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Self‐assembly of single integral membrane proteins into soluble nanoscale phospholipid bilayers

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Bayburt, Timothy H., Sligar, Stephen G.·2003·Protein Science

Abstract

One of the biggest challenges in pharmaceutical research is obtaining integral membrane proteins in a functional, solubilized, and monodisperse state that provides a native‐like environment that maintains the spectrum of in vivo activities. Many of these integral membrane proteins are receptors, enzymes, or other macromolecular assemblies that are important drug targets. An example is the general class of proteins composed of seven‐transmembrane segments (7‐TM) as exemplified by the G‐protein–coupled receptors. In this article, we describe a simple system for self‐assembling bacteriorhodopsin, as a model protein containing 7‐TM helices, with phospholipids to form a nanometer‐scale soluble bilayer structure encircled by a 200 amino acid scaffold protein. The result is the single molecule incorporation of an integral membrane protein target into a soluble and monodisperse structure that allows the structural and functional tools of solution biochemistry to be applied.

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Metadata

Authors
Bayburt, T. H., & Sligar, S. G.
Venue
Protein Science
Publisher
Wiley
Published
2003-11
Volume
12
Issue
11
Pages
2476-2481
ISSN
  • 0961-8368 (ISSN-L)
  • 1469-896X
OpenAlex
W2040795711
Cited by
270
References
0
FWCI
2.14
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Self‐assembly of single integral membrane proteins into soluble nanoscale phospholipid bilayers. https://app.cochat.ai/papers/10.1110/ps.03267503
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Bayburt, T. H., & Sligar, S. G. (2003). Self‐assembly of single integral membrane proteins into soluble nanoscale phospholipid bilayers. Protein Science. https://doi.org/10.1110/ps.03267503

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.