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An Analysis of the Autocorrelation Descriptor for Molecules

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Abstract

We discuss properties of the autocorrelation descriptor, a topological descriptor encoding both molecular structure and physico-chemical properties of a molecule. We introduce two random graph models for molecules and show that this descriptor may exhibit unwanted correlation properties, making the generated data unusable for structure–activity relationship studies. This shortcoming can easily be eliminated by centering properties, facilitating subsequent statistical analysis.

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References

  1. H. Kubinyi, QSAR: Hansch Analysis and Related Approaches (VCH, 1993).

  2. L.B. Kier and L.H. Hall, Molecular Connectivity in Structure Activity Analysis (Wiley, 1986).

  3. N. Trinajstić, Chemical Graph Theory (CRC Press, 1992).

  4. D. Bonchev and D.H. Rouvray (eds.), Chemical Graph Theory, Vols. 1 and 2 (Gordon & Breach, 1991, 1992).

  5. H. Wiener, Structural determination of parrafin boiling points, J. Am. Chem. Soc. 69 (1947) 17–20.

    Google Scholar 

  6. G. Moreau and P. Broto, Autocorrelation of a topological structure: A new molecular descriptor, Nouv. J. Chim. 4 (1980) 359–360.

    Google Scholar 

  7. J. Devillers and D. Domine, Comparison of reliability of log P values calculated from a group contribution approach and from the autocorrelation method, SAR QSAR Environ. Res. 7 (1997) 195–232.

    Google Scholar 

  8. M. Wagener, J. Sadowski and J. Gasteiger, Autocorrelation of molecular properties for modelling corticosteroid binding globulin and cytosolic Ah receptor activity by neural networks, J. Am. Chem. Soc. 117 (1995) 7769–7775.

    Google Scholar 

  9. J. Devillers, Autocorrelation descriptors for modelling (eco)toxicological endpoints, in: Topological Indices and Related Descriptors in QSAR and QSPR, ed. J. Devillers (Gordon & Breach, 1999) pp. 595–612.

  10. H. Bauknecht, A. Zell, H. Bayer, P. Levi, M. Wagener, J. Sadowsky and J. Gasteiger, Locating biologically active compounds in medium-sized heterogeneous datasets by topological autocorrelation vectors: Dopamine and benzodiazepine agonists, J. Chem. Inf. Comput. Sci. 36 (1996) 1205–1213.

    Article  PubMed  Google Scholar 

  11. J. Devillers, D. Domine and R.S. Boethling, Use of a backpropagation neural network and autocorrelation descriptors for predicting the biodegradability of organic chemicals, in: Neural Networks in QSAR and Drug Design, ed. J. Devillers (Academic Press, 1996) pp. 65–82.

  12. http://www.disat.unimib.it/chm/Dragon.htm

  13. B. Bollobas, Random Graphs (Academic Press, 1984).

  14. E.M. Palmer, Graphical Evolution (Wiley, 1985).

  15. B. Hollas, Correlation properties of the autocorrelation descriptor for molecules, Comm. Math. Chem. (MATCH) 45 (2002) 27–33.

    Google Scholar 

  16. J. Köbler, U. Schöning and J. Toran, The Graph Isomorphism Problem: Its Structural Complexity (Birkhäuser Verlag, Boston, 1993).

    Google Scholar 

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Hollas, B. An Analysis of the Autocorrelation Descriptor for Molecules. Journal of Mathematical Chemistry 33, 91–101 (2003). https://doi.org/10.1023/A:1023247831238

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  • DOI: https://doi.org/10.1023/A:1023247831238

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