Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm.
A longstanding question in molecular biology is the extent to which the behavior of macromolecules observed in vitro accurately reflects their behavior in vivo. A number of sophisticated experimental techniques now allow the behavior of individual types of macromolecule to be studied directly in viv...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2010-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC2832674?pdf=render |
| _version_ | 1818842994106695680 |
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| author | Sean R McGuffee Adrian H Elcock |
| author_facet | Sean R McGuffee Adrian H Elcock |
| author_sort | Sean R McGuffee |
| collection | DOAJ |
| description | A longstanding question in molecular biology is the extent to which the behavior of macromolecules observed in vitro accurately reflects their behavior in vivo. A number of sophisticated experimental techniques now allow the behavior of individual types of macromolecule to be studied directly in vivo; none, however, allow a wide range of molecule types to be observed simultaneously. In order to tackle this issue we have adopted a computational perspective, and, having selected the model prokaryote Escherichia coli as a test system, have assembled an atomically detailed model of its cytoplasmic environment that includes 50 of the most abundant types of macromolecules at experimentally measured concentrations. Brownian dynamics (BD) simulations of the cytoplasm model have been calibrated to reproduce the translational diffusion coefficients of Green Fluorescent Protein (GFP) observed in vivo, and "snapshots" of the simulation trajectories have been used to compute the cytoplasm's effects on the thermodynamics of protein folding, association and aggregation events. The simulation model successfully describes the relative thermodynamic stabilities of proteins measured in E. coli, and shows that effects additional to the commonly cited "crowding" effect must be included in attempts to understand macromolecular behavior in vivo. |
| first_indexed | 2024-12-19T04:50:49Z |
| format | Article |
| id | doaj.art-c5fa7d121b534ea196b9fd5c85749f63 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-19T04:50:49Z |
| publishDate | 2010-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-c5fa7d121b534ea196b9fd5c85749f632022-12-21T20:35:21ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-03-0163e100069410.1371/journal.pcbi.1000694Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm.Sean R McGuffeeAdrian H ElcockA longstanding question in molecular biology is the extent to which the behavior of macromolecules observed in vitro accurately reflects their behavior in vivo. A number of sophisticated experimental techniques now allow the behavior of individual types of macromolecule to be studied directly in vivo; none, however, allow a wide range of molecule types to be observed simultaneously. In order to tackle this issue we have adopted a computational perspective, and, having selected the model prokaryote Escherichia coli as a test system, have assembled an atomically detailed model of its cytoplasmic environment that includes 50 of the most abundant types of macromolecules at experimentally measured concentrations. Brownian dynamics (BD) simulations of the cytoplasm model have been calibrated to reproduce the translational diffusion coefficients of Green Fluorescent Protein (GFP) observed in vivo, and "snapshots" of the simulation trajectories have been used to compute the cytoplasm's effects on the thermodynamics of protein folding, association and aggregation events. The simulation model successfully describes the relative thermodynamic stabilities of proteins measured in E. coli, and shows that effects additional to the commonly cited "crowding" effect must be included in attempts to understand macromolecular behavior in vivo.http://europepmc.org/articles/PMC2832674?pdf=render |
| spellingShingle | Sean R McGuffee Adrian H Elcock Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. PLoS Computational Biology |
| title | Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. |
| title_full | Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. |
| title_fullStr | Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. |
| title_full_unstemmed | Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. |
| title_short | Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. |
| title_sort | diffusion crowding protein stability in a dynamic molecular model of the bacterial cytoplasm |
| url | http://europepmc.org/articles/PMC2832674?pdf=render |
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