@article{2069db4e11ff429697b80f35e210a87c,
title = "Neurotransmitter Funneling Optimizes Glutamate Receptor Kinetics",
abstract = "Ionotropic glutamate receptors (iGluRs) mediate neurotransmission at the majority of excitatory synapses in the brain. Little is known, however, about how glutamate reaches the recessed binding pocket in iGluR ligand-binding domains (LBDs). Here we report the process of glutamate binding to a prototypical iGluR, GluA2, in atomistic detail using unbiased molecular simulations. Charged residues on the LBD surface form pathways that facilitate glutamate binding by effectively reducing a three-dimensional diffusion process to a spatially constrained, two-dimensional one. Free energy calculations identify residues that metastably bind glutamate and help guide it into the binding pocket. These simulations also reveal that glutamate can bind in an inverted conformation and also reorient while in its pocket. Electrophysiological recordings demonstrate that eliminating these transient binding sites slows activation and deactivation, consistent with slower glutamate binding and unbinding. These results suggest that binding pathways have evolved to optimize rapid responses of AMPA-type iGluRs at synapses. Yu et al. show that the ligand-binding domain of ionotropic glutamate receptors has structural features on its surface that guide the agonist glutamate to its binding site. This phenomenon serves to accelerate receptor activation.",
keywords = "electrophysiology, free energy, glutamate receptors, ligand binding, ligand-gated ion channels, molecular dynamics simulations",
author = "Alvin Yu and H{\'e}ctor Salazar and Plested, {Andrew J.R.} and Lau, {Albert Y.}",
note = "Funding Information: We thank Jelena Baranovic for comments on the manuscript. Anton computer time was provided by the Pittsburgh Supercomputing Center (PSC) through Grant R01GM116961 from the National Institutes of Health. The Anton machine at PSC was generously made available by D.E. Shaw Research. Resources provided by the Maryland Advanced Research Computing Center (MARCC) at Johns Hopkins University were used. This work was supported by the National Institutes of Health grant R01GM094495 (to A.Y.L.), the ERC grant “GluActive” (647895), and the DFG Cluster of Excellence “NeuroCure” (EXC-257) (to A.J.R.P.). A.J.R.P. is a Heisenberg Professor of the DFG (PL619-3.1). H.S. was the recipient of a fellowship from the Human Frontier Science Program (LT000079/2011-L). Funding Information: We thank Jelena Baranovic for comments on the manuscript. Anton computer time was provided by the Pittsburgh Supercomputing Center (PSC) through Grant R01GM116961 from the National Institutes of Health . The Anton machine at PSC was generously made available by D.E. Shaw Research. Resources provided by the Maryland Advanced Research Computing Center (MARCC) at Johns Hopkins University were used. This work was supported by the National Institutes of Health grant R01GM094495 (to A.Y.L.), the ERC grant “GluActive” ( 647895 ), and the DFG Cluster of Excellence “NeuroCure” ( EXC-257 ) (to A.J.R.P.). A.J.R.P. is a Heisenberg Professor of the DFG (PL619-3.1). H.S. was the recipient of a fellowship from the Human Frontier Science Program ( LT000079/2011-L ). Publisher Copyright: {\textcopyright} 2017 The Authors",
year = "2018",
month = jan,
day = "3",
doi = "10.1016/j.neuron.2017.11.024",
language = "English (US)",
volume = "97",
pages = "139--149.e4",
journal = "Neuron",
issn = "0896-6273",
publisher = "Cell Press",
number = "1",
}