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Friday picture: molecular modelling of the cytoplasm Grant Jacobs Mar 26

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A very striking image features on the cover of the March 2010 of PLoS Computational Biology (below), showing a molecular simulation of the interior of the cytoplasm of the bacterium Escherichia coli.

Source: PLoS Computational Biology; image credits: Elcock

Source: PLoS Computational Biology; image credits: Elcock, University of Iowa.

One of the things that has impressed me as important to understand molecular biology is a need to understand how molecules work within the very dense of the interior of a cell.

’Test tube’ studies of molecules–properly termed in vitro studies (literally, in glass) as opposed to in vivo studies (literally, in life)–are usually in very different conditions to the crowded conditions found in the interior of the cell the molecules being studied came from.

The research associated with this figure reports one of a small number of attempts to examine the impact of crowding effects inside the cells on the behaviour of proteins.

The authors based their model on the 50 most common molecules found in the cytoplasm of E. coli. The molecules in a mixture of green and yellow are RNAs (ribonucleic acid), the others are proteins.

They show that their model matches reasonably well with in vivo measurements of the diffusion rate of a fluorescent ’marker’ protein (the popular cell biologists‘ work horse GFP, green fluorescent protein, which won the 2008 Nobel Prize for Chemistry). Likewise, the thermodynamic stabilities of the protein studied are comparable.

This work points to a promising future of detailed molecular simulations of large collections of molecules aimed at understanding the behaviour of molecules in these conditions.

Reference

Diffusion, Crowding & Protein Stability in a Dynamic Molecular Model of the Bacterial Cytoplasm

McGuffee and Elcock, PLoS Computational Biology 6(3)694 (2010).

doi:10.1371/journal.pcbi.1000705


Other articles in Code for life:

Bioinformatics blog carnival

Prince or pauper? Tell Nature what you earn

Developing bioinformatics methods: by who and how

The inheritance of face recognition, or should you blame your parents if you can’t recognise faces?

Retrospective–The mythology of bioinformatics

Deleting a gene can turn an ovary into a testis in adult mammals

Bioinformatics — computing with biotechnology and molecular biology data.


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