Hwang Wonseok, Lee Il-Buem, Hong Seok-Cheol, Hyeon Changbong
Korea Institute for Advanced Study, Seoul, Republic of Korea.
Department of Physics, Korea University, Seoul, Republic of Korea.
PLoS Comput Biol. 2016 Dec 27;12(12):e1005286. doi: 10.1371/journal.pcbi.1005286. eCollection 2016 Dec.
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.
生物分子的单分子时间轨迹为我们提供了对复杂折叠景观的一瞥，而使用传统的系综测量很难直观地呈现这些景观。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现象，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系统的方法来分析此类数据。在这里，我们报告了一种新的算法——变分贝叶斯双链马尔可夫模型（VB-DCMM），用于分析显示动态无序的单分子时间轨迹。采用VB-DCMM进行的拟议分析使我们能够检测每条轨迹中是否存在动态无序，识别内部状态的数量，并估计内部状态之间的转变速率以及每个内部状态内的构象转变速率。将VB-DCMM算法应用于100 mM - Na+溶液中H-DNA的单分子FRET数据，然后进行数据聚类，我们表明至少需要6条连接4个不同内部状态的动力学路径才能正确解释H-DNA的双链-三链转变。
