during their time as project students. Additionally, we thank Patrick Maaß for help in generating the fragments out of the inhibitors sets. We further thank all partners in the NovoBench project for fruitful feedback and the german federal ministry of education and research for funding (grant 313324A).

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Authors and Affiliations

  1. Center for Bioinformatics, Bundesstrasse 43, 20146, Hamburg, Germany

    Juri Pärn, Jörg Degen & Matthias Rarey

Authors
  1. Juri Pärn
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  2. Jörg Degen
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  3. Matthias Rarey
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Corresponding author

Correspondence to Matthias Rarey.

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Pärn, J., Degen, J. & Rarey, M. Exploring fragment spaces under multiple physicochemical constraints. J Comput Aided Mol Des 21, 327–340 (2007). https://doi.org/10.1007/s10822-007-9121-3

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  • DOI: https://doi.org/10.1007/s10822-007-9121-3

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