A universal model of restricted diffusion for fluorescence correlation spectroscopy.

Area of Science:

• Biophysics
• Materials Science
• Physical Chemistry

Background:

• Fluorescence correlation spectroscopy (FCS) is crucial for studying restricted diffusion.
• Determining the size of structures hindering molecular motion is key.
• Understanding different restricted diffusion models is vital for biophysics and materials science.

Purpose of the Study:

• To evaluate the applicability of the Gaussian approximation in FCS for interpreting non-Gaussian diffusion data.
• To assess the accuracy of fitting confinement size and diffusion coefficients across diverse restricted diffusion models.
• To provide physical insights into the statistical behaviors of restricted diffusion and FCS's discriminative capabilities.

Main Methods:

• Simulations of three distinct restricted diffusion models: diffusion constrained by elastic force, walking confined diffusion, and hop diffusion.
• Analysis of Fluorescence Correlation Spectroscopy (FCS) autocorrelation functions.
• Comparison of data interpretation using Gaussian approximation versus underlying diffusion mechanisms.

Main Results:

• All three models exhibit similar mean square displacements.
• The Gaussian approximation of FCS data provides excellent accuracy in fitting confinement size, even for non-Gaussian diffusion.
• Diffusion coefficients are also estimated with good accuracy using this approach.
• The archetypal model of diffusion constrained by elastic force can reliably interpret FCS data suspected of restricted diffusion.

Conclusions:

• The Gaussian approximation is a robust tool for interpreting FCS data in restricted diffusion scenarios, irrespective of the specific underlying mechanism.
• FCS, interpreted via the Gaussian approximation, can accurately determine structural confinement sizes and diffusion coefficients.
• This study enhances the understanding of restricted diffusion behaviors and the power of FCS in their analysis.