Bioinformatics 20(10) © Oxford University Press 2004; all rights reserved.
GCB Conference Paper |
Efficient similarity search in protein structure databases by k-clique hashing
1 Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Straße, 35032 Marburg, Germany and 2 Institute of Pharmaceutical Chemistry, University of Marburg, Marbacher Weg 6, 35032 Marburg, Germany
Received on October 12, 2003; accepted on February 3, 2004
Motivation: Graph-based clique-detection techniques are widely used for the recognition of common substructures in proteins. They permit the detection of resemblances that are independent of sequence or fold homologies and are also able to handle conformational flexibility. Their high computational complexity is often a limiting factor and prevents a detailed and fine-grained modeling of the protein structure.
Results: We present an efficient two-step method that significantly speeds up the detection of common substructures, especially when used to screen larger databases. It combines the advantages from both clique-detection and geometric hashing. The method is applied to an established approach for the comparison of protein binding-pockets, and some empirical results are presented.
Availability: Upon request from the authors.
Contact: eyke{at}mathematik.uni-marburg.de
* To whom correspondence should be addressed.
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