Emergent systems energy laws for predicting myosin ensemble processivity.

Paul Egan,Philip Leduc,Jonathan Cagan,Jeffrey Moore,Christian Schunn

doi:10.1371/journal.pcbi.1004177

Paul Egan, Philip Leduc + Show 3 more

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https://doi.org/10.1371/journal.pcbi.1004177

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Abstract

In complex systems with stochastic components, systems laws often emerge that describe higher level behavior regardless of lower level component configurations. In this paper, emergent laws for describing mechanochemical systems are investigated for processive myosin-actin motility systems. On the basis of prior experimental evidence that longer processive lifetimes are enabled by larger myosin ensembles, it is hypothesized that emergent scaling laws could coincide with myosin-actin contact probability or system energy consumption. Because processivity is difficult to predict analytically and measure experimentally, agent-based computational techniques are developed to simulate processive myosin ensembles and produce novel processive lifetime measurements. It is demonstrated that only systems energy relationships hold regardless of isoform configurations or ensemble size, and a unified expression for predicting processive lifetime is revealed. The finding of such laws provides insight for how patterns emerge in stochastic mechanochemical systems, while also informing understanding and engineering of complex biological systems.

Highlights

In multi-level stochastic systems, the collective interactions of lower-level building blocks are necessary for producing emergent system functionality, some emergent system properties may hold regardless of how lower level building blocks are configured [1]
Complex biological systems consist of many parts that interact in non-obvious ways
The hypothesis was tested using simulations of motor protein systems, and demonstrated that patterns in their behavior emerge at a systems level

Summary

Introduction

In multi-level stochastic systems, the collective interactions of lower-level building blocks are necessary for producing emergent system functionality, some emergent system properties may hold regardless of how lower level building blocks are configured [1]. Myosins exert force as they stochastically attach and detach to gliding actin filaments [6,7,8] It is not fully understood how changes in myosin isoform structure affect the system’s higher level functioning (e.g. how fast/long the filament continues gliding). Derived system laws that describe the operations at the systems level as components are altered could significantly advance analyses of natural and synthetic myosin performance [14,15], and have particular applications relating to myosin-based diseases such as cardiomyopathy, where muscle tissue growth is affected by individual myosin configuration [16] Such rules could aid in developing heuristics for engineered technologies such as nano-actuators, molecular materials, and bio-sensors [17,18]

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