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  Thermodynamic modeling reveals widespread multivalent binding by RNA-binding proteins

Sohrabi-Jahromi, S., & Söding, J. (2021). Thermodynamic modeling reveals widespread multivalent binding by RNA-binding proteins. Bioinformatics, 37, i308-i316. doi:doi.org/10.1093/bioinformatics/btab300.

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Sohrabi-Jahromi, S.1, Author           
Söding, J1, Author           
Affiliations:
1Research Group of Computational Biology, MPI for Biophysical Chemistry, Max Planck Society, ou_1933286              

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Free keywords: Regulatory and functional genomics
 Abstract: Motivation: Understanding how proteins recognize their RNA targets is essential to elucidate regulatory processes in the cell. Many RNA-binding proteins (RBPs) form complexes or have multiple domains that allow them to bind to
RNA in a multivalent, cooperative manner. They can thereby achieve higher specificity and affinity than proteins with a single RNA-binding domain. However, current approaches to de novo discovery of RNA binding motifs do not take multivalent binding into account.
Results: We present Bipartite Motif Finder (BMF), which is based on a thermodynamic model of RBPs with two co-operatively binding RNA-binding domains. We show that bivalent binding is a common strategy among RBPs, yielding higher affinity and sequence specificity. We furthermore illustrate that the spatial geometry between the binding sites can be learned from bound RNA sequences. These discovered bipartite motifs are consistent with previously
known motifs and binding behaviors. Our results demonstrate the importance of multivalent binding for RNA-binding proteins and highlight the value of bipartite motif models in representing the multivalency of protein-RNA
interactions.

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Language(s): eng - English
 Dates: 2021-07-12
 Publication Status: Issued
 Pages: 9
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: Bioinformatics
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: 9 Volume / Issue: 37 Sequence Number: - Start / End Page: i308 - i316 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991