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State-dependent protein-lipid interactions of a pentameric ligand-gated ion channel in a neuronal membrane.
- Source :
-
PLoS computational biology [PLoS Comput Biol] 2021 Feb 11; Vol. 17 (2), pp. e1007856. Date of Electronic Publication: 2021 Feb 11 (Print Publication: 2021). - Publication Year :
- 2021
-
Abstract
- Pentameric ligand-gated ion channels (pLGICs) are receptor proteins that are sensitive to their membrane environment, but the mechanism for how lipids modulate function under physiological conditions in a state dependent manner is not known. The glycine receptor is a pLGIC whose structure has been resolved in different functional states. Using a realistic model of a neuronal membrane coupled with coarse-grained molecular dynamics simulations, we demonstrate that some key lipid-protein interactions are dependent on the receptor state, suggesting that lipids may regulate the receptor's conformational dynamics. Comparison with existing structural data confirms known lipid binding sites, but we also predict further protein-lipid interactions including a site at the communication interface between the extracellular and transmembrane domain. Moreover, in the active state, cholesterol can bind to the binding site of the positive allosteric modulator ivermectin. These protein-lipid interaction sites could in future be exploited for the rational design of lipid-like allosteric drugs.<br />Competing Interests: The authors have declared that no competing interests exist.
- Subjects :
- Allosteric Site
Animals
Binding Sites
Cholesterol chemistry
Cholesterol metabolism
Computational Biology
Humans
Ivermectin chemistry
Ivermectin metabolism
Ligand-Gated Ion Channels chemistry
Membrane Lipids chemistry
Membrane Lipids metabolism
Membrane Proteins chemistry
Membrane Proteins metabolism
Molecular Dynamics Simulation
Protein Binding
Protein Domains
Protein Structure, Quaternary
Receptors, Glycine chemistry
Receptors, Glycine metabolism
Ligand-Gated Ion Channels metabolism
Models, Neurological
Neurons metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 1553-7358
- Volume :
- 17
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- PLoS computational biology
- Publication Type :
- Academic Journal
- Accession number :
- 33571182
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1007856