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.
Highlights
Aromatic amino acids play a critical role in protein-glycan interactions
Linear discriminant analysis of coplanar aromatic surface motifs To determine whether coplanar aromatic surface motifs like those found in type A and B Carbohydratebinding modules (CBMs) are structural signatures of glycan-binding proteins, linear discriminant analysis (LDA) was applied to a training set of coplanar aromatic motifs occurring in structures of known glycanbinding proteins
Positive cases used in training included 26 pairs of glycan-binding aromatic residues in known type A and B CBM binding sites from 18 different structures (Figure 1)
Summary
Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. Carbohydrate-binding proteins (CBPs) are highly diverse in terms of their sequences, structures, binding sites, and evolutionary histories [1]. Sequence-based classifications (e.g., as used in the CAZy database [2]) are an attempt to organize this diversity, and do so by grouping CBPs into evolutionarily related families and subfamilies Many of these families have a common function and mechanism, while in others functions have diversified [2]. As binding site residues and other functional motifs may be close in 3 D space but be non-contiguous in the amino acid sequence, structural patterns are inherently better at representing proteins functions than primary sequence alone. Structure-based prediction of CBPs with novel folds and binding sites has not been performed and validated experimentally. Given their enormous potential in biotechnological applications [9], computational prediction of novel CBPs is a worthwhile goal
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
