Partner-specific prediction of RNA-binding residues in proteins: A critical assessment |
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Authors: | Yong Jung Yasser EL-Manzalawy Drena Dobbs Vasant G Honavar |
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Institution: | 1. Bioinformatics and Genomics Graduate Program, Pennsylvania State University, University Park, Pennsylvania;2. Artificial Intelligence Research Laboratory, Pennsylvania State University, University Park, Pennsylvania
Clinical and Translational Sciences Institute, Pennsylvania State University, University Park, Pennsylvania
College of Information Sciences and Technology, Pennsylvania State University, Pennsylvania;3. Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa
Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, Iowa |
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Abstract: | RNA-protein interactions play essential roles in regulating gene expression. While some RNA-protein interactions are “specific”, that is, the RNA-binding proteins preferentially bind to particular RNA sequence or structural motifs, others are “non-RNA specific.” Deciphering the protein-RNA recognition code is essential for comprehending the functional implications of these interactions and for developing new therapies for many diseases. Because of the high cost of experimental determination of protein-RNA interfaces, there is a need for computational methods to identify RNA-binding residues in proteins. While most of the existing computational methods for predicting RNA-binding residues in RNA-binding proteins are oblivious to the characteristics of the partner RNA, there is growing interest in methods for partner-specific prediction of RNA binding sites in proteins. In this work, we assess the performance of two recently published partner-specific protein-RNA interface prediction tools, PS-PRIP, and PRIdictor, along with our own new tools. Specifically, we introduce a novel metric, RNA-specificity metric (RSM), for quantifying the RNA-specificity of the RNA binding residues predicted by such tools. Our results show that the RNA-binding residues predicted by previously published methods are oblivious to the characteristics of the putative RNA binding partner. Moreover, when evaluated using partner-agnostic metrics, RNA partner-specific methods are outperformed by the state-of-the-art partner-agnostic methods. We conjecture that either (a) the protein-RNA complexes in PDB are not representative of the protein-RNA interactions in nature, or (b) the current methods for partner-specific prediction of RNA-binding residues in proteins fail to account for the differences in RNA partner-specific versus partner-agnostic protein-RNA interactions, or both. |
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Keywords: | partner-specific protein-RNA binding performance evaluation protein-RNA interactions protein-RNA Interface prediction RNA-specificity metric |
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