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

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationCell Signaling Reactions
Subtitle of host publicationSingle-Molecular Kinetic Analysis
PublisherSpringer Netherlands
Number of pages21
ISBN (Print)9789048198634
StatePublished - 2011

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology


  • Conformation distribution
  • Correlation function
  • Cramér-Rao bound
  • Dynamical depolarization
  • Dynamically induced fit
  • Emergence
  • Ergodic
  • Fisher information
  • Förster-Type Resonance Energy Transfer (FRET)
  • Induced fit
  • Local unfolding
  • Maximum Entropy
  • Maximum Likelihood Estimate (MLE)
  • Maximum-information algorithm
  • Molecular machine
  • Orientation factor, (κ)


Dive into the research topics of 'Analysis of large-amplitude conformational transition dynamics in proteins at the single-molecule level'. Together they form a unique fingerprint.

Cite this