Multiple Semi-flexible 3D Superposition of Drug-Sized Molecules

  • Daniel Baum
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3695)


A new algorithm for multiple semi-flexible superpositioning of drug-sized molecules is described. It identifies structural similarities between two or more molecules. To account for the flexibility of a molecule, multiple conformers drawn from molecular ensembles generated by conformational analysis are used. To address the varying degree of similarity among the molecules, similar substructures present in different subsets of the molecules are identified.

All molecules are compared to a preselected reference molecule. Clique detection on the correspondence graph of two molecular structures is applied to generate feasible start transformations, which are used to compute common substructures. The results of these pairwise comparisons are efficiently merged using binary matching trees.

Despite considering the full atomic information for identifying multiple structural similarities, the algorithm is well suited as an interactive tool for exploring drug-sized molecules, and has been integrated into the molecular visualization package AmiraMol. The algorithm’s capabilities are demonstrated on two sets of molecules.


Reference Molecule Start Transformation Match Tree Common Substructure Matching Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    McMartin, C., Bohacek, R.: Flexible matching of test ligands to a 3d pharmacophore using a molecular superposition force field. J. Comput. Aid. Mol. Des. 9, 237–250 (1995)CrossRefGoogle Scholar
  2. 2.
    Jones, G., Willett, P., Glen, R.C.: A genetic algorithm for flexible molecular overlay and pharmacophore elucidation. J. Comput. Aid. Mol. Des. 9, 532–549 (1995)CrossRefGoogle Scholar
  3. 3.
    Lemmen, C., Lengauer, T.: FLEXS: a method for fast flexible ligand superposition. J. Comp. Chem. 41, 4502–4520 (1998)Google Scholar
  4. 4.
    Handschuh, S., Wagener, M., Gasteiger, J.: Superposition of three-dimensional chemical structures allowing for conformational flexibility by a hybrid method. J. Chem. Inf. Comp. Sci. 38, 220–232 (1998)Google Scholar
  5. 5.
    Good, A.C., Hodgkin, E.E., Richards, W.G.: Utilization of Gaussian functions for the rapid evaluation of molecular similarity. J. Chem. Inf. Comp. Sci. 32, 188–191 (1992)Google Scholar
  6. 6.
    Grant, J.A., Gallardo, M.A., Pickup, B.T.: A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape. J. Comp. Chem. 17, 1653–1666 (1996)CrossRefGoogle Scholar
  7. 7.
    Lemmen, C., Hiller, C., Lengauer, T.: RigFit: A new approach to superimposing ligand molecules. J. Comput. Aid. Mol. Des. 12, 491–502 (1998)CrossRefGoogle Scholar
  8. 8.
    Cosgrove, D., Bayada, D.M., Johnson, A.P.: A novel method of aligning molecules by local surface shape similarity. J. Comput. Aid. Mol. Des. 14, 573–591 (2000)CrossRefGoogle Scholar
  9. 9.
    Hofbauer, C.: Molecular Surface Comparison. A Versatile Drug Discovery Tool. PhD thesis, Technische Universität Wien (2004)Google Scholar
  10. 10.
    Brint, A.T., Willett, P.: Algorithms for the identification of three-dimensional maximal common substructures. J. Chem. Inf. Comp. Sci. 27, 152–158 (1987)Google Scholar
  11. 11.
    Martin, Y.C., Bures, M.G., Willett, P.: Searching databases of three-dimensional structures. In: Lipkowitz, K.B. (ed.) Reviews in Computational Chemistry, vol. 1, pp. 213–263. Elsevier Science Publishers B.V., Amsterdam (1990)CrossRefGoogle Scholar
  12. 12.
    Lemmen, C., Lengauer, T.: Computational methods for the structural alignment of molecules. J. Comput. Aid. Mol. Des. 14, 215–232 (2000)CrossRefGoogle Scholar
  13. 13.
    Martin, Y.C., Bures, M.G., Danaher, E., DeLazzer, J., Lico, I.: A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists. J. Comput. Aid. Mol. Des. 7, 83–102 (1993)CrossRefGoogle Scholar
  14. 14.
    Kirchner, S.: Ein Approximationsalgorithmus zur Berechnung der Ähnlichkeit dreidimensionaler Punktmengen. Diploma Thesis, Department of Computer Science, Humboldt University Berlin (2003)Google Scholar
  15. 15.
    Bron, C., Kerbosch, J.: Algorithm 457: Finding all cliques of an undirected graph. Communications of the ACM 16, 575–577 (1973)zbMATHCrossRefGoogle Scholar
  16. 16.
    Kabsch, W.: A discussion of the solution for the best rotation to relate two sets of vectors. Acta Crystallographica A 34, 827–828 (1978)CrossRefGoogle Scholar
  17. 17.
    Thimm, M., Goede, A., Hougardy, S., Preissner, R.: Comparison of 2d similarity and 3d superposition. Application to searching a conformational drug database. J. Chem. Inf. Comp. Sci. 44, 1816–1822 (2004)Google Scholar
  18. 18.
    Veldhuizen, D.A.V.: Multiobjective Evolutionary Algorithms: Classification, Analyses, and New Innovations. PhD thesis (1999)Google Scholar
  19. 19.
    Fischer, A., Schütte, C., Deuflhard, P., Cordes, F.: Hierarchical uncoupling-coupling of metastable conformations. LNCSE Series, vol. 24, pp. 235–259. Springer, Berlin (2002) Google Scholar
  20. 20.
    Berman, H., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T., Weissig, H., Shindyalov, I., Bourne, P.: The Protein Data Bank. Nucleic Acids Res. 28, 235–242 (2000)CrossRefGoogle Scholar
  21. 21.
    AmiraMol – User’s Guide and Reference Manual. Zuse Institute Berlin (ZIB) and Indeed - Visual Concepts GmbH, Berlin (2002),
  22. 22.
    Wexler, R.R., Greenlee, W.J., Irvin, J.D., Goldberg, M.R., Prendergast, K., Smith, R.D., Timmermans, P.B.M.W.M.: Nonpeptide Angiotensin II Receptor Antagonists. J. Comp. Chem. 39, 625–656 (1996)Google Scholar
  23. 23.
    Sadowski, J., Gasteiger, J.: From Atoms and Bonds to Three-Dimensional Atomic Coordinates: Automatic Model Builders. Chemical Reviews, 2567–2581 (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Daniel Baum
    • 1
  1. 1.Zuse Institute Berlin (ZIB)Germany

Personalised recommendations