title: A new residue-nucleotide propensity potential with structural information considered for discriminating protein-RNA docking decoys.
abstract: Understanding the key factors that influence the preferences of residue-nucleotide interactions in specific protein-RNA interactions has remained a research focus. We propose an effective approach to derive residue-nucleotide propensity potentials through considering both the types of residues and nucleotides, and secondary structure information of proteins and RNAs from the currently largest nonredundant and nonribosomal protein-RNA interaction database. To test the validity of the potentials, we used them to select near-native structures from protein-RNA docking poses. The results show that considering secondary structure information, especially for RNAs, greatly improves the predictive power of pair potentials. The success rate is raised from 50.7 to 65.5% for the top 2000 structures, and the number of cases in which a near-native structure is ranked in top 50 is increased from 7 to 13 out of 17 cases. Furthermore, the exclusion of ribosomes from the database contributes 8.3% to the success rate. In addition, some very interesting findings follow: (i) the protein secondary structure element π-helix is strongly associated with RNA-binding sites; (ii) the nucleotide uracil occurs frequently in the most preferred pairs in which the unpaired and non-Watson-Crick paired uracils are predominant, which is probably significant in evolution. The new residue-nucleotide potentials can be helpful for the progress of protein-RNA docking methods, and for understanding the mechanisms of protein-RNA interactions.
authors.affiliation: College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China. chunhuali@bjut.edu.cn
authors.forename: Chun Hua
authors.initials: CH
authors.lastname: Li
authors.forename: Li Bin
authors.initials: LB
authors.lastname: Cao
authors.forename: Ji Guo
authors.initials: JG
authors.lastname: Su
authors.forename: Yong Xiao
authors.initials: YX
authors.lastname: Yang
authors.forename: Cun Xin
authors.initials: CX
authors.lastname: Wang
mesh_terms: D000596:Amino Acids / Q000737:chemistry*; D001665:Binding Sites; D003198:Computer Simulation; D030562:Databases, Protein; D006860:Hydrogen Bonding; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D011485:Protein Binding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D012313:RNA / Q000737:chemistry*; D016601:RNA-Binding Proteins / Q000737:chemistry*; D012265:Ribonucleotides / Q000737:chemistry*
chemical_list: D000596:Amino Acids; D016601:RNA-Binding Proteins; D012265:Ribonucleotides; D012313:RNA