Department
neurobiology
Document Type
Article
Abstract
The Cys loop family of ligand-gated ion channels mediate fast synaptic transmission for communication between neurons. They are allosteric proteins, in which binding of a neurotransmitter to its binding site in the extracellular amino-terminal domain triggers structural changes in distant transmembrane domains to open a channel for ion flow. Although the locations of binding site and channel gating machinery are well defined, the structural basis of the activation pathway coupling binding and channel opening remains to be determined. In this paper, by analyzing amino acid covariance in a multiple sequence alignment, we have identified an energetically interconnected network in the Cys loop family of ligand-gated ion channels. Statistical coupling and correlated mutational analyses along with clustering revealed a highly coupled cluster. Mapping the positions in the cluster onto a three-dimensional structural model demonstrated that these highly coupled positions form an interconnected network linking experimentally identified binding domains through the coupling region to the gating machinery. In addition, these highly coupled positions are also condensed in the transmembrane domains, which are a recent focus for the sites of action of many allosteric modulators. Thus, our results revealed a genetically interconnected network that potentially plays an important role in the allosteric activation and modulation of the Cys loop family of ligand-gated ion channels. © 2006 by The American Society for Biochemistry and Molecular Biology, Inc.
Publication Date
6-30-2006
Publication Title
Journal of Biological Chemistry
ISSN
00219258
Volume
281
Issue
26
First Page
18184
Last Page
18192
Digital Object Identifier (DOI)
10.1074/jbc.M600349200
Recommended Citation
Chen, Yonghui; Reilly, Kevin; and Chang, Yongchang, "Evolutionarily Conserved Allosteric Network In The Cys Loop Family Of Ligand-Gated Ion Channels Revealed By Statistical Covariance Analyses" (2006). Translational Neuroscience. 50.
https://scholar.barrowneuro.org/neurobiology/50