Improve the prediction of RNA-binding residues using structural neighbours.
The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence- or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA-binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure),which is available at http://mcgill.3322.org/RNA/.
Li
Quan
Q
School of Life Sciences, Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China (USTC), Hefei, Anhui, 230027, China. jeele@mail.ustc.edu.cn
Cao
Zanxia
Z
Liu
Haiyan
H
D030562:Databases, Protein; D016014:Linear Models; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs / Q000235:genetics*; D040901:Proteomics / Q000379:methods*; D016601:RNA-Binding Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D012372:ROC Curve; D015203:Reproducibility of Results; D020539:Sequence Analysis, Protein / Q000379:methods*
D016601:RNA-Binding Proteins