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Annotation and classification of chemical space in chemogenomics

  • Dragos Horvath
Chapter

Abstract

How do we recognise a drug? Can one, by looking at any chemical formula, declare: “it is out of the question that this molecule could act as a drug – it is simply not drug-like!”? Is this a question of intuition or does it lend itself to a mathematical analysis? Using which tools? Lastly, what can we expect from modelling the biological activity of molecules? The complexity of the living world for the moment evades all attempts of a reductionist analysis from the underlying physicochemical processes. However, the ‘blind’ search for drugs, expecting to come across by chance a molecule that illicits the ‘right’ effect in vivo – too expensive, too slow and ethically questionable as it involves many animal tests – is nowadays no longer an option.

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References

  1. AJAY A., WALTERS W.P., MURCKO M.A. (1998) Can we learn to distinguish between drug-like and non-drug-like molecules? J. Med. Chem. 41: 3314-3324CrossRefGoogle Scholar
  2. GINI G., LORENZINI H., BENFENATI E., GRASSO P., BRUSCHI M. (1999) Predictive carcinogenicity: a model for aromatic compounds, with nitrogen-containing substituants, based on molecular descriptors using an artificial neural network. J. Chem. Inf. Comput. Sci. 39: 1076-1080Google Scholar
  3. BREIMAN L., FRIEDMAN J.H., OHLSEN R.A., STONE C.J. (1984) Classification and Regression Trees. Wadsworth, New York, U.S.A.Google Scholar
  4. GOLBRAIKH A., TROPSHA A. (2002) Beware of q2! J. Mol. Graph. Model. 20: 269-276CrossRefGoogle Scholar
  5. GOLBRAIKH A., SHEN M., XIAO Z., XIAO Y.D., LEE K.H., TROPSHA A. (2003) Rational selection of training and test sets for the development of validated QSAR models. J. Comput. Aided Mol. Des. 17: 241-253CrossRefGoogle Scholar
  6. HANSCH C., LEO A. (1995) Exploring QSAR Fundamentals and applications in chemistry and biology. American Chemical Society, Washington DC, U.S.A.Google Scholar
  7. HANSCH C., LEO A., MEKAPATI S.B., KURUP A. (2004) QSAR and ADME. Bioorg. Med. Chem. 12: 3391-3400CrossRefGoogle Scholar
  8. HORTON D.A., BOURNE G.T., SMYTHE M.L. (2003) The combinatorial synthesis of bicyclic privileged structures or privileged substructures. Chem. Rev. 103: 893-930CrossRefGoogle Scholar
  9. HORVATH D. (2001a) High throughput conformational sampling and fuzzy similarity metrics: a novel approach to similarity searching and focused combinatorial library design and its role in the drug discovery laboratory. In Combinatorial library design and evaluation: principles, software tools and applications (GHOSE A., VISWANADHAN V. Eds) Marcel Dekker, Inc., New York: 429-472Google Scholar
  10. HORVATH D. (2001b) ComPharm – automated comparative analysis of pharmacophoric patterns and derived QSAR approaches, novel tools. In High throughput drug discovery. A proof of concept study applied to farnesyl protein transferase inhibitor design, in QSPR/QSAR studies by molecular descriptors (DIUDEA M. Ed.) Nova Science Publishers, Inc., New York: 395-439Google Scholar
  11. HORVATH D., JEANDENANS C. (2003) Neighborhood behavior of in silico structural spaces with respect to in vitro activity spaces – A novel understanding of the molecular similarity principle in the context of multiple receptor binding profiles. J. Chem. Inf. Comput. Sci. 43: 680-690Google Scholar
  12. HORVATH D., JEANDENANS C. (2003) Neighborhood behavior of in silico structural spaces with respect to in vitro activity spaces – A benchmark for neighborhood behavior assessment of different in silico similarity metrics. J. Chem. Inf. Comput. Sci. 43: 691-698Google Scholar
  13. HORVATH D., MAO B., GOZALBES R., BARBOSA F., ROGALSKI S.L. (2005) Pharmacophore-based virtual screening: strengths and limitations of the computational exploitation of the pharmacophore concept. In Chemoinformatics in drug discovery (OPREA T. Ed.) Wiley, New York, U.S.A.Google Scholar
  14. LIPINSKI C.A., LOMBARDO F., DOMINY, B.W., FEENEY, P.J. (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development setting. Adv. Drug Deliv. Rev. 46: 3-26CrossRefGoogle Scholar
  15. OPREA T.I., GOTTFRIES, J. (2001) Chemography: The art of navigating in chemical space. J. Comb. Chem. 3: 157-166CrossRefGoogle Scholar
  16. PATTERSON D.E., CRAMER R.D., FERGUSON A.M., CLARK R.D., WEINBERGER L.E. (1996) Neighborhood behavior: a useful concept for validation of molecular diversity descriptors. J. Med. Chem. 39: 3049-3059CrossRefGoogle Scholar
  17. PICKETT S.D., MASON J.S., MCLAY I.M. (1996) Diversity profiling and design using 3D pharmacophores: pharmacophore-derived queries. J. Chem. Inf. Comput. Sci. 36: 1214-1223Google Scholar
  18. POULAIN R., HORVATH D., BONNET B., ECKHOFF C., CHAPELAIN B., BODINIER M.C., DEPREZ B. (2001) From hit to lead. Analyzing structure-profile relationships. J. Med. Chem. 44: 3391-3401CrossRefGoogle Scholar
  19. ROLLAND C., GOZALBES R., NICOLAÏ E., PAUGAM M.F., COUSSY L., HORVATH D., BARBOSA F., REVAH F., FROLOFF N. (2004) Qsar strategy for the development of a Gpcr focused library, synthesis and experimental validation. In Proceeding of the EuroQSAR 2004, Istanbul, TurkeyGoogle Scholar
  20. SADOWSKI J., KUBINYI H. (1998) A scoring scheme for discriminating between drugs and non-drugs. J. Med. Chem. 41: 3325-3329CrossRefGoogle Scholar
  21. WILLETT P., BARNARD J.M., DOWNS G.M. (1998) Chemical similarity searching. J. Chem. Inf. Comput. Sci. 38: 983-996Google Scholar
  22. WOLD H. (1985) Partial least squares. In Encyclopedia of Statistical Sciences (KOTZ S., JOHNSON N.L. Eds) Wiley, New York, U.S.A., Vol. 6: 581-591Google Scholar
  23. XU J., HAGLER A. (2002) Chemoinformatics and drug discovery. Molecules 7: 566-600CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dragos Horvath
    • 1
  1. 1.Institute of ChemistryUMR 7177 CNRS - Strasbourg UniversityStrasbourgFrance

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