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The Journal of Chemical Physics
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The Journal of Chemical Physics
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Network analysis reveals how lipids and other cofactors influence membrane protein allostery

Authors: Annie M. Westerlund; Oliver Fleetwood; Sergio Pérez-Conesa; Lucie Delemotte;

Network analysis reveals how lipids and other cofactors influence membrane protein allostery

Abstract

Many membrane proteins are modulated by external stimuli, such as small molecule binding or change in pH, transmembrane voltage, or temperature. This modulation typically occurs at sites that are structurally distant from the functional site. Revealing the communication, known as allostery, between these two sites is key to understanding the mechanistic details of these proteins. Residue interaction networks of isolated proteins are commonly used to this end. Membrane proteins, however, are embedded in a lipid bilayer, which may contribute to allosteric communication. The fast diffusion of lipids hinders direct use of standard residue interaction networks. Here, we present an extension that includes cofactors such as lipids and small molecules in the network. The novel framework is applied to three membrane proteins: a voltage-gated ion channel (KCNQ1), a G-protein coupled receptor (GPCR—β2 adrenergic receptor), and a pH-gated ion channel (KcsA). Through systematic analysis of the obtained networks and their components, we demonstrate the importance of lipids for membrane protein allostery. Finally, we reveal how small molecules may stabilize different protein states by allosterically coupling and decoupling the protein from the membrane.

Country
Spain
Keywords

Mice, Allosteric Regulation, Bacterial Proteins, Potassium Channels, Voltage-Gated, Cell Membrane, KCNQ1 Potassium Channel, Escherichia coli, Animals, Phosphatidylglycerols, Streptomyces lividans, Receptors, Adrenergic, beta-2, Molecular Dynamics Simulation, Camelids, New World

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    31
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
31
Top 10%
Average
Top 10%
Green
hybrid
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