Discovering structural motifs using a structural alphabet: application to magnesium-binding sites.

Abstract

BackgroundFor many metalloproteins, sequence motifs characteristic of metal-binding sites have not been found or are so short that they would not be expected to be metal-specific. Striking examples of such metalloproteins are those containing Mg2+, one of the most versatile metal cofactors in cellular biochemistry. Even when Mg2+-proteins share insufficient sequence homology to identify Mg2+-specific sequence motifs, they may still share similarity in the Mg2+-binding site structure. However, no structural motifs characteristic of Mg2+-binding sites have been reported. Thus, our aims are (i) to develop a general method for discovering structural patterns/motifs characteristic of ligand-binding sites, given the 3D protein structures, and (ii) to apply it to Mg2+-proteins sharing <30% sequence identity. Our motif discovery method employs structural alphabet encoding to convert 3D structures to the corresponding 1D structural letter sequences, where the Mg2+-structural motifs are identified as recurring structural patterns.ResultsThe structural alphabet-based motif discovery method has revealed the structural preference of Mg2+-binding sites for certain local/secondary structures: compared to all residues in the Mg2+-proteins, both first and second-shell Mg2+-ligands prefer loops to helices. Even when the Mg2+-proteins share no significant sequence homology, some of them share a similar Mg2+-binding site structure: 4 Mg2+-structural motifs, comprising 21% of the binding sites, were found. In particular, one of the Mg2+-structural motifs found maps to a specific functional group, namely, hydrolases. Furthermore, 2 of the motifs were not found in non metalloproteins or in Ca2+-binding proteins. The structural motifs discovered thus capture some essential biochemical and/or evolutionary properties, and hence may be useful for discovering proteins where Mg2+ plays an important biological role.ConclusionThe structural motif discovery method presented herein is general and can be applied to any set of proteins with known 3D structures. This new method is timely considering the increasing number of structures for proteins with unknown function that are being solved from structural genomics incentives. For such proteins, which share no significant sequence homology to proteins of known function, the presence of a structural motif that maps to a specific protein function in the structure would suggest likely active/binding sites and a particular biological function.