4.5 Review

Retinal proteins as model systems for membrane protein folding

期刊

BIOCHIMICA ET BIOPHYSICA ACTA-BIOENERGETICS
卷 1837, 期 5, 页码 656-663

出版社

ELSEVIER
DOI: 10.1016/j.bbabio.2013.11.021

关键词

Rhodopsin; Bacteriorhodopsin; Membrane protein folding; Denatured states

资金

  1. NSF CAREER [CC044917]
  2. NSF EAGER [IIS-1144281]
  3. National Institutes of Health [NLM108730]
  4. DAAD-Helmholtz Fellowship
  5. Royal Society Wolfson Merit Award
  6. Leverhulme Research Fellowship
  7. BBSRC [BB/G002037/1, BB/F013183/1]
  8. BBSRC [BB/F013183/1, BB/G002037/1] Funding Source: UKRI
  9. Biotechnology and Biological Sciences Research Council [BB/G002037/1, BB/F013183/1] Funding Source: researchfish

向作者/读者索取更多资源

Experimental folding studies of membrane proteins are more challenging than water-soluble proteins because of the higher hydrophobicity content of membrane embedded sequences and the need to provide a hydrophobic milieu for the transmembrane regions. The first challenge is their denaturation: due to the thermodynamic instability of polar groups in the membrane, secondary structures in membrane proteins are more difficult to disrupt than in soluble proteins. The second challenge is to refold from the denatured states. Successful refolding of membrane proteins has almost always been from very subtly denatured states. Therefore, it can be useful to analyze membrane protein folding using computational methods, and we will provide results obtained with simulated unfolding of membrane protein structures using the Floppy Inclusions and Rigid Substructure Topography (FIRST) method. Computational methods have the advantage that they allow a direct comparison between diverse membrane proteins. We will review here both, experimental and FIRST studies of the retinal binding proteins bacteriorhodopsin and mammalian rhodopsin, and discuss the extension of the findings to deriving hypotheses on the mechanisms of folding of membrane proteins in general. This article is part of a Special Issue entitled: Retinal Proteins - You can teach an old dog new tricks. (C) 2014 Elsevier B.V. All rights reserved.

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