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Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm
- Source :
- eLife, Vol 5 (2016), eLife
- Publication Year :
- 2016
- Publisher :
- eLife Sciences Publications, Ltd, 2016.
-
Abstract
- Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology. DOI: http://dx.doi.org/10.7554/eLife.19274.001<br />eLife digest Much of the work that has been done to understand how cells work has involved studying parts of a cell in isolation. This is particularly true of studies that have examined the arrangement of atoms in large molecules with elaborate structures like proteins or DNA. However, cells are densely packed with many different molecules and there is little proof that proteins keep the same structures inside cells that they have when they are studied alone. To really understand how cells work, new ways to understand how molecules behave inside cells are needed. While this cannot be achieved directly, technology has now reached the stage where we can, to some extent, study living cells by recreating them virtually. Simulated cells can copy the atomic details of all the molecules in a cell and can estimate how different molecules might behave together. Yu et al. have now developed a computer simulation of part of a cell from the bacterium, Mycoplasma genitalium, one of the simplest forms of life on Earth. This model suggested new possible interactions between molecules inside cells that cannot currently be studied in real cells. The model shows that some proteins have a much less rigid structure in cells than they do in isolation, whilst others are able to work together more closely to carry out certain tasks. Finally, the model predicted that small molecules such as food, water and drugs would move more slowly through cells as they become stuck or trapped by larger molecules. These results could be particularly important in helping to improve drug design. Currently the simulations are limited, and can only model parts of simple cells for less than a thousandth of a second. However, in future it should be possible to recreate larger and more complex cells, including human cells, for longer periods of time. These could be used to better study human diseases and help to design new treatments. The ultimate goal is to simulate a whole cell in full detail by combining all the available experimental data. DOI: http://dx.doi.org/10.7554/eLife.19274.002
- Subjects :
- 0301 basic medicine
Cytoplasm
Macromolecular Substances
QH301-705.5
Science
Systems biology
Mycoplasma genitalium
Molecular Dynamics Simulation
Biology
Bioinformatics
General Biochemistry, Genetics and Molecular Biology
native state stability
03 medical and health sciences
Spatio-Temporal Analysis
None
Biology (General)
General Immunology and Microbiology
crowding effects
General Neuroscience
diffusion
Dynamics (mechanics)
Rigid structure
General Medicine
Biophysics and Structural Biology
Small molecule
whole-cell modeling
quinary interactions
030104 developmental biology
Structural biology
metabolite dynamics
Medicine
Whole cell
Biological system
Computational and Systems Biology
Research Article
Macromolecule
Subjects
Details
- ISSN :
- 2050084X
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- eLife
- Accession number :
- edsair.doi.dedup.....8916f8e05fafe414e3c74ff23b780d51