McGrath Jake, Kent Brian, Johnson Colin L, Alvarado José
Center for Nonlinear Dynamics, Department of Physics, University of Texas at Austin, Austin, Texas, USA.
Theory Group, Weinberg Institute, Department of Physics, University of Texas at Austin, Austin, Texas, USA.
Commun Biol. 2025 May 12;8(1):733. doi: 10.1038/s42003-025-08098-5.
Myosin motors are fundamental biological actuators that power diverse mechanical tasks in eukaryotic cells via ATP hydrolysis. Previous work has linked myosin's velocity-dependent detachment rate to macroscopic scale muscle dynamics described by Hill's model, yet its impact on energetic flows - power consumption, output, and efficiency - remains unclear. We develop an analytical model relating myosin unbinding, quantified by a dimensionless parameter α, to energetics. Our model agrees with published in-vivo muscle data and reveals a performance-efficiency tradeoff governed by α. To experimentally validate this tradeoff, we build HillBot, a robophysical Hill muscle model that mimics nonlinearity and decouples α's concurrent effects on performance and efficiency, demonstrating that nonlinearity sensitively drives efficiency. We analyze 136 published α measurements from in-vivo muscle samples and find a distribution centered at α* = 3.85 ± 2.32. Importantly, both our analytical model and HillBot - despite operating under entirely different mechanisms - converge on the finding that this value α* of nonlinearity observed in muscle corresponds to generalist actuators that balance power and efficiency. These insights inform a nonlinear variable-impedance protocol that directly shifts along a performance-efficiency axis, which could be implemented in robotics applications.
肌球蛋白马达是基本的生物致动器，通过ATP水解为真核细胞中的各种机械任务提供动力。先前的研究工作已将肌球蛋白的速度依赖性脱离速率与希尔模型描述的宏观尺度肌肉动力学联系起来，但其对能量流——功耗、输出和效率——的影响仍不清楚。我们开发了一个分析模型，将以无量纲参数α量化的肌球蛋白解离与能量学联系起来。我们的模型与已发表的体内肌肉数据一致，并揭示了由α控制的性能-效率权衡。为了通过实验验证这种权衡，我们构建了HillBot，这是一个模拟非线性并解耦α对性能和效率的并发影响的机器人物理希尔肌肉模型，证明非线性敏感地驱动效率。我们分析了136个已发表的来自体内肌肉样本的α测量值，发现分布集中在α* = 3.85 ± 2.32。重要的是，我们的分析模型和HillBot——尽管在完全不同的机制下运行——都得出了这样的结论：在肌肉中观察到的这个非线性值α*对应于平衡功率和效率的通用致动器。这些见解为一种直接沿性能-效率轴移动的非线性可变阻抗协议提供了信息，该协议可在机器人应用中实现。
