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Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows

Recently, when studying folding of a SH3 domain, we discovered that the flows of transitions between protein states can be surprisingly similar to turbulent fluid flows. This similarity was not restricted by a vortex pattern of the flow fields but extended to a spatial correlation of flow fluctuatio...

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Autores principales: Andryushchenko, Vladimir A., Chekmarev, Sergei F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716548/
https://www.ncbi.nlm.nih.gov/pubmed/29206845
http://dx.doi.org/10.1371/journal.pone.0188659
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author Andryushchenko, Vladimir A.
Chekmarev, Sergei F.
author_facet Andryushchenko, Vladimir A.
Chekmarev, Sergei F.
author_sort Andryushchenko, Vladimir A.
collection PubMed
description Recently, when studying folding of a SH3 domain, we discovered that the flows of transitions between protein states can be surprisingly similar to turbulent fluid flows. This similarity was not restricted by a vortex pattern of the flow fields but extended to a spatial correlation of flow fluctuations, resulting, in particular, in the structure functions such as in the Kolmogorov theory of homogeneous and isotropic turbulence. Here, we undertake a detailed analysis of spatial distribution of folding flows and their similarity to turbulent fluid flows. Using molecular dynamics simulations, we study folding of another benchmark system—Trp-cage miniprotein, which has different content of secondary structure elements and mechanism of folding. Calculating the probability fluxes of transitions in a three-dimensional space of collective variables, we have found that similar to the SH3 domain, the structure functions of the second and third orders correspond to the Kolmogorov functions. The spatial distributions of the probability fluxes are self-similar with a fractal dimension, and the fractal index decreases toward the native state, indicating that the flow becomes more turbulent as the native state is approached. We also show that the process of folding can be viewed as Brownian diffusion in the space of probability fluxes. The diffusion coefficient plays a role of the key parameter that defines the structures functions, similar to the rate of dissipation of kinetic energy in hydrodynamic turbulence. The obtained results, first, show that the very complex dynamics of protein folding allows a simple characterization in terms of scaling and diffusion of probability fluxes, and, secondly, they suggest that the turbulence phenomena similar to hydrodynamic turbulence are not specific of folding of a particular protein but are common to protein folding.
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spelling pubmed-57165482017-12-15 Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows Andryushchenko, Vladimir A. Chekmarev, Sergei F. PLoS One Research Article Recently, when studying folding of a SH3 domain, we discovered that the flows of transitions between protein states can be surprisingly similar to turbulent fluid flows. This similarity was not restricted by a vortex pattern of the flow fields but extended to a spatial correlation of flow fluctuations, resulting, in particular, in the structure functions such as in the Kolmogorov theory of homogeneous and isotropic turbulence. Here, we undertake a detailed analysis of spatial distribution of folding flows and their similarity to turbulent fluid flows. Using molecular dynamics simulations, we study folding of another benchmark system—Trp-cage miniprotein, which has different content of secondary structure elements and mechanism of folding. Calculating the probability fluxes of transitions in a three-dimensional space of collective variables, we have found that similar to the SH3 domain, the structure functions of the second and third orders correspond to the Kolmogorov functions. The spatial distributions of the probability fluxes are self-similar with a fractal dimension, and the fractal index decreases toward the native state, indicating that the flow becomes more turbulent as the native state is approached. We also show that the process of folding can be viewed as Brownian diffusion in the space of probability fluxes. The diffusion coefficient plays a role of the key parameter that defines the structures functions, similar to the rate of dissipation of kinetic energy in hydrodynamic turbulence. The obtained results, first, show that the very complex dynamics of protein folding allows a simple characterization in terms of scaling and diffusion of probability fluxes, and, secondly, they suggest that the turbulence phenomena similar to hydrodynamic turbulence are not specific of folding of a particular protein but are common to protein folding. Public Library of Science 2017-12-05 /pmc/articles/PMC5716548/ /pubmed/29206845 http://dx.doi.org/10.1371/journal.pone.0188659 Text en © 2017 Andryushchenko, Chekmarev 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
Andryushchenko, Vladimir A.
Chekmarev, Sergei F.
Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows
title Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows
title_full Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows
title_fullStr Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows
title_full_unstemmed Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows
title_short Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows
title_sort turbulence in protein folding: vorticity, scaling and diffusion of probability flows
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716548/
https://www.ncbi.nlm.nih.gov/pubmed/29206845
http://dx.doi.org/10.1371/journal.pone.0188659
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