Title:Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors
Volume: 16
Issue: 6
Author(s): Zhi-Ping Liu and Luonan Chen
Affiliation:
Keywords:
Bioinformatics, Molecular descriptor, Prediction, Protein-RNA interaction, Protein-RNA recognition.
Abstract: Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions
and binding sites between protein and RNA by traditional experiments is still time consuming and labor
costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and
binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the
interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and
drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions
and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus
on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted
and integrated as feature vectors of representing the interaction events and recognition residues. In addition,
the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate
the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural
complementary perspective.
