Automated Discovery of Active Motifs in Three Dimensional Molecules

Document Type

Conference Proceeding

Publication Date

1-1-1997

Abstract

In this paper we present a method for discovering approximately common motifs (also known as active motifs) in three dimensional (3D) molecules. Each node in a molecule is represented by a 3D point in the Euclidean Space and each edge is represented by an undirected line segment connecting two nodes in the molecule. Motifs are rigid substructures which may occur in a molecule after allowing for an arbitrary number of rotations and translations as well as a small number (specified by the user) of node insert/delete operations in the motifs or the molecule. (We call this "approximate occurrence.") The proposed method combines the geometric hashing technique and block detection algorithms for undirected graphs. To demonstrate the utility of our algorithms, we discuss their applications to classifying three families of molecules pertaining to antibacterial sulfa drugs, anti-anxiety agents (benzodiazepines) and antiadrenergic agents (β receptors). Experimental results indicate the good performance of our algorithms and the high quality of the discovered motifs.

Identifier

0002621677 (Scopus)

ISBN

[1577350278, 9781577350279]

Publication Title

Proceedings 3rd International Conference on Knowledge Discovery and Data Mining Kdd 1997

First Page

89

Last Page

95

Grant

9531548

Fund Ref

National Science Foundation

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