论文标题
复杂能量景观中的第一分时间：非肌肉肌球蛋白II组装的案例研究
First-passage times in complex energy landscapes: a case study with nonmuscle myosin II assembly
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Complex energy landscapes often arise in biological systems, e.g. for protein folding, biochemical reactions or intracellular transport processes. Their physical effects are often reflected in the first-passage times arising from these energy landscapes. However, their calculation is notoriously challenging and it is often difficult to identify the most relevant features of a given energy landscape. Here we show how this can be achieved by coarse-graining the Fokker-Planck equation to a master equation and decomposing its first-passage times in an iterative process. We apply this method to the electrostatic interaction between two rods of nonmuscle myosin II (NM2), which is the main molecular motor for force generation in nonmuscle cells. Energy landscapes are computed directly from the amino acid sequences of the three different isoforms. Our approach allows us to identify the most relevant energy barriers for their self-assembly into nonmuscle myosin II minifilaments and how they change under force. In particular, we find that antiparallel configurations are more stable than parallel ones, but also show more changes under mechanical loading. Our work demonstrates the rich dynamics that can be expected for NM2-assemblies under mechanical load and in general shows how one can identify the most relevant energy barriers in complex energy landscapes.
