Extracting the Underlying Unique Reaction Scheme from a Single-Molecule Time Series

Abstract

Single molecule spectroscopy provides us with a new means to look deeply into the question of how an individual molecule behaves when performing biological functions in a thermally fluctuating environment. However, what information one can extract from the observed data is still an open question. We overview our new method which extracts the underlying reaction scheme, a state-space network (SSN), from the time series data of an experimental measurement. We demand that a time series analysis should provide not only an interpretation of the dynamical behavior but also provide new insights into biological functions buried in ensemble-based measurements. Our method is based on the combination of information theory and Wavelet multiresolution decomposition analysis. The resultant reaction scheme does not rely on an a priori ansatz like local equilibrium and detailed balance. It is mathematically assured as unique, minimally complex and stochastic, but best predictive. We demonstrate the potential of this method by applying it to the analysis of an anomalous conformation in Flavin oxidoreductase dependent on the timescale of observation. We also discuss future perspectives concerning its use as a new means for the exploration of single molecule biophysics.