PRIGSA2: Improved version of Protein Repeat Identification by Graph Spectral Analysis

Abstract

Tandemly repeated structural motifs in proteins form highly stable structural folds and provide multiple binding sites associated with diverse functional roles. The tertiary structure and function of these proteins are determined by the type and copy number of the repeating units. Each repeat type exhibits a unique pattern of intra- and inter-repeat unit interactions that is well-captured by the topological features in the network representation of protein structures. Here we present an improved version of our graph based algorithm, PRIGSA, with structure-based validation and filtering steps incorporated for accurate detection of tandem structural repeats. The algorithm integrates available knowledge on repeat families with de novo prediction to detect repeats in single monomer chains as well as in multimeric protein complexes. Three levels of performance evaluation are presented: comparison with state-of-the-art algorithms on benchmark dataset of repeat and non-repeat proteins, accuracy in the detection of members of 13 known repeat families reported in UniProt and execution on the complete Protein Data Bank to show its ability to identify previously uncharacterized proteins. A [~]3-fold increase in the coverage of the members of 13 known families and 3,408 novel uncharacterized structural repeat proteins are identified on executing it on PDB. URL: http://bioinf.iiit.ac.in/PRIGSA2/.