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Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations
Passive forces in sarcomeres are mainly related to the giant protein titin. Titin’s extensible region consists of spring-like elements acting in series. In skeletal muscles these elements are the PEVK segment, two distinct immunoglobulin (Ig) domain regions (proximal and distal), and a N2A portion....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898704/ https://www.ncbi.nlm.nih.gov/pubmed/27276390 http://dx.doi.org/10.1371/journal.pcbi.1004904 |
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author | Schappacher-Tilp, Gudrun Leonard, Timothy Desch, Gertrud Herzog, Walter |
author_facet | Schappacher-Tilp, Gudrun Leonard, Timothy Desch, Gertrud Herzog, Walter |
author_sort | Schappacher-Tilp, Gudrun |
collection | PubMed |
description | Passive forces in sarcomeres are mainly related to the giant protein titin. Titin’s extensible region consists of spring-like elements acting in series. In skeletal muscles these elements are the PEVK segment, two distinct immunoglobulin (Ig) domain regions (proximal and distal), and a N2A portion. While distal Ig domains are thought to form inextensible end filaments in intact sarcomeres, proximal Ig domains unfold in a force- and time-dependent manner. In length-ramp experiments of single titin strands, sequential unfolding of Ig domains leads to a typical saw-tooth pattern in force-elongation curves which can be simulated by Monte Carlo simulations. In sarcomeres, where more than a thousand titin strands are arranged in parallel, numerous Monte Carlo simulations are required to estimate the resultant force of all titin filaments based on the non-uniform titin elongations. To simplify calculations, the stochastic model of passive forces is often replaced by linear or non-linear deterministic and phenomenological functions. However, new theories of muscle contraction are based on the hypothesized binding of titin to the actin filament upon activation, and thereby on a prominent role of the structural properties of titin. Therefore, these theories necessitate a detailed analysis of titin forces in length-ramp experiments. In our study we present a simple and efficient alternative to Monte Carlo simulations. Based on a structural titin model, we calculate the exact probability distributions of unfolded Ig domains under length-ramp conditions needed for rigorous analysis of expected forces, distribution of unfolding forces, etc. Due to the generality of our model, the approach is applicable to a wide range of stochastic protein unfolding problems. |
format | Online Article Text |
id | pubmed-4898704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48987042016-06-16 Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations Schappacher-Tilp, Gudrun Leonard, Timothy Desch, Gertrud Herzog, Walter PLoS Comput Biol Research Article Passive forces in sarcomeres are mainly related to the giant protein titin. Titin’s extensible region consists of spring-like elements acting in series. In skeletal muscles these elements are the PEVK segment, two distinct immunoglobulin (Ig) domain regions (proximal and distal), and a N2A portion. While distal Ig domains are thought to form inextensible end filaments in intact sarcomeres, proximal Ig domains unfold in a force- and time-dependent manner. In length-ramp experiments of single titin strands, sequential unfolding of Ig domains leads to a typical saw-tooth pattern in force-elongation curves which can be simulated by Monte Carlo simulations. In sarcomeres, where more than a thousand titin strands are arranged in parallel, numerous Monte Carlo simulations are required to estimate the resultant force of all titin filaments based on the non-uniform titin elongations. To simplify calculations, the stochastic model of passive forces is often replaced by linear or non-linear deterministic and phenomenological functions. However, new theories of muscle contraction are based on the hypothesized binding of titin to the actin filament upon activation, and thereby on a prominent role of the structural properties of titin. Therefore, these theories necessitate a detailed analysis of titin forces in length-ramp experiments. In our study we present a simple and efficient alternative to Monte Carlo simulations. Based on a structural titin model, we calculate the exact probability distributions of unfolded Ig domains under length-ramp conditions needed for rigorous analysis of expected forces, distribution of unfolding forces, etc. Due to the generality of our model, the approach is applicable to a wide range of stochastic protein unfolding problems. Public Library of Science 2016-06-08 /pmc/articles/PMC4898704/ /pubmed/27276390 http://dx.doi.org/10.1371/journal.pcbi.1004904 Text en © 2016 Schappacher-Tilp 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Schappacher-Tilp, Gudrun Leonard, Timothy Desch, Gertrud Herzog, Walter Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations |
title | Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations |
title_full | Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations |
title_fullStr | Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations |
title_full_unstemmed | Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations |
title_short | Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations |
title_sort | computing average passive forces in sarcomeres in length-ramp simulations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898704/ https://www.ncbi.nlm.nih.gov/pubmed/27276390 http://dx.doi.org/10.1371/journal.pcbi.1004904 |
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