We analyse sequence and structural features of protein-RNA interfaces using RB-147, a non-redundant dataset of protein-RNA complexes extracted from the PDB. We train classifiers using machine learning algorithms to predict protein-RNA interfaces from sequence and structure-derived features of proteins. Our experiments show that Struct-NB, a Naive Bayes classifier that exploits structural features, outperforms its counterparts that use only sequence features to predict protein-RNA binding residues.
['Fadi Towfic', 'Cornelia Caragea', 'David C. Gemperline', 'Drena Dobbs', 'Vasant Honavar']
Struct-NB: predicting protein-RNA binding sites using structural features