Three-color single-molecule maximum likelihood analysis of folding and binding of diffusing molecules.

Area of Science:

• Biophysics
• Chemical Physics
• Molecular Biology

Background:

• Single-molecule Förster resonance energy transfer (smFRET) is crucial for studying macromolecular conformational dynamics.
• Three-color smFRET faces challenges due to lower quantum yield of the third dye, causing biased burst detection and inaccurate kinetic parameter estimation.
• Existing methods often fail to account for burst selection bias and background noise in three-color smFRET.

Purpose of the Study:

• To present an advanced maximum likelihood method for analyzing three-color smFRET data from freely diffusing molecules.
• To rigorously address burst selection criteria and background noise in three-color smFRET analysis.
• To accurately determine molecular properties and dynamics, especially for states with unequal brightness or high noise.

Main Methods:

• Extension of the two-color maximum likelihood method (burstML) to three-color smFRET data analysis.
• Rigorous accounting for burst selection criteria and background noise in confocal microscopy data.
• Analysis of both experimental and simulated fluorescence burst data from freely diffusing molecules.

Main Results:

• Accurate determination of molecular brightness, FRET efficiencies, diffusivity, and state populations.
• Precise estimation of transition rates between different molecular states.
• Demonstration of superior performance over conventional methods, particularly for challenging datasets.

Conclusions:

• The enhanced burstML method accurately analyzes three-color smFRET data, overcoming limitations of previous approaches.
• This method is vital for studying molecular states with unequal brightness and in high background noise conditions.
• The developed method enables reliable characterization of conformational dynamics in single-molecule free diffusion experiments.