dsRBPBind: modeling the effect of RNA secondary structure on double-stranded RNA–protein binding

Author:

Shatoff Elan12ORCID,Bundschuh Ralf1234ORCID

Affiliation:

1. Department of Physics, The Ohio State University, Columbus, OH 43210, USA

2. Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA

3. Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA

4. Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH 43210, USA

Abstract

Abstract Motivation RNA-binding proteins are fundamental to many cellular processes. Double-stranded RNA-binding proteins (dsRBPs) in particular are crucial for RNA interference, mRNA elongation, A-to-I editing, host defense, splicing and a multitude of other important mechanisms. Since dsRBPs require double-stranded RNA to bind, their binding affinity depends on the competition among all possible secondary structures of the target RNA molecule. Here, we introduce a quantitative model that allows calculation of the effective affinity of dsRBPs to any RNA given a principal affinity and the sequence of the RNA, while fully taking into account the entire secondary structure ensemble of the RNA. Results We implement our model within the ViennaRNA folding package while maintaining its O(N3) time complexity. We validate our quantitative model by comparing with experimentally determined binding affinities and stoichiometries for transactivation response element RNA-binding protein (TRBP). We also find that the change in dsRBP binding affinity purely due to the presence of alternative RNA structures can be many orders of magnitude and that the predicted affinity of TRBP for pre-miRNA-like constructs correlates with experimentally measured processing rates. Availability and implementation Our modified version of the ViennaRNA package is available for download at http://bioserv.mps.ohio-state.edu/dsRBPBind, is free to use for research and educational purposes, and utilizes simple get/set methods for footprint size, concentration, cooperativity, principal dissociation constant and overlap.

Funder

National ScienceFoundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. RBPBind: Quantitative Prediction of Protein-RNA Interactions;Journal of Molecular Biology;2022-06

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