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Bioinformatics Advance Access published online on October 31, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm503
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Moment Invariants as Shape Recognition Technique for Comparing Protein Binding Sites

Ingolf Sommer a,*, Oliver Müller a, Francisco S. Domingues a, Oliver Sander a, Joachim Weickert b and Thomas Lengauer a

aMax-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany, bFaculty of Mathematics and Computer Science, Saarland University, Building E1.1, 66041 Saarbrücken, Germany

*To whom correspondence should be addressed. Dr. Ingolf Sommer E-mail: sommer{at}mpi-inf.mpg.de


  Abstract

Motivation: An approach for identifying similarities of protein-protein binding sites is presented. The geometric shape of a binding site is described by computing a feature vector based on moment invariants. In order to search for similarities, features vectors of binding sites are compared. Similar feature vectors indicate binding sites with similar shapes.

Results: The approach is validated on a representative set of proteinprotein binding sites, extracted from the SCOPPI database. When querying binding sites from a representative set we search for known similarities among 2819 binding sites. A median area under the ROC curve of 0.98 is observed. For half of the queries, a similar binding site is identified among the first two of 2819 when sorting all binding sites according the proposed similarity measure. Typical examples identified by this method are analyzed and discussed. The nitrogenase iron protein-like SCOP family is clustered hierarchically according to the proposed similarity measure as a case study.

Availability: Python code is available on request from the authors.

Contact: sommer{at}mpi-inf.mpg.de

Associate Editor: Prof. Burkhard Rost

Received on July 7, 2007; revised on September 13, 2007; accepted on October 2, 2007

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