Author:
Murthy Vidya,Baker Josh E.
Abstract
ABSTRACTWith implications for both clean energy technologies and human health, models of muscle contraction provide insights into the inner workings of one of the most energy-efficient engines on the planet and into the modifications to that engine that lead to human diseases. However, only scientific methods can provide these insights. A binary mechanical model is a recently developed thermodynamic model of muscle contraction that implies a novel entropic kinetic formalism, provides a solution to a paradox that has perplexed scientists for over a century, and accounts for many mechanical and energetic aspects of muscle contraction. Here we use this model to perform discrete state chemical simulations of isometric force generation under different conditions and show explicitly that force generating kinetics are bounded by thermodynamic equations, that four phases of force generation occur as four separate thermodynamic processes, and that periodic force generation emerges with amplitudes and periodicities that bifurcate between constant and stochastic values through mechanisms easily understood relative to ideal thermodynamic processes. We discuss these results relative to experimental observations of spontaneous oscillatory contractions (SPOCs) in muscle and periodic force generation in small myosin ensembles.Significance StatementMost models of muscle contraction to date are based on the obsolete 17th century scientific philosophy that the force of the system is determined by the force of the molecules in that system. A new thermodynamic model of muscle provides a completely different interpretation of muscle mechanics and chemistry, implies a novel thermodynamic kinetic formalism, and has solved a paradigm that has intrigued scientists for over a century. Here, we use this model to simulate muscle force generation and show that force generating kinetics are constrained by thermodynamic equations that provide a clear mechanism for the periodic force generation that emerges from these stochastic simulations.
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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