title: A predicted binding site for cholesterol on the GABAA receptor.
abstract: Modulation of the GABA type A receptor (GABAAR) function by cholesterol and other steroids is documented at the functional level, yet its structural basis is largely unknown. Current data on structurally related modulators suggest that cholesterol binds to subunit interfaces between transmembrane domains of the GABAAR. We construct homology models of a human GABAAR based on the structure of the glutamate-gated chloride channel GluCl of Caenorhabditis elegans. The models show the possibility of previously unreported disulfide bridges linking the M1 and M3 transmembrane helices in the α and γ subunits. We discuss the biological relevance of such disulfide bridges. Using our models, we investigate cholesterol binding to intersubunit cavities of the GABAAR transmembrane domain. We find that very similar binding modes are predicted independently by three approaches: analogy with ivermectin in the GluCl crystal structure, automated docking by AutoDock, and spontaneous rebinding events in unbiased molecular dynamics simulations. Taken together, the models and atomistic simulations suggest a somewhat flexible binding mode, with several possible orientations. Finally, we explore the possibility that cholesterol promotes pore opening through a wedge mechanism.
authors.affiliation: Laboratoire de Biochimie Théorique, CNRS, IBPC, and Université Paris Diderot, Paris, France.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Hénin
authors.affiliation: Department of Physics, Rutgers University-Camden, Camden, New Jersey; Center for Computational and Integrative Biology, Rutgers University-Camden, Camden, New Jersey.
authors.forename: Reza
authors.initials: R
authors.lastname: Salari
authors.affiliation: Center for Computational and Integrative Biology, Rutgers University-Camden, Camden, New Jersey.
authors.forename: Sruthi
authors.initials: S
authors.lastname: Murlidaran
authors.affiliation: Department of Physics, Rutgers University-Camden, Camden, New Jersey; Center for Computational and Integrative Biology, Rutgers University-Camden, Camden, New Jersey. Electronic address: Grace.Brannigan@rutgers.edu.
authors.forename: Grace
authors.initials: G
authors.lastname: Brannigan
mesh_terms: D001665:Binding Sites; D029742:Caenorhabditis elegans Proteins / Q000737:chemistry; D018118:Chloride Channels / Q000737:chemistry; D002784:Cholesterol / Q000378:metabolism*; D006801:Humans; D006860:Hydrogen Bonding; D007559:Ivermectin / Q000378:metabolism; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D016062:Porosity; D011485:Protein Binding; D011487:Protein Conformation; D011963:Receptors, GABA-A / Q000737:chemistry / Q000378:metabolism*; D017386:Sequence Homology, Amino Acid; D013379:Substrate Specificity
chemical_list: D029742:Caenorhabditis elegans Proteins; D018118:Chloride Channels; D011963:Receptors, GABA-A; C109777:glutamate-gated chloride channels; D007559:Ivermectin; D002784:Cholesterol