RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information

• Published in: Nucleic Acids Research 2015-02, Vol.43 (3), p.1370-1379
• Main Authors: Suresh, V, Liu, Liang, Adjeroh, Donald, Zhou, Xiaobo
• Format: Article
• Language: English
• Subjects: Animals; Computational Biology; Nucleic Acid Conformation; Protein Interaction Maps; RNA, Untranslated - chemistry; RNA, Untranslated - metabolism; RNA-Binding Proteins - chemistry; RNA-Binding Proteins - metabolism; Support Vector Machine
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkv020

RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with ∼94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ∼83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA-protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred.