Model of fluorescence intermittency in single enzymes

Area of Science:

• Single-molecule biophysics
• Statistical mechanics
• Nanoscale systems

Background:

• Fluorescence intermittency is common in nanoscale systems like enzymes and quantum dots.
• Statistical correlations characterize the emitted signal.
• Previous models exist for protein conformational fluctuations.

Purpose of the Study:

• To formulate a one-dimensional model for fluorescence intermittency in enzymes.
• To analyze statistical correlations in emitted signals.
• To predict the behavior of key fluorescence parameters.

Main Methods:

• Developed a model based on protein conformational fluctuations.
• Used a particle-based stochastic model with fractional Gaussian noise.
• Analyzed the time correlation function, interval distribution, and Mandel parameter.

Main Results:

• Model predicts exponential decay at short times and power-law decay at long times for correlation and interval functions.
• Decay exponents depend on noise temporal correlations.
• Mandel parameter indicates super-Poisson statistics (signal bunching).

Conclusions:

• The model provides a theoretical framework for understanding fluorescence intermittency.
• Results align with experimental data from single-molecule enzyme studies.
• The model captures key statistical features of nanoscale signal fluctuations.