Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5dReportar como inadecuado




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BMC Structural Biology

, 10:23

First Online: 03 August 2010Received: 25 April 2010Accepted: 03 August 2010

Abstract

BackgroundAromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank PDB for coplanar aromatic motifs similar to those found in known glycan-binding proteins.

ResultsThe proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology GO enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif W34-W36-W192 in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d-s insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry.

ConclusionsBased on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.

Electronic supplementary materialThe online version of this article doi:10.1186-1472-6807-10-23 contains supplementary material, which is available to authorized users.

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Autor: Andrew C Doxey - Zhenyu Cheng - Barbara A Moffatt - Brendan J McConkey

Fuente: https://link.springer.com/







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