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Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity

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 b...

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Detalles Bibliográficos
Autores principales: Egan, Paul, Moore, Jeffrey, Schunn, Christian, Cagan, Jonathan, LeDuc, Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401713/
https://www.ncbi.nlm.nih.gov/pubmed/25885169
http://dx.doi.org/10.1371/journal.pcbi.1004177
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author Egan, Paul
Moore, Jeffrey
Schunn, Christian
Cagan, Jonathan
LeDuc, Philip
author_facet Egan, Paul
Moore, Jeffrey
Schunn, Christian
Cagan, Jonathan
LeDuc, Philip
author_sort Egan, Paul
collection PubMed
description 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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spelling pubmed-44017132015-04-21 Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity Egan, Paul Moore, Jeffrey Schunn, Christian Cagan, Jonathan LeDuc, Philip PLoS Comput Biol Research Article 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. Public Library of Science 2015-04-17 /pmc/articles/PMC4401713/ /pubmed/25885169 http://dx.doi.org/10.1371/journal.pcbi.1004177 Text en © 2015 Egan et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Egan, Paul
Moore, Jeffrey
Schunn, Christian
Cagan, Jonathan
LeDuc, Philip
Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
title Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
title_full Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
title_fullStr Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
title_full_unstemmed Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
title_short Emergent Systems Energy Laws for Predicting Myosin Ensemble Processivity
title_sort emergent systems energy laws for predicting myosin ensemble processivity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401713/
https://www.ncbi.nlm.nih.gov/pubmed/25885169
http://dx.doi.org/10.1371/journal.pcbi.1004177
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