Computational modeling of RNA-protein binding interactions under an external force

TL;DR

This study uses computational modeling to explore how RNA-protein interactions can be characterized through single molecule force spectroscopy, revealing concentration-dependent responses and structural insights relevant to gene regulation and disease.

Contribution

It introduces a modified ViennaRNA model to simulate RNA-protein interactions under external force, enabling better interpretation of experimental force extension data.

Findings

Protein concentration affects RNA force extension measurements.

Differences in extension are linked to protein binding domain geometry.

Model predicts measurable effects at biologically relevant concentrations.

Abstract

RNA binding proteins play a crucial role in post-transcriptional gene regulation by controlling the transport, processing, and translation of their target RNAs. Post-transcriptional gene regulation leads to the differential expression of genetic material and loss of regulation or over-regulation relates to a large range of cancers and diseases - many of which have directly been associated with RNA binding proteins and their target RNAs. To understand RNA, RNA binding proteins, and how they function in gene expression, it is essential to characterize how RNA binding proteins interact with their target RNAs. Here, we aim to assess the potential for single molecule force spectroscopy experiments to be used in the characterization of RNA-protein binding by investigating to what extent a change of extension due to RNA-protein binding is experimentally measurable and what aspects of the interaction can be deduced from such measurements. We predict the effect of protein binding on RNA force extension measurements via the open-source ViennaRNA package, which we have modified to simultaneously consider an external force, protein binding, and RNA secondary structure. From this work, we see protein concentration-dependent responses to external forces with discernable differences in predicted extensions around biologically relevant concentrations and a connection to protein binding domain geometry for several RNA binding proteins.