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Rotational and Translational Diffusion of Proteins as a Function of Concentration

[Image: see text] Atomistic simulations of three different proteins at different concentrations are performed to obtain insight into protein mobility as a function of protein concentration. We report on simulations of proteins from diluted to the physiological water concentration (about 70% of the m...

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Autores principales: Bashardanesh, Zahedeh, Elf, Johan, Zhang, Haiyang, van der Spoel, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2019
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906769/
https://www.ncbi.nlm.nih.gov/pubmed/31858051
http://dx.doi.org/10.1021/acsomega.9b02835
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author Bashardanesh, Zahedeh
Elf, Johan
Zhang, Haiyang
van der Spoel, David
author_facet Bashardanesh, Zahedeh
Elf, Johan
Zhang, Haiyang
van der Spoel, David
author_sort Bashardanesh, Zahedeh
collection PubMed
description [Image: see text] Atomistic simulations of three different proteins at different concentrations are performed to obtain insight into protein mobility as a function of protein concentration. We report on simulations of proteins from diluted to the physiological water concentration (about 70% of the mass). First, the viscosity was computed and found to increase by a factor of 7–9 going from pure water to the highest protein concentration, in excellent agreement with in vivo nuclear magnetic resonance results. At a physiological concentration of proteins, the translational diffusion is found to be slowed down to about 30% of the in vitro values. The slow-down of diffusion found here using atomistic models is slightly more than that of a hard sphere model that neglects the electrostatic interactions. Interestingly, rotational diffusion of proteins is slowed down somewhat more (by about 80–95% compared to in vitro values) than translational diffusion, in line with experimental findings and consistent with the increased viscosity. The finding that rotation is retarded more than translation is attributed to solvent-separated clustering. No direct interactions between the proteins are found, and the clustering can likely be attributed to dispersion interactions that are stronger between proteins than between protein and water. Based on these simulations, we can also conclude that the internal dynamics of the proteins in our study are affected only marginally under crowding conditions, and the proteins become somewhat more stable at higher concentrations. Simulations were performed using a force field that was tuned for dealing with crowding conditions by strengthening the protein–water interactions. This force field seems to lead to a reproducible partial unfolding of an α-helix in one of the proteins, an effect that was not observed in the unmodified force field.
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spelling pubmed-69067692019-12-19 Rotational and Translational Diffusion of Proteins as a Function of Concentration Bashardanesh, Zahedeh Elf, Johan Zhang, Haiyang van der Spoel, David ACS Omega [Image: see text] Atomistic simulations of three different proteins at different concentrations are performed to obtain insight into protein mobility as a function of protein concentration. We report on simulations of proteins from diluted to the physiological water concentration (about 70% of the mass). First, the viscosity was computed and found to increase by a factor of 7–9 going from pure water to the highest protein concentration, in excellent agreement with in vivo nuclear magnetic resonance results. At a physiological concentration of proteins, the translational diffusion is found to be slowed down to about 30% of the in vitro values. The slow-down of diffusion found here using atomistic models is slightly more than that of a hard sphere model that neglects the electrostatic interactions. Interestingly, rotational diffusion of proteins is slowed down somewhat more (by about 80–95% compared to in vitro values) than translational diffusion, in line with experimental findings and consistent with the increased viscosity. The finding that rotation is retarded more than translation is attributed to solvent-separated clustering. No direct interactions between the proteins are found, and the clustering can likely be attributed to dispersion interactions that are stronger between proteins than between protein and water. Based on these simulations, we can also conclude that the internal dynamics of the proteins in our study are affected only marginally under crowding conditions, and the proteins become somewhat more stable at higher concentrations. Simulations were performed using a force field that was tuned for dealing with crowding conditions by strengthening the protein–water interactions. This force field seems to lead to a reproducible partial unfolding of an α-helix in one of the proteins, an effect that was not observed in the unmodified force field. American Chemical Society 2019-11-27 /pmc/articles/PMC6906769/ /pubmed/31858051 http://dx.doi.org/10.1021/acsomega.9b02835 Text en Copyright © 2019 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Bashardanesh, Zahedeh
Elf, Johan
Zhang, Haiyang
van der Spoel, David
Rotational and Translational Diffusion of Proteins as a Function of Concentration
title Rotational and Translational Diffusion of Proteins as a Function of Concentration
title_full Rotational and Translational Diffusion of Proteins as a Function of Concentration
title_fullStr Rotational and Translational Diffusion of Proteins as a Function of Concentration
title_full_unstemmed Rotational and Translational Diffusion of Proteins as a Function of Concentration
title_short Rotational and Translational Diffusion of Proteins as a Function of Concentration
title_sort rotational and translational diffusion of proteins as a function of concentration
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906769/
https://www.ncbi.nlm.nih.gov/pubmed/31858051
http://dx.doi.org/10.1021/acsomega.9b02835
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