<p>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&#xa0;—&#xa0;power consumption, output, and efficiency&#xa0;—&#xa0;remains unclear. We develop an analytical model relating myosin unbinding, quantified by a dimensionless parameter <i>α</i>, to energetics. Our model agrees with published in-vivo muscle data and reveals a performance-efficiency tradeoff governed by <i>α</i>. To experimentally validate this tradeoff, we build HillBot, a robophysical Hill muscle model that mimics nonlinearity and decouples <i>α</i>’s concurrent effects on performance and efficiency, demonstrating that nonlinearity sensitively drives efficiency. We analyze 136 published <i>α</i> measurements from in-vivo muscle samples and find a distribution centered at <i>α</i>*&#xa0;=&#xa0;3.85&#xa0;±&#xa0;2.32. Importantly, both our analytical model and HillBot&#xa0;—&#xa0;despite operating under entirely different mechanisms&#xa0;—&#xa0;converge on the finding that this value <i>α</i>* 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.</p>

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Microscale velocity-dependent unbinding generates a macroscale performance-efficiency tradeoff in actomyosin systems

  • Jake McGrath,
  • Brian Kent,
  • Colin L. Johnson,
  • José Alvarado

摘要

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.