A kinetic model describing the processivity of Myosin-V
| Autor: | Rebecca B. Hoyle, Matthew S. Turner, Karl I. Skau |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2006 |
| Předmět: |
Myosin Type V
Biophysics Motion (geometry) Biophysical Theory and Modeling Parameter space Models Biological Phosphates Strain energy Quantitative Biology::Subcellular Processes Motion Adenosine Triphosphate Reaction rate constant QD Statistical physics Network model Chemistry Biomolecules (q-bio.BM) Actin cytoskeleton Fick's laws of diffusion Adenosine Diphosphate Actin Cytoskeleton Kinetics Classical mechanics Models Chemical Quantitative Biology - Biomolecules FOS: Biological sciences Head (vessel) |
| Zdroj: | ResearcherID |
| ISSN: | 0006-3495 |
| Popis: | The precise details of how myosin-V coordinates the biochemical reactions and mechanical motions of its two head elements to engineer effective processive molecular motion along actin filaments remain unresolved. We compare a quantitative kinetic model of the myosin-V walk, consisting of five basic states augmented by two further states to allow for futile hydrolysis and detachments, with experimental results for run lengths, velocities, and dwell times and their dependence on bulk nucleotide concentrations and external loads in both directions. The model reveals how myosin-V can use the internal strain in the molecule to synchronise the motion of the head elements. Estimates for the rate constants in the reaction cycle and the internal strain energy are obtained by a computational comparison scheme involving an extensive exploration of the large parameter space. This scheme exploits the fact that we have obtained analytic results for our reaction network, e.g. for the velocity but also the run length, diffusion constant and fraction of backward steps. The agreement with experiment is often reasonable but some open problems are highlighted, in particular the inability of such a general model to reproduce the reported dependence of run length on ADP. The novel way that our approach explores parameter space means that any confirmed discrepancies should give new insights into the reaction network model. Comment: 49 pages, 14 figures |
| Databáze: | OpenAIRE |
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