Department of Physics & Astronomy. University of Kansas, Lawrence, Kansas 66045, USA.
J Chem Phys. 2011 Apr 14;134(14):145101. doi: 10.1063/1.3568946.
We introduce a new approach to analyze single-molecule Förster resonance energy transfer (FRET) data. The method recognizes that FRET efficiencies assumed by traditional ensemble methods are unobservable for single molecules. We propose instead a method to predict distributions of FRET parameters obtained directly from the data. Distributions of FRET rates, given the data, are precisely defined using Bayesian methods and increase the information derived from the data. Benchmark comparisons find that the response time of the new method outperforms traditional methods of averaging. Our approach makes no assumption about the number or distribution of underlying FRET states. The new method also yields information about joint parameter distributions going beyond the standard framework of FRET analysis. For example, the running distribution of FRET means contains more information than any conceivable single measure of FRET efficiency. The method is tested against simulated data and then applied to a pilot-study sample of calmodulin molecules immobilized in lipid vesicles, revealing evidence for multiple dynamical states.
我们介绍了一种新的方法来分析单分子Förster 共振能量转移（FRET）数据。该方法认识到传统的整体方法所假设的 FRET 效率对于单分子是不可观察的。我们提出了一种方法来预测直接从数据中获得的 FRET 参数分布。使用贝叶斯方法精确定义了给定数据的 FRET 速率分布，并增加了从数据中得出的信息。基准比较发现，新方法的响应时间优于传统的平均方法。我们的方法对潜在的 FRET 状态的数量或分布没有任何假设。新方法还提供了有关联合参数分布的信息，超出了 FRET 分析的标准框架。例如，FRET 平均值的运行分布包含比任何可想象的单个 FRET 效率测量更多的信息。该方法经过模拟数据的测试，然后应用于固定在脂质小泡中的钙调蛋白分子的初步研究样本，揭示了存在多种动力学状态的证据。
