Inferring properties of disordered chains from FRET transfer efficiencies.

Area of Science:

• Biophysics
• Polymer Physics
• Single-Molecule Biophysics

Background:

• Förster resonance energy transfer (FRET) is crucial for studying disordered biomolecules.
• Current FRET analysis methods average over distance distributions, making results dependent on chosen models.
• Model suitability can change with environmental conditions, potentially distorting findings.

Purpose of the Study:

• To develop a more accurate and flexible approach for determining ensemble properties from FRET data.
• To overcome limitations of fixed polymer models in FRET analysis.
• To accurately infer structural and dynamic properties of biomolecules under varying conditions.

Main Methods:

• Developed a novel FRET data analysis method allowing the polymer scaling exponent to vary with solution conditions.
• Utilized synthetic FRET data from simulations (30 protein sequences).
• Validated the method with experimental single-molecule FRET data from disordered and denatured proteins.

Main Results:

• The new method accurately infers radii of gyration within 10% of true values.
• Achieved higher accuracy compared to simpler, fixed polymer models.
• Obtained scaling exponents consistent with direct molecular ensemble measurements.

Conclusions:

• The proposed method offers a straightforward and accurate way to determine ensemble properties from FRET data.
• It provides a more reliable understanding of biomolecular dimensions under diverse conditions.
• The approach is generalizable to other ensemble-averaged intramolecular distance measurements.