• Title of article

    Modeling residual force enhancement with generic cross-bridge models

  • Author/Authors

    Walcott، نويسنده , , Sam and Herzog، نويسنده , , Walter، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    15
  • From page
    172
  • To page
    186
  • Abstract
    The interaction of actin and myosin through cross-bridges explains much of muscle behavior. However, some properties of muscle, such as residual force enhancement, cannot be explained by current cross-bridge models. There is ongoing debate whether conceptual cross-bridge models, as pioneered by Huxley (A.F. Huxley, Muscle structure and theories of contraction, Prog. Biophys. Biophys. Chem. 7 (1957) 255) could, if suitably modified, fit experimental data showing residual force enhancement. Here we prove that there are only two ways to explain residual force enhancement with these ‘traditional’ cross-bridge models: the first requires cross-bridges to become stuck on actin (the stuck cross-bridge model) while the second requires that cross-bridges that are pulled off beyond a critical strain enter a ‘new’ unbound state that leads to a new force-producing cycle (the multi-cycle model). Stuck cross-bridge models cannot fit the velocity and stretch amplitude dependence of residual force enhancement, while the multi-cycle models can. The results of this theoretical analysis demonstrate that current kinetic models of cross-bridge action cannot explain the experimentally observed residual force enhancement. Either cross-bridges in the force-enhanced state follow a different kinetic cycle than cross-bridges in a ‘normal’ force state, or the assumptions underlying traditional cross-bridge models must be violated during experiments that show residual force enhancement.
  • Keywords
    Force enhancement , Molecular history-dependence , Stuck cross-bridge model , Strain-dependent rate constants , Multi-cycle model
  • Journal title
    Mathematical Biosciences
  • Serial Year
    2008
  • Journal title
    Mathematical Biosciences
  • Record number

    1589274