Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs

BMC Bioinformatics

Research Article

Leslie Regad¹  Anne-Claude Camproux¹  Juliette Martin² 

[1] INSERM, U973, F-75013, Paris, France;Université Paris 7 - Paris Diderot,UMR-S973, MTi, F-75013, Paris, France;Université Lyon 1, Univ Lyon, France;Université Lyon 1, Univ Lyon, France;

关键词: Structural Motif;    Functional Site;    Structural Word;    Regular Secondary Structure;    Deterministic Finite Automaton;   

DOI  :  10.1186/1471-2105-12-247

 received in 2010-10-07, accepted in 2011-06-20,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundOne of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function.ResultsHere, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet), which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i) ubiquitous motifs, shared by several superfamilies and (ii) superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P) and SAH/SAM.ConclusionsOur findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins.

【 授权许可】

Unknown   
© Regad et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.