title: A Graph Approach to Mining Biological Patterns in the Binding Interfaces.
abstract: Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, we present a graph-mining method for discovering biological patterns in the protein-RNA interfaces. We represented known protein-RNA interfaces using graphs and then discovered graph patterns enriched in the interfaces. Comparison of the discovered graph patterns with UniProt annotations showed that the graph patterns had a significant overlap with residue sites that had been proven crucial for the RNA binding by experimental methods. Using 200 patterns as input features, a support vector machine method was able to classify protein surface patches into RNA-binding sites and non-RNA-binding sites with 84.0% accuracy and 88.9% precision. We built a simple scoring function that calculated the total number of the graph patterns that occurred in a protein-RNA interface. That scoring function was able to discriminate near-native protein-RNA complexes from docking decoys with a performance comparable with that of a state-of-the-art complex scoring function. Our work also revealed possible patterns that might be important for binding affinity.
authors.affiliation: Department of Computer Science, North Dakota State University , Fargo, North Dakota.
authors.forename: Wen
authors.initials: W
authors.lastname: Cheng
authors.affiliation: Department of Computer Science, North Dakota State University , Fargo, North Dakota.
authors.forename: Changhui
authors.initials: C
authors.lastname: Yan
mesh_terms: D020816:Amino Acid Motifs; D000818:Animals; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D057225:Data Mining; D006801:Humans; D062105:Molecular Docking Simulation; D011485:Protein Binding; D011487:Protein Conformation; D054730:Protein Interaction Domains and Motifs; D011506:Proteins / Q000737:chemistry*; D012313:RNA / Q000737:chemistry*; D016601:RNA-Binding Proteins / Q000737:chemistry*; D060388:Support Vector Machine
chemical_list: D011506:Proteins; D016601:RNA-Binding Proteins; D012313:RNA
keywords: binding sites; common subgraphs; graph patterns; protein–RNA interactions; recurrent patterns; scoring functions