Repetitive substructures within a protein play an important role in understanding protein folding and stability, biological function, and genome evolution. About 25% of all proteins contain repeat structures for eukaryote species and most of them do not have the resolved structural information yet. Therefore, this study aimed to design a comprehensive system for identifying internal repeats either from a protein sequence or structural information. In this study, we have curated a set of internal repeat units as a benchmark dataset for performing both sequence and structural alignment with respect to the query sequence or structure. Except for the traditional BLAST algorithms on amino acid sequence or the optimal structural superposition approaches on structures, a novel method employing the predicted secondary structure element information for internal repeat identification was proposed. Sequences were firstly transformed into Length Encoded Secondary Structure (LESS) profiles and followed by autocorrelation analyses. From the primary experimental results, the developed Internal Repeat Identification System (IRIS) can successfully identify internal repeats from those known protein structures, and the web system is freely available at http://iris.cs.ntou.edu.tw/.
Proceedings of the Fourth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2010), pp.689-693