Dataset Information

Analysis of the RNA Binding Specificity Landscape of C5 Protein Reveals Structure and Sequence Preferences that Direct RNase P Specificity.

ABSTRACT: RNA binding proteins (RBPs) are typically involved in non-equilibrium cellular processes, and specificity can arise from differences in ground state, transition state, or product states of the binding reactions for alternative RNAs. Here, we use high-throughput methods to measure and analyze the RNA association kinetics and equilibrium binding affinity for all possible sequence combinations in the precursor tRNA binding site of C5, the essential protein subunit of Escherichia coli RNase P. The results show that the RNA sequence specificity of C5 arises due to favorable RNA-protein interactions that stabilize the transition state for association and bound enzyme-substrate complex. Specificity is further impacted by unfavorable RNA structure involving the C5 binding site in the ground state. The results illustrate a comprehensive quantitative approach for analysis of RNA binding specificity, and show how both RNA structure and sequence preferences of an essential protein subunit direct the specificity of a ribonucleoprotein enzyme.

SUBMITTER: Lin HC

PROVIDER: S-EPMC5088717 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Analysis of the RNA Binding Specificity Landscape of C5 Protein Reveals Structure and Sequence Preferences that Direct RNase P Specificity.

Lin Hsuan-Chun HC Zhao Jing J Niland Courtney N CN Tran Brandon B Jankowsky Eckhard E Harris Michael E ME

Cell chemical biology 20160929 10

RNA binding proteins (RBPs) are typically involved in non-equilibrium cellular processes, and specificity can arise from differences in ground state, transition state, or product states of the binding reactions for alternative RNAs. Here, we use high-throughput methods to measure and analyze the RNA association kinetics and equilibrium binding affinity for all possible sequence combinations in the precursor tRNA binding site of C5, the essential protein subunit of Escherichia coli RNase P. The r ...[more]

PMID: 27693057

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Project description:BackgroundCharacterizing the binding preference of RNA-binding proteins (RBP) is essential for us to understand the interaction between an RBP and its RNA targets, and to decipher the mechanism of post-transcriptional regulation. Experimental methods have been used to generate protein-RNA binding data for a number of RBPs in vivo and in vitro. Utilizing the binding data, a couple of computational methods have been developed to detect the RNA sequence or structure preferences of the RBPs. However, the majority of RBPs have not yet been experimentally characterized and lack RNA binding data. For these poorly studied RBPs, the identification of their binding preferences cannot be performed by most existing computational methods because the experimental binding data are prerequisite to these methods.ResultsHere we propose a new method based on co-evolution to predict the sequence preferences for the poorly studied RBPs, waiving the requirement of their binding data. First, we demonstrate the co-evolutionary relationship between RBPs and their RNA partners. We then present a K-nearest neighbors (KNN) based algorithm to infer the sequence preference of an RBP using only the preference information from its homologous RBPs. By benchmarking against several in vitro and in vivo datasets, our proposed method outperforms the existing alternative which uses the closest neighbor's preference on all the datasets. Moreover, it shows comparable performance with two state-of-the-art methods that require the presence of the experimental binding data. Finally, we demonstrate the usage of this method to infer sequence preferences for novel proteins which have no binding preference information available.ConclusionFor a poorly studied RBP, the current methods used to determine its binding preference need experimental data, which is expensive and time consuming. Therefore, determining RBP's preference is not practical in many situations. This study provides an economic solution to infer the sequence preference of such protein based on the co-evolution. The source codes and related datasets are available at https://github.com/syang11/KNN .

Dataset Information

Analysis of the RNA Binding Specificity Landscape of C5 Protein Reveals Structure and Sequence Preferences that Direct RNase P Specificity.

Publications

Analysis of the RNA Binding Specificity Landscape of C5 Protein Reveals Structure and Sequence Preferences that Direct RNase P Specificity.

Similar Datasets

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