Analytical formulas for effective drift, diffusivity, run times, and run lengths are derived for an intracellular transport system consisting of a cargo attached to two cooperative but not identical molecular motors (for example, kinesin-1 and kinesin-2) which can each attach and detach from a microtubule. The dynamics of the motor and cargo in each phase are governed by stochastic differential equations, and the switching rates depend on the spatial configuration of the motor and cargo. This system is analyzed in a limit where the detached motors have faster dynamics than the cargo, which in turn has faster dynamics than the attached motors. The attachment and detachment rates are also taken to be slow relative to the spatial dynamics. Through an application of iterated stochastic averaging to this system, and the use of renewal-reward theory to stitch together the progress within each switching phase, we obtain explicit analytical expressions for the effective drift, diffusivity, and processivity of the motor-cargo system. Our approach accounts in particular for jumps in motor-cargo position that occur during attachment and detachment events, as the cargo tracking variable makes a rapid adjustment due to the averaged fast scales. The asymptotic formulas are in generally good agreement with direct stochastic simulations of the detailed model based on experimental parameters for various pairings of kinesin-1 and kinesin-2 under assisting, hindering, or no load.

有效漂移、扩散率、运行时间和运行长度的分析公式是针对细胞内运输系统得出的，该系统由连接到两个协作但不相同的分子马达（例如，驱动蛋白-1 和驱动蛋白-2）的货物组成，每个分子马达可以连接并与微管分离。每个阶段的电机和货物的动力学由随机微分方程控制，并且切换速率取决于电机和货物的空间配置。该系统在一个限制下进行分析，其中分离的电机比货物具有更快的动态，而货物又比连接的电机具有更快的动态。相对于空间动力学，附着和分离速率也被认为是缓慢的。通过在该系统中应用迭代随机平均，并使用更新奖励理论将每个切换阶段的进展缝合在一起，我们获得了汽车-货物系统的有效漂移、扩散性和过程性的明确解析表达式。我们的方法特别考虑了在附着和分离事件期间发生的汽车货物位置的跳跃，因为货物跟踪变量由于平均快速尺度而进行快速调整。渐近公式总体上与基于驱动蛋白 1 和驱动蛋白 2 各种配对在辅助、阻碍或无负载下的实验参数的详细模型的直接随机模拟非常一致。