Probing Why Nature may Favor Heterogeneous Myosin Systems through Single Molecule and Systems Level Approaches

Abstract

Myosin motor proteins utilize chemical energy and apply mechanical force to actin filaments. We computationally model the emergent interactions of large populations of varied myosin molecules with actin. Two levels are considered: individual myosin molecules and a systems level. We found that heterogeneous systems with a distribution of two different isoforms have unique and sometimes superior performance in comparison to homogeneous systems.At the single molecule level, we derived a mathematical model based on the swinging lever arm theory for mapping molecular structures to mechano-chemical behaviors. We explored the configurations of four myosin structures as inputs and when all parameters were perturbed individually, they each modulated emergent system behavior differently.At the systems level, the number and relative concentration of myosin isoforms is varied. The steady-state emergent response of the system (i.e. filament velocity, energy usage, and stability) is determined with respect to varied exogenous forces applied to a moving actin filament. System robustness (ability to operate under a number of different conditions) was examined, and we find that greater robustness requires higher energy usage and larger systems.When homogeneous and heterogeneous systems are compared, we find superior qualities present in heterogeneous systems. For instance, one heterogeneous system had decreased energy usage at lower velocities (i.e. greater performance) and a higher maximum stable system velocity than any possible homogeneous configuration.These results provide novel insights for why nature may favor molecularly heterogeneous systems. While myosin heterogeneity in muscles is beneficial because their relative concentrations may adapt over time, our findings suggest that the heterogeneity may also provide increased performance at a specific time. These findings inform the design of future myosin-based technologies, in addition to elucidating the complexity present in natural systems.