The differential response of proteins to macromolecular crowding

Data de publicació

2016-10-03T11:22:14Z

2016-10-03T11:22:14Z

2016-07-29

2016-10-03T11:22:19Z

Resum

The habitat in which proteins exert their function contains up to 400 g/L of macromolecules, most of which are proteins. The repercussions of this dense environment on protein behavior are often overlooked or addressed using synthetic agents such as poly(ethylene glycol), whose ability to mimic protein crowders has not been demonstrated. Here we performed a comprehensive atomistic molecular dynamic analysis of the effect of protein crowders on the structure and dynamics of three proteins, namely an intrinsically disordered protein (ACTR), a molten globule conformation (NCBD), and a one-fold structure (IRF-3) protein. We found that crowding does not stabilize the native compact structure, and, in fact, often prevents structural collapse. Poly(ethylene glycol) PEG500 failed to reproduce many aspects of the physiologically-relevant protein crowders, thus indicating its unsuitability to mimic the cell interior. Instead, the impact of protein crowding on the structure and dynamics of a protein depends on its degree of disorder and results from two competing effects: the excluded volume, which favors compact states, and quinary interactions, which favor extended conformers. Such a viscous environment slows down protein flexibility and restricts the conformational landscape, often biasing it towards bioactive conformations but hindering biologically relevant protein-protein contacts. Overall, the protein crowders used here act as unspecific chaperons that modulate the protein conformational space, thus having relevant consequences for disordered proteins.

Tipus de document

Article


Versió publicada

Llengua

Anglès

Matèries i paraules clau

Proteïnes; Macromolècules; Proteins; Macromolecules

Publicat per

Public Library of Science (PLoS)

Documents relacionats

Reproducció del document publicat a: http://dx.doi.org/10.1371/journal.pcbi.1005040

PLoS Computational Biology, 2016, vol. 12, num. 7, p. e1005040

http://dx.doi.org/10.1371/journal.pcbi.1005040

info:eu-repo/grantAgreement/EC/H2020/675728/EU//BioExcel

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Drets

cc-by (c) Candotti, Michela et al., 2016

http://creativecommons.org/licenses/by/3.0/es

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