A New Method for Determining Structure Ensemble: Application to a RNA Binding Di-Domain Protein.

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• Understanding multidomain protein structure-function relationships requires accurate structure ensemble determination.
• Paramagnetic relaxation enhancement (PRE) is valuable for studying protein dynamics but faces challenges like spin-label flexibility and overfitting.
• Existing methods struggle with complex dynamics and accurate representation of protein ensembles.

Purpose of the Study:

• To develop a novel computational method for determining protein structure ensembles using a minimal number of conformers.
• To address limitations of current methods in handling spin-label flexibility, domain dynamics, and overfitting in PRE studies.
• To provide a robust framework for analyzing weak domain-domain interactions in multidomain proteins.

Main Methods:

• A new method treating individual domains as rigid, defining spin-label and protein conformers by orthogonal parameters.
• Optimization of spin-label ensembles using genetic algorithms against intradomain PRE data.
• Protein structure ensemble optimization via a novel genetic algorithm-based approach with an overfitting indicator.

Main Results:

• The method successfully determined a protein structure ensemble using a minimal set of conformers.
• Validation against a reference ensemble with known conformer populations and structures confirmed method accuracy.
• Application to a poly(U) binding protein revealed an ensemble supported by experimental data (SAXS, NMR).

Conclusions:

• The developed method offers an efficient and accurate approach for multidomain protein structure ensemble determination.
• The determined ensemble for the poly(U) binding protein suggests an induced fit mechanism for RNA recognition.
• This work advances the study of protein dynamics and structure-function relationships, particularly for systems with weak interactions.