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

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

Abstract

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.

Keywords

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

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

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