Including Thermal Fluctuations in Actomyosin Stable States Increases the Predicted Force per Motor and Macroscopic Efficiency in Muscle Modelling

PLoS Comput Biol. 2016 Sep 14;12(9):e1005083. doi: 10.1371/journal.pcbi.1005083. eCollection 2016 Sep.

Abstract

Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Actomyosin / chemistry*
  • Actomyosin / metabolism*
  • Animals
  • Anura
  • Computational Biology
  • Humans
  • Models, Biological*
  • Muscle Contraction / physiology*
  • Muscles / physiology*

Substances

  • Actomyosin

Grants and funding

LM’s work was partially supported by High Performance Computing Infrastructure (HPCI) Field 1 Supercomputational Life Science (Strategic institution: RIKEN) and European Commission, Seventh Framework Programme (FP7/2007-2013) under Grant Agreement n°600376. TW’s work was supported in part by MEXT as Strategic Programs for Innovative Research Field 1 Supercomputational Life Science and a social and scientific priority issue (Integrated computational life science to support personalized and preventive medicine) to be tackled by using post-K computer. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.