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Stochastic simulations of cargo transport by processive molecular motors

机译:用过程分子电动机进行货物运输的随机模拟

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摘要

We use stochastic computer simulations to study the transport of a spherical cargo particle along a microtubule-like track on a planar substrate by several kinesin-like processive motors. Our newly developed adhesive motor dynamics algorithm combines the numerical integration of a Langevin equation for the motion of a sphere with kinetic rules for the molecular motors. The Langevin part includes diffusive motion, the action of the pulling motors, and hydrodynamic interactions between sphere and wall. The kinetic rules for the motors include binding to and unbinding from the filament as well as active motor steps. We find that the simulated mean transport length increases exponentially with the number of bound motors, in good agreement with earlier results. The number of motors in binding range to the motor track fluctuates in time with a Poissonian distribution, both for springs and cables being used as models for the linker mechanics. Cooperativity in the sense of equal load sharing only occurs for high values for viscosity and attachment time.
机译:我们使用随机计算机模拟来研究通过几种驱动蛋白样过程性电机沿着球形微颗粒状轨迹在平面基板上的球形货物颗粒的运输。我们新开发的粘性电动机动力学算法将球运动的Langevin方程的数值积分与分子电动机的动力学规则结合在一起。 Langevin部分包括扩散运动,牵引电动机的作用以及球体与壁之间的流体动力相互作用。电机的动力学规则包括与灯丝绑定和解开以及有源电机步骤。我们发现,模拟的平均运输长度随绑定电机的数量呈指数增长,与早期结果很好地吻合。在弹簧范围内,与弹簧连接的马达数量随泊松分布的变化而波动,弹簧和电缆均用作连接器机构的模型。就均等的负载分配而言,协作性仅在粘度和附着时间较高的情况下才会发生。

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