Department of Physics, Graduate School of Science, Kyoto University, Kyoto, Japan.
J Chem Phys. 2011 Apr 7;134(13):135104. doi: 10.1063/1.3574396.
We present an effective method for estimating the motion of proteins from the motion of attached probe particles in single-molecule experiments. The framework naturally incorporates Langevin dynamics to compute the most probable trajectory of the protein. By using a perturbation expansion technique, we achieve computational costs more than 3 orders of magnitude smaller than the conventional gradient descent method without loss of simplicity in the computation algorithm. We present illustrative applications of the method using simple models of single-molecule experiments and confirm that the proposed method yields reasonable and stable estimates of the hidden motion in a highly efficient manner.
我们提出了一种从单分子实验中附着探针粒子的运动来估计蛋白质运动的有效方法。该框架自然地包含了 Langevin 动力学，以计算蛋白质最可能的轨迹。通过使用微扰展开技术，我们实现了计算成本比传统的梯度下降方法小 3 个数量级以上，而计算算法的简单性没有损失。我们使用单分子实验的简单模型展示了该方法的应用实例，并证实了所提出的方法能够以高效的方式合理且稳定地估计隐藏的运动。
