用动态无序解码单分子时间轨迹
Decoding Single Molecule Time Traces with Dynamic Disorder
摘要：
生物分子的单分子时间轨迹提供了对复杂折叠景观的一瞥，这些景观很难使用传统的系综测量来可视化。最近的实验和理论分析突出了某些类别的生物分子中的动态无序，其构象转变的动态模式受到隐藏在低维投影中的内部状态的较慢转变动力学的影响。然而，目前还没有很好地开发出一种分析这种数据的系统手段。在这里，我们报告了一个新的算法-变分贝叶斯双链马尔可夫模型（VB-DCMM）-分析单分子的时间轨迹，显示动态的混乱。建议的分析采用VB-DCMM使我们能够检测存在的动态障碍，如果有的话，在每个轨迹中，确定内部状态的数量，并估计内部状态之间的转换率以及每个内部状态内的构象转换率。应用VB-DCMM算法对H-DNA在100 mM-Na $^+$溶液中的单分子FRET数据进行聚类分析，结果表明，要正确解释H-DNA的三链体-三链体转换，至少需要6条连接4种不同内部状态的动力学路径.
英文摘要：
Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed. Here we report a new algorithm - Variational Bayes-double chain Markov model (VB-DCMM) - to analyze single molecule time trajectories that display dynamic disorder. The proposed analysis employing VB-DCMM allows us to detect the presence of dynamic disorder, if any, in each trajectory, identify the number of internal states, and estimate transition rates between the internal states as well as the rates of conformational transition within each internal state. Applying VB-DCMM algorithm to single molecule FRET data of H-DNA in 100 mM-Na$^+$ solution, followed by data clustering, we show that at least 6 kinetic paths linking 4 distinct internal states are required to correctly interpret the duplex-triplex transitions of H-DNA.
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