RNA-protein interactions play a key role in many biological processes such as gene regulation and viral replication. It remains challenging to characterize structures of RNA/protein complexes experimentally, but given abundant sequence information, computational methods can be trained using existing structures to develop algorithms for predicting residues in RNA/protein interfaces. We have therefore developed a web server and a standalone tool, RPIMapPr, which is based on data extracted from 1,484 known structure files of RNA/protein complexes. This tool uses an efficient method for predicting interfacing residues compared to other tools such as PSSM profile and physio-chemical profile tools, while also exceeding or maintaining key statistical metrics of other tools. RPIMapPr uses mean probabilities of interaction for the combinations of groups of residues surrounding a queried residue. Due to being comparable in accuracy and other metrics to current predictive tools, this tool has the potential for substantially accelerating and increasing the utility of sequentially based predictive methods for RNA/protein interactions. RPIMapPr is available for free use and can be downloaded from: http://rpimappr.appspot.com

RPIMapPr: A novel approach to predicting interfacing protein residues in RNA-protein complexes

254th National Meeting (2017)

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