Analysis of large-amplitude conformational transition dynamics in proteins at the single-molecule level

By monitoring the processes of individual, immobilized molecules in real time, it is possible to capture transient and stochastic events that cannot be detected using conventional ensemble-averaged methods. Such rare events on the molecular level are believed to have significant consequences in biological functions. The single-molecule approach therefore offers promising new routes to uncovering the physical and chemical transformations underlying cellular responses. Dynamics and distribution are two unique pieces of information provided by time-dependent single-molecule spectroscopy. However, to extract these pieces of information from the noisy single-molecule time series in an unbiased way is very challenging because single-molecule signals are qualitatively different from ensemble-averaged experiments. With an overarching goal of formulating a predictive understanding of protein molecular machines, this chapter outlines a framework that affords a quantitative and objective analysis of single-molecule signals, with an emphasis on Förster-type energy transfer. Both computer simulations and experimental results are used to illustrate the ideas and practical protocols.