RNA-binding residues in sequence space: Conservation and interaction patterns

Abstract

RNA-binding proteins (RBPs) perform fundamental and diverse functions within the cell. Approximately 15% of proteins sequences are annotated as RNA-binding, but with a significant number of proteins without functional annotation, many RBPs are yet to be identified. A percentage of uncharacterised proteins can be annotated by transferring functional information from proteins sharing significant sequence homology. However, genomes contain a significant number of orphan open reading frames (ORFs) that do not share significant sequence similarity to other ORFs, but correspond to functional proteins. Hence methods for protein function annotation that go beyond sequence homology are essential. One method of annotation is the identification of ligands that bind to proteins, through the characterisation of binding site residues. In the current work RNA-binding residues (RBRs) are characterised in terms of their evolutionary conservation and the patterns they form in sequence space. The potential for such characteristics to be used to identify RBPs from sequence is then evaluated. In the current work the conservation of residues in 261 RBPs is compared for (a) RBRs vs. non-RBRs surface residues, and for (b) specific and non-specific RBRs. The analysis shows that RBRs are more conserved than other surface residues, and RBRs hydrogen-bonded to the RNA backbone are more conserved than those making hydrogen bonds to RNA bases. This observed conservation of RBRs was then used to inform the construction of RBR sequence patterns from known protein–RNA structures. A series of RBR patterns were generated for a case study protein aspartyl-tRNA synthetase bound to tRNA; and used to differentiate between RNA-binding and non-RNA-binding protein sequences. Six sequence patterns performed with high precision values of >80% and recall values 7 times that of an homology search. When the method was expanded to the complete dataset of 261 proteins, many patterns were of poor predictive value, as they had not been manipulated on a family-specific basis. However, two patterns with precision values ≥85% were used to make function predictions for a set of hypothetical proteins. This revealed a number of potential RBPs that require experimental verification.