Nguyen Trini, Narayanareddy Babu Janakaloti, Gross Steven P, Miles Christopher E
Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697.
Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697.
bioRxiv. 2023 Nov 10:2023.11.08.563482. doi: 10.1101/2023.11.08.563482.
The self-organization of cells relies on the profound complexity of protein-protein interactions. Challenges in directly observing these events have hindered progress toward understanding their diverse behaviors. One notable example is the interaction between molecular motors and cytoskeletal systems that combine to perform a variety of cellular functions. In this work, we leverage theory and experiments to identify and quantify the rate-limiting mechanism of the initial association between a cargo-bound kinesin motor and a microtubule track. Recent advances in optical tweezers provide binding times for several lengths of kinesin motors trapped at varying distances from a microtubule, empowering the investigation of competing models. We first explore a diffusion-limited model of binding. Through Brownian dynamics simulations and simulation-based inference, we find this simple diffusion model fails to explain the experimental binding times, but an extended model that accounts for the ADP state of the molecular motor agrees closely with the data, even under the scrutiny of penalizing for additional model complexity. We provide quantification of both kinetic rates and biophysical parameters underlying the proposed binding process. Our model suggests that most but not every motor binding event is limited by their ADP state. Lastly, we predict how these association rates can be modulated in distinct ways through variation of environmental concentrations and spatial distances.
细胞的自组织依赖于蛋白质-蛋白质相互作用的高度复杂性。直接观察这些事件所面临的挑战阻碍了我们对其多样行为的理解。一个显著的例子是分子马达与细胞骨架系统之间的相互作用,它们共同执行各种细胞功能。在这项工作中,我们利用理论和实验来识别和量化负载货物的驱动蛋白马达与微管轨道之间初始结合的限速机制。光镊技术的最新进展为被困在距微管不同距离处的几种长度的驱动蛋白马达提供了结合时间,从而有助于对竞争模型进行研究。我们首先探索了一种扩散限制的结合模型。通过布朗动力学模拟和基于模拟的推断,我们发现这个简单的扩散模型无法解释实验结合时间,但一个考虑分子马达ADP状态的扩展模型与数据非常吻合,即使在因额外模型复杂性而受到惩罚的情况下也是如此。我们对所提出的结合过程的动力学速率和生物物理参数进行了量化。我们的模型表明,大多数但并非每一个马达结合事件都受其ADP状态的限制。最后,我们预测了如何通过改变环境浓度和空间距离以不同方式调节这些结合速率。