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Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
Authors:Paul Egan  Jeffrey Moore  Christian Schunn  Jonathan Cagan  Philip LeDuc
Affiliation:1. Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.; 2. Department of Physiology and Biophysics, Boston University School of Medicine, Boston, Massachusetts, United States of America.; 3. Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.; Yale University, UNITED STATES,
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.
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