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Identification of related proteins with weak sequence identity using secondary structure information

Pôle BioInformatique Lyonnais, Institut de Biologie et Chimie des Protéines, Centre National de la Recherche Scientifique, UMR 5086, 69 367 Lyon CEDEX 07, France

Reprint requests to: Dr. C. Geourjon, Pôle BioInformatique Lyonnais, IBCP-CNRS UMR 5086, 7 Passage du Vercors, 69 367 Lyon CEDEX 07, France; e-mail c.geourjon{at}ibcp.fr; fax 3304-72722601.

Molecular modeling of proteins is confronted with the problem of finding homologous proteins, especially when few identities remain after the process of molecular evolution. Using even the most recent methods based on sequence identity detection, structural relationships are still difficult to establish with high reliability. As protein structures are more conserved than sequences, we investigated the possibility of using protein secondary structure comparison (observed or predicted structures) to discriminate between related and unrelated proteins sequences in the range of 10%–30% sequence identity. Pairwise comparison of secondary structures have been measured using the structural overlap (Sov) parameter. In this article, we show that if the secondary structures likeness is >50%, most of the pairs are structurally related. Taking into account the secondary structures of proteins that have been detected by BLAST, FASTA, or SSEARCH in the noisy region (with high E value), we show that distantly related protein sequences (even with <20% identity) can be still identified. This strategy can be used to identify three-dimensional templates in homology modeling by finding unexpected related proteins and to select proteins for experimental investigation in a structural genomic approach, as well as for genome annotation.

Keywords: Protein; molecular modeling; sequence; databank; alignment; structure prediction; secondary structure; Web server

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