Gopich Irina V
Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA.
J Chem Phys. 2015 Jan 21;142(3):034110. doi: 10.1063/1.4904381.
Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when the FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a "chevron" shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated.
来自单分子荧光共振能量转移(FRET)实验的光子序列可以使用最大似然法进行分析。通过最大化适当的似然函数来获得基础动力学模型的参数(状态的FRET效率和构象状态之间的转换速率)。此外,提取参数的误差(不确定性)可以从似然函数在最大值处的曲率获得。我们研究了从具有记录颜色和到达时间的光子序列中获得的两态模型参数的标准差。在状态的FRET效率为0和1的特殊情况下以及在快速和慢速构象动力学的极限情况下,可以通过解析方法获得标准差。将这些结果与数值模拟结果进行比较。预测模型参数的准确性以及相应能力取决于转换速率与光子计数率的比较速度。在慢速转换的极限情况下,决定准确性的关键参数是状态之间的转换次数和独立光子序列的数量。在快速转换极限情况下,准确性由与其相邻光子相关的一小部分光子决定。在对数-对数尺度上,弛豫速率的相对标准差作为转换速率的函数呈“V”形。该函数最小值的位置极大地取决于状态的FRET效率的分离程度。