A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins.

Area of Science:

• Molecular Biology
• Biochemistry
• Genomics

Background:

• High-throughput methods generate RNA target sets and motifs for RNA-binding proteins (RBPs).
• Quantitative approaches are essential to understand the full scope of RNA-RBP interactions in cellular regulation.

Purpose of the Study:

• To quantitatively measure equilibrium binding of designed RNAs to human Pumilio proteins (PUM1 and PUM2).
• To develop a predictive model for RNA recognition by PUM1 and PUM2.
• To investigate the factors governing RNA-RBP interactions and cellular occupancy.

Main Methods:

• Utilized the RNA-MaP platform to directly measure equilibrium binding affinities for thousands of designed RNAs.
• Constructed a predictive thermodynamic model for RNA recognition by PUM1 and PUM2.
• Applied the model to published in vivo crosslinking data to compare predicted affinities with in vivo occupancies.

Main Results:

• Revealed widespread residue flipping and positional coupling in RNA recognition, challenging linear motif assumptions.
• Demonstrated quantitative agreement between predicted binding affinities and in vivo protein occupancies.
• Identified a thermodynamically driven, continuous Pumilio-binding landscape.

Conclusions:

• Pumilio protein binding to RNA is primarily governed by thermodynamics, forming a continuous landscape.
• RNA structure and kinetic factors like ribosome displacement have minimal impact on Pumilio binding.
• Provides a quantitative framework for understanding RBP behavior and cellular occupancy.