Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
J Phys Condens Matter. 2011 Sep 21;23(37):374106. doi: 10.1088/0953-8984/23/37/374106. Epub 2011 Aug 23.
Molecular motors convert chemical energy into mechanical motion and power the transport of material within living cells; the motion of a motor is thought to be influenced by stochastic chemical state transitions of the molecule as well as intramolecular diffusion of one motor head seeking the next binding site. Existing models for the motility of single-headed monomeric motors that map the system to a simplified two-state Brownian ratchet have some predictive power, but in general are unable to elucidate the contributions of different molecular level processes to the overall effective parameters. In this work, we build a detailed molecular level model of monomeric kinesin motility that naturally incorporates conformational changes (power strokes) and biased diffusion. Our results predict that mean velocity is most sensitive to the power stroke size, while run length distribution is sensitive primarily to the strength of the microtubule bias potential with a weak dependence on power stroke that can be tuned by the strength of an applied load. In addition, we demonstrate that motor pairs attached to the same cargo can cooperatively function to increase motility in both the plus- and minus-end directions. These findings illustrate the importance of a detailed mechanochemical model for dissecting the contributions of microscopic parameters to monomeric kinesin dynamics.
分子马达将化学能转化为机械运动，并为细胞内物质的运输提供动力；据认为，马达的运动受到分子随机化学状态转变以及一个马达头的分子内扩散的影响，后者正在寻找下一个结合位点。将系统映射到简化的双态布朗棘轮的单头单体马达的运动现有模型具有一定的预测能力，但总体上无法阐明不同分子水平过程对整体有效参数的贡献。在这项工作中，我们构建了单体肌球蛋白运动的详细分子水平模型，该模型自然地包含构象变化（动力冲程）和有偏扩散。我们的结果表明，平均速度对动力冲程的大小最敏感，而运行长度分布主要对微管偏置势的强度敏感，对动力冲程的依赖性较弱，可以通过施加负载的强度进行调节。此外，我们证明附着在同一货物上的马达对可以协同作用，以增加正向和负向的运动能力。这些发现说明了详细的机械化学模型对于剖析微观参数对单体肌球蛋白动力学的贡献的重要性。
