Title
Moment invariants as shape recognition technique for comparing protein binding sites.
Abstract
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, feature vectors of binding sites are compared. Similar feature vectors indicate binding sites with similar shapes.The approach is validated on a representative set of protein-protein 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.Python code is available on request from the authors.
Year
DOI
Venue
2007
10.1093/bioinformatics/btm503
Bioinformatics
Keywords
Field
DocType
shape recognition technique,feature vector,similar feature vector,known similarity,binding site,representative set,protein binding site,similar binding site,querying binding site,similar shape,moment invariants,proposed similarity measure,roc curve,protein binding,iron
Feature vector,Binding site,Similarity (geometry),Similarity measure,Pattern recognition,Binding protein,Computer science,Sorting,Invariant (mathematics),Geometric shape,Artificial intelligence,Bioinformatics
Journal
Volume
Issue
ISSN
23
23
1367-4811
Citations 
PageRank 
References 
19
0.91
23
Authors
6
Name
Order
Citations
PageRank
Ingolf Sommer122118.10
Oliver Müller2190.91
Francisco S Domingues334018.01
Oliver Sander437222.95
Joachim Weickert55489391.03
Thomas Lengauer63155605.03