Myosin Binding to Actin in the 3D Sarcomere Lattice
2016
The effect of tethering molecules in 3D space on bimolecular binding kinetics is rarely addressed and occasionally incorporated in models of cell motility. The simplest system to quantitatively determine this effect is in the 3D sarcomere lattice of the striated muscle where the tethered myosin can only bind to a relatively few available actin sites, positioned within a limited range of the thermal movement of myosin head. A multiscale Monte Carlo software platform MUSICO takes into account the exact number of unbound myosin molecules interacting only with unoccupied actin sites in their proximity and provides quantitative predictions of muscle response at the macroscopic scale. As such MUSICO is well suited to determine the effect of the distortion of interacting molecules on biochemical reactions, i.e. modulation of state transition rates in the actomyosin cycle by the imposed geometrical constraints of tethered myosin molecules. The simulations provide the distribution of bound sites, preservation of species, and most importantly the departure in nanoscopic behavior of tethered myosin molecules from unconstrained myosin interactions with actin. The MUSICO simulations with the simplest actomyosin cycles show large differences in predicted force velocity curves and during early force recovery phase after step in change in length comparing to all mass-action models. The origin of the differences in predicted muscle response is rooted in the differences the fluxes of myosin binding and corresponding instantaneous crossbridge distributions. Consequently a new approach showed that fitting of the experiments require significantly different binding rates than used in mass-action models and, therefore, to correctly describe the biochemical reactions of tethered molecules and the interaction energetics. The knowledge gained by this analysis can be used for development of new mass-action and other models that can implicitly incorporate this phenomenon via correction factors.
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