Multiscale Modeling of Skeletal Muscle Active Contraction in Relation to Mechanochemical Coupling of Molecular Motors†Report as inadecuate




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1

Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xian Jiaotong University, Xian 710049, China

2

Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588-0656, USA



This paper is an extended version of our paper published in the 10th Annual IEEE International Conference on Nano-Micro Engineered and Molecular Systems IEEE NEMS 2015, Xi’an, China, 7–11 April 2015.



These authors contributed equally to this work.





*

Author to whom correspondence should be addressed.



Academic Editors: Wen Jung Li and Ting-Hsuan Chen

Abstract In this work, a mathematical model was developed to relate the mechanochemical characterizations of molecular motors with the macroscopic manifestation of muscle contraction. Non-equilibrium statistical mechanics were used to study the collective behavior of myosin molecular motors in terms of the complex conformation change and multiple chemical states in one working cycle. The stochastic evolution of molecular motor probability density distribution during the contraction of sarcomere was characterized by the Fokker-Planck Equation. Quick muscle contraction was demonstrated by the collective dynamic behavior of myosin motors, the muscle contraction force, and the muscle contraction velocity-force relation. Our results are validated against published experiments, as well as the predictions from the Hill’s model. The quantitative relation between myosin molecular motors and muscle contraction provides a novel way to unravel the mechanism of force generation. View Full-Text

Keywords: muscle contraction; non-equilibrium statistical mechanics; molecular motor; biomechanical model; Fokker-Planck Equation muscle contraction; non-equilibrium statistical mechanics; molecular motor; biomechanical model; Fokker-Planck Equation





Author: Jiangcheng Chen 1,* , Xiaodong Zhang 1,‡, Shengmao Lin 2,‡, He Wang 1,‡ and Linxia Gu 2,‡

Source: http://mdpi.com/



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