标题： 分子马达的离散步长在力的作用下导致双峰非高斯速度分布 显示英文标题

标题： Discrete step sizes of molecular motors lead to bimodal non-Gaussian velocity distributions under force

摘要： 生物机器的物理性质的波动与其功能密不可分。 过程性分子马达（如kinesin-1）的运行长度和速度分布可以通过单分子技术获得，但迄今为止尚缺乏对这些概率的严格理论模型。 我们推导出一个动力学模型的精确解析结果，以预测通用有限过程性分子马达在轨道上前进和后退步态时的抗力（$F$）依赖速度（$P(v)$）和运行长度（$P(n)$）分布函数。 我们的理论通过仅使用解离率作为参数，定量解释了kinesin-1在零力下的数据，适用于$P(n)$和$P(v)$，从而允许我们获得这些量在负载下的变化。 在非零$F$处，$P(v)$是非高斯的，并且是双峰的，在$v$的正负值处有峰值。 预测$P(v)$是双峰的是由于动力蛋白-1的离散步长，即使考虑步长分布时这一结论仍然成立。 尽管这些预测是基于对动力蛋白-1数据的分析，但我们的结果是普遍的，应适用于任何通过采取离散步长在轨道上行走的过程性马达。 显示英文摘要

摘要： Fluctuations in the physical properties of biological machines are inextricably linked to their functions. Distributions of run-lengths and velocities of processive molecular motors, like kinesin-1, are accessible through single molecule techniques, yet there is lack a rigorous theoretical model for these probabilities up to now. We derive exact analytic results for a kinetic model to predict the resistive force ($F$) dependent velocity ($P(v)$) and run-length ($P(n)$) distribution functions of generic finitely processive molecular motors that take forward and backward steps on a track. Our theory quantitatively explains the zero force kinesin-1 data for both $P(n)$ and $P(v)$ using the detachment rate as the only parameter, thus allowing us to obtain the variations of these quantities under load. At non-zero $F$, $P(v)$ is non-Gaussian, and is bimodal with peaks at positive and negative values of $v$. The prediction that $P(v)$ is bimodal is a consequence of the discrete step-size of kinesin-1, and remains even when the step-size distribution is taken into account. Although the predictions are based on analyses of kinesin-1 data, our results are general and should hold for any processive motor, which walks on a track by taking discrete steps.