Identification of hot regions in protein-protein interactions by sequential pattern mining

Background: Identification of protein interacting sites is an important task in computational molecular biology. As more and more protein sequences are deposited without available structural information, it is strongly desirable to predict protein binding regions by their sequences alone. This paper presents a pattern mining approach to tackle this problem. It is observed that a functional region of protein structures usually consists of several peptide segments linked with large wildcard regions. Thus, the proposed mining technology considers large irregular gaps when growing patterns, in order to find the residues that are simultaneously conserved but largely separated on the sequences. A derived pattern is called a cluster-like pattern since the discovered conserved residues are always grouped into several blocks, which each corresponds to a local conserved region on the protein sequence. Results: The experiments conducted in this work demonstrate that the derived long patterns aut...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Chen-Ming Hsu, Chien-Yu Chen, Baw-Jhiune Liu, Chih-Chang Huang, Min-Hung Laio, Chien-Chieh Lin, Tzung-Lin Wu
• Keywords: BMCBI 2007, Computational Molecular Biology, Protein Sequence, Proteins