Correlation analysis of enzymatic reaction of a single protein molecule

TL;DR

This paper analyzes the correlation structure of enzymatic reaction times at the single-molecule level, validating a stochastic network model against experimental data and exploring substrate concentration effects.

Contribution

It provides a detailed theoretical and data analysis of a stochastic network model explaining single-molecule enzyme reaction correlations, advancing understanding of enzyme dynamics.

Findings

The stochastic network model explains experimental correlation data.

Correlation of fluorescence intensity aligns with reaction time correlations.

Substrate concentration influences enzymatic reaction correlations.

Abstract

New advances in nano sciences open the door for scientists to study biological processes on a microscopic molecule-by-molecule basis. Recent single-molecule biophysical experiments on enzyme systems, in particular, reveal that enzyme molecules behave fundamentally differently from what classical model predicts. A stochastic network model was previously proposed to explain the experimental discovery. This paper conducts detailed theoretical and data analyses of the stochastic network model, focusing on the correlation structure of the successive reaction times of a single enzyme molecule. We investigate the correlation of experimental fluorescence intensity and the correlation of enzymatic reaction times, and examine the role of substrate concentration in enzymatic reactions. Our study shows that the stochastic network model is capable of explaining the experimental data in depth.