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Biomolecular crowding affects the biophysical and biochemical behavior of macro- molecules when compared to the dilute environment in experiments on isolated proteins. Computational modeling and simulation are useful tools to study how crowding affects the structural dynamics and biological properties of macromolecules. As computational power increased, modeling and simulating large scale all-atom explicit solvent models of the prokaryote cytoplasm has now become possible. In this work, we build an atomistic model of the cytoplasm of Escherichia coli composed of 1.5 million atoms and submit it to a total of 3μs of molecular dynamics simulations. The model consists of 8 different proteins representing about 50% of the cytoplasmic proteins and one type of t-RNA molecule. Properties of biomolecules under crowding conditions are compared to those from simulations of the individual compounds under dilute conditions. The simulation model is found to be consistent with experimental data about the diffusion coefficient and stability of macromolecules under crowded conditions. In order to stimulate further work we provide a Python script and a set of files to enable other researchers to build their own E. coli cytoplasm models to address questions related to crowding.
This article was published in the following journal.
Name: Journal of chemical information and modeling
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Models used experimentally or theoretically to study molecular shape, electronic properties, or interactions; includes analogous molecules, computer-generated graphics, and mechanical structures.
Models connecting initiating events at the cellular and molecular level to population-wide impacts. Computational models may be at levels relating toxicology to adverse effects.
Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.
Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression.
Statistical models of the production, distribution, and consumption of goods and services, as well as of financial considerations. For the application of statistics to the testing and quantifying of economic theories MODELS, ECONOMETRIC is available.
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