title: Predicting RNA-binding sites from the protein structure based on electrostatics, evolution and geometry.
abstract: An RNA-binding protein places a surface helix, beta-ribbon, or loop in an RNA helix groove and/or uses a cavity to accommodate unstacked bases. Hence, our strategy for predicting RNA-binding residues is based on detecting a surface patch and a disparate cleft. These were generated and scored according to the gas-phase electrostatic energy change upon mutating each residue to Asp(-)/Glu(-) and each residue's relative conservation. The method requires as input the protein structure and sufficient homologous sequences to define each residue's relative conservation. It yields as output a priority list of surface patch residues followed by a backup list of surface cleft residues distant from the patch residues for experimental testing of RNA binding. Among the 69 structurally non-homologous proteins tested, 81% possess a RNA-binding site with at least 70% of the maximum number of true positives in randomly generated patches of the same size as the predicted site; only two proteins did not contain any true RNA-binding residues in both predicted regions. Regardless of the protein conformational changes upon RNA-binding, the prediction accuracies based on the RNA-free/bound protein structures were found to be comparable and their binding sites overlapped as long as there are no disordered RNA-binding regions in the free structure that are ordered in the corresponding RNA-bound protein structure.
authors.affiliation: Department of Chemistry, National Tsing Hua University, Hsinchu 300, Taiwan.
authors.forename: Yao Chi
authors.initials: YC
authors.lastname: Chen
authors.forename: Carmay
authors.initials: C
authors.lastname: Lim
mesh_terms: D001665:Binding Sites; D019143:Evolution, Molecular; D008958:Models, Molecular; D009154:Mutation; D011485:Protein Binding; D011487:Protein Conformation; D012313:RNA / Q000737:chemistry / Q000378:metabolism; D016601:RNA-Binding Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D020539:Sequence Analysis, Protein; D055672:Static Electricity
chemical_list: D016601:RNA-Binding Proteins; D012313:RNA