Dataset Information

All atom NMDA receptor transmembrane domain model development and simulations in lipid bilayers and water.

ABSTRACT: N-methyl-d-aspartate receptors (NMDARs) are members of the ionotropic glutamate receptor family that mediate excitatory synaptic transmission in the central nervous system. The channels of NMDARs are permeable to Ca2+ but blocked by Mg2+, distinctive properties that underlie essential brain processes such as induction of synaptic plasticity. However, due to limited structural information about the NMDAR transmembrane ion channel forming domain, the mechanism of divalent cation permeation and block is understood poorly. In this paper we developed an atomistic model of the transmembrane domain (TMD) of NMDARs composed of GluN1 and GluN2A subunits (GluN1/2A receptors). The model was generated using (a) a homology model based on the structure of the NaK channel and a partially resolved structure of an AMPA receptor (AMPAR), and (b) a partially resolved X-ray structure of GluN1/2B NMDARs. Refinement and extensive Molecular Dynamics (MD) simulations of the NMDAR TMD model were performed in explicit lipid bilayer membrane and water. Targeted MD with simulated annealing was introduced to promote structure refinement. Putative positions of the Mg2+ and Ca2+ ions in the ion channel divalent cation binding site are proposed. Differences in the structural and dynamic behavior of the channel protein in the presence of Mg2+ or Ca2+ are analyzed. NMDAR protein conformational flexibility was similar with no ion bound to the divalent cation binding site and with Ca2+ bound, whereas Mg2+ binding reduced protein fluctuations. While bound at the binding site both ions retained their preferred ligand coordination numbers: 6 for Mg2+, and 7-8 for Ca2+. Four asparagine side chain oxygens, a back-bone oxygen, and a water molecule participated in binding a Mg2+ ion. The Ca2+ ion first coordination shell ligands typically included four to five side-chain oxygen atoms of the binding site asparagine residues, two water molecules and zero to two backbone oxygens of the GluN2B subunits. These results demonstrate the importance of high-resolution channel structures for elucidation of mechanisms of NMDAR permeation and block.

SUBMITTER: Mesbahi-Vasey S

PROVIDER: S-EPMC5459333 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

All atom NMDA receptor transmembrane domain model development and simulations in lipid bilayers and water.

Mesbahi-Vasey Samaneh S Veras Lea L Yonkunas Michael M Johnson Jon W JW Kurnikova Maria G MG

PloS one 20170605 6

N-methyl-d-aspartate receptors (NMDARs) are members of the ionotropic glutamate receptor family that mediate excitatory synaptic transmission in the central nervous system. The channels of NMDARs are permeable to Ca2+ but blocked by Mg2+, distinctive properties that underlie essential brain processes such as induction of synaptic plasticity. However, due to limited structural information about the NMDAR transmembrane ion channel forming domain, the mechanism of divalent cation permeation and blo ...[more]

PMID: 28582391

Similar Datasets

Project description:Diphtheria toxin translocation (T) domain undergoes conformational changes in acidic solution and associates with the lipid membranes, followed by refolding and transmembrane insertion of two nonpolar helices. This process is an essential step in delivery of the toxic catalytic domain of the diphtheria toxin to the infected cell, yet its molecular determinants are poorly characterized and understood. Therefore, an atomistic model of the T-domain-membrane interaction is needed to help characterize factors responsible for such association. In this work, we present atomistic model structures of T-domain membrane-bound conformations and investigate structural factors responsible for T-domain affinity with the lipid bilayer in acidic solution using all-atom molecular dynamics (MD) simulations. The initial models of the protein conformations and protein-membrane association that serve as starting points in the present work were developed using atomistic simulations of partial unfolding of the T-domain in acidic solution (Kurnikov, I. V.; et al. J. Mol. Biol. 2013, 425, 2752-2764), and coarse-grained simulations of the T-domain association with the membranes of various compositions (Flores-Canales, J. C.; et al. J. Membr. Biol. 2015, 248, 529-543). In this work we present atomistic level modeling of two distinct configurations of the T-domain in association with the anionic lipid bilayer. In microsecond-long MD simulations both conformations retain their compact structure and gradually penetrate deeper into the bilayer interface. One membrane-bound conformation is stabilized by the protein contacts with the lipid hydrophobic core. The second modeled conformation is initially inserted less deeply and forms multiple contacts with the lipid at the interface (headgroup) region. Such contacts are formed by the charged and hydrophilic groups of partially unfolded terminal helixes and loops. Neutralization of the acidic residues at the membrane interface allows for deeper insertion of the protein and reorientation of the protein at the membrane interface, which corroborates that acidic residue protonation as well as presence of the anionic lipids may play a role in the membrane association and further membrane insertion of the T-domain as implicated in experiments. All simulations reported in this work were performed using AMBER force-field on Anton supercomputer. To perform these reported simulations, we developed and carefully tested a force-field for the anionic 1-palmitoyl-2-oleoyl-phosphatidyl-glycerol (POPG) lipid, compatible with the Amber 99SB force-field and stable in microsecond-long MD simulations in isothermal-isobaric ensemble.

Dataset Information

All atom NMDA receptor transmembrane domain model development and simulations in lipid bilayers and water.

Publications

All atom NMDA receptor transmembrane domain model development and simulations in lipid bilayers and water.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets