Literature DB >> 16935957

Mathematical simulation of muscle cross-bridge cycle and force-velocity relationship.

Leslie Chin1, Pengtao Yue, James J Feng, Chun Y Seow.   

Abstract

Muscle contraction underlies many essential functions such as breathing, heart beating, locomotion, regulation of blood pressure, and airway resistance. Active shortening of muscle is the result of cycling of myosin cross-bridges that leads to sliding of myosin filaments relative to actin filaments. In this study, we have developed a computer program that allows us to alter the rates of transitions between any cross-bridge-states in a stochastic cycle. The cross-bridge states within the cycle are divided into six attached (between myosin cross-bridges and actin filaments) states and one detached state. The population of cross-bridges in each of the states is determined by the transition rates throughout the cycle; differential equations describing the transitions are set up as a cyclic matrix. A method for rapidly obtaining steady-state exact solutions for the cyclic matrix has been developed to reduce computation time and avoid the divergence problem associated with numerical solutions. In the seven-state model, two power strokes are assumed for each cross-bridge cycle, one before the release of inorganic phosphate, and one after. The characteristic hyperbolic force-velocity relationship observed in muscle contraction can be reproduced by the model. Deviation from the single hyperbolic behavior at low velocities can be mimicked by allowing the rate of cross-bridge-attachment to vary with velocity. The effects of [ATP], [ADP], and [P(i)] are simulated by changing transition rates between specific states. The model has revealed new insights on how the force-velocity characteristics are related to the state transitions in the cross-bridge cycle.

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Year:  2006        PMID: 16935957      PMCID: PMC1630484          DOI: 10.1529/biophysj.106.092510

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  29 in total

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Journal:  Biophys J       Date:  2005-09-02       Impact factor: 4.033

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  10 in total

1.  β-adrenergic effects on cardiac myofilaments and contraction in an integrated rabbit ventricular myocyte model.

Authors:  Jorge A Negroni; Stefano Morotti; Elena C Lascano; Aldrin V Gomes; Eleonora Grandi; José L Puglisi; Donald M Bers
Journal:  J Mol Cell Cardiol       Date:  2015-02-25       Impact factor: 5.000

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Journal:  J Comput Neurosci       Date:  2008-05-28       Impact factor: 1.621

3.  The Huxley crossbridge model as the basic mechanism for airway smooth muscle contraction.

Authors:  Ling Luo; Lu Wang; Peter D Paré; Chun Y Seow; Pasquale Chitano
Journal:  Am J Physiol Lung Cell Mol Physiol       Date:  2019-05-22       Impact factor: 5.464

4.  A biomechanical model for fluidization of cells under dynamic strain.

Authors:  Tenghu Wu; James J Feng
Journal:  Biophys J       Date:  2015-01-06       Impact factor: 4.033

5.  Variability, frequency composition, and temporal regularity of submaximal isometric elbow flexion force in subacute stroke.

Authors:  John W Chow; Dobrivoje S Stokic
Journal:  Exp Brain Res       Date:  2016-07-01       Impact factor: 1.972

6.  Actin Stress Fibers Response and Adaptation under Stretch.

Authors:  Roberto Bernal; Milenka Van Hemelryck; Basile Gurchenkov; Damien Cuvelier
Journal:  Int J Mol Sci       Date:  2022-05-03       Impact factor: 6.208

7.  Robust mechanobiological behavior emerges in heterogeneous myosin systems.

Authors:  Paul F Egan; Jeffrey R Moore; Allen J Ehrlicher; David A Weitz; Christian Schunn; Jonathan Cagan; Philip LeDuc
Journal:  Proc Natl Acad Sci U S A       Date:  2017-09-12       Impact factor: 11.205

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Authors:  Paul Egan; Jeffrey Moore; Christian Schunn; Jonathan Cagan; Philip LeDuc
Journal:  PLoS Comput Biol       Date:  2015-04-17       Impact factor: 4.475

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Authors:  Alf Månsson; Dilson Rassier; Georgios Tsiavaliaris
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Review 10.  Hill's equation of muscle performance and its hidden insight on molecular mechanisms.

Authors:  Chun Y Seow
Journal:  J Gen Physiol       Date:  2013-12       Impact factor: 4.086

  10 in total

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