Rzepiela Andrzej J, Schaudinnus Norbert, Buchenberg Sebastian, Hegger Rainer, Stock Gerhard
Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104 Freiburg, Germany.
Institute of Physical and Theoretical Chemistry, Goethe University, 60438 Frankfurt, Germany.
J Chem Phys. 2014 Dec 28;141(24):241102. doi: 10.1063/1.4904894.
Based on a given time series, the data-driven Langevin equation (dLE) estimates the drift and the diffusion field of the dynamics, which are then employed to reproduce the essential statistical and dynamical features of the original time series. Because the propagation of the dLE requires only local information, the input data are neither required to be Boltzmann weighted nor to be a continuous trajectory. Similar to a Markov state model, the dLE approach therefore holds the promise of predicting the long-time dynamics of a biomolecular system from relatively short trajectories which can be run in parallel. The practical applicability of the approach is shown to be mainly limited by the initial sampling of the system's conformational space obtained from the short trajectories. Adopting extensive molecular dynamics simulations of the unfolding and refolding of a short peptide helix, it is shown that the dLE approach is able to describe microsecond conformational dynamics from a few hundred nanosecond trajectories. In particular, the dLE quantitatively reproduces the free energy landscape and the associated conformational dynamics along the chosen five-dimensional reaction coordinate.
基于给定的时间序列，数据驱动的朗之万方程（dLE）估计动力学的漂移和扩散场，然后利用这些场来重现原始时间序列的基本统计和动力学特征。由于dLE的传播仅需要局部信息，因此输入数据既不需要进行玻尔兹曼加权，也不需要是连续轨迹。因此，与马尔可夫状态模型类似，dLE方法有望从相对较短的轨迹（可以并行运行）预测生物分子系统的长时间动力学。该方法的实际适用性主要受从短轨迹获得的系统构象空间的初始采样限制。通过对短肽螺旋展开和重折叠进行广泛的分子动力学模拟，结果表明dLE方法能够从几百纳秒的轨迹描述微秒级的构象动力学。特别是，dLE定量地重现了自由能景观以及沿所选五维反应坐标的相关构象动力学。
