Modeling neuronal nicotinic and GABA receptors: important interface salt-links and protein dynamics

Structure-function Studies of GABA (A) Receptors and Related computer-aided Studies

The γ-aminobutyric acid type A receptor (GABA (A) receptor) is a membrane protein activated by the neurotransmitter GABA. Structurally, this major inhibitory neurotransmitter receptor in the human central nervous system is a pentamer that can be built from a selection of 19 subunits consisting of α(1,2,3,4,5 or 6), β (1,2 or 3), γ (1,2 or 3), ρ (1,2 or 3), and δ, π, θ, and ε. This creates several possible pentameric arrangements, which also influence the pharmacological and physiological properties of the receptor. The complexity and heterogeneity of the receptors are further increased by the addition of short and long splice variants in several subunits and the existence of multiple allosteric binding sites and expansive ligands that can bind to the receptors. Therefore, a comprehensive understanding of the structure and function of the receptors is required to gain novel insights into the consequences of receptor dysfunction and subsequent drug development studies. Notably, advancements in computational-aided studies have facilitated the elucidation of residual interactions and exploring energy binding, which may otherwise be challenging to investigate. In this review, we aim to summarize the current understanding of the structure and function of GABA (A) receptors obtained from advancements in computational-aided applications.

Unravelling the Turn-On Fluorescence Mechanism of a Fluorescein-Based Probe in GABAA Receptors

GABAA (γ-aminobutyric acid type A) receptors are ligand-gated ion channels mediating fast inhibitory transmission in the mammalian brain. Here we report the molecular and electronic mechanism governing the turn-on emission of a fluorescein-based imaging probe able to target the human GABAA receptor. Multiscale calculations evidence a drastic conformational change of the probe from folded in solution to extended upon binding to the receptor. Intramolecular ππ-stacking interactions present in the folded probe are responsible for quenching fluorescence in solution. In contrast, unfolding within the GABAA receptor changes the nature of the bright excited state triggering emission. Remarkably, this turn-on effect only manifests for the dianionic prototropic form of the imaging probe, which is found to be the strongest binder to the GABAA receptor. This study is expected to assist the design of new photoactivatable screening tools for allosteric modulators of the GABAA receptor.

Unravelling the Turn‐On Fluorescence Mechanism of a Fluorescein‐Based Probe in GABA A Receptors

GABA_A (γ‐aminobutyric acid type A) receptors are ligand‐gated ion channels mediating fast inhibitory transmission in the mammalian brain. Here we report the molecular and electronic mechanism governing the turn‐on emission of a fluorescein‐based imaging probe able to target the human GABA_A receptor. Multiscale calculations evidence a drastic conformational change of the probe from folded in solution to extended upon binding to the receptor. Intramolecular ππ‐stacking interactions present in the folded probe are responsible for quenching fluorescence in solution. In contrast, unfolding within the GABA_A receptor changes the nature of the bright excited state triggering emission. Remarkably, this turn‐on effect only manifests for the dianionic prototropic form of the imaging probe, which is found to be the strongest binder to the GABA_A receptor. This study is expected to assist the design of new photoactivatable screening tools for allosteric modulators of the GABA_A receptor.

Modulation of the Gloeobacter violaceus Ion Channel by Fentanyl: A Molecular Dynamics Study

Fentanyl is an opioid analgesic, which is routinely used in general surgery to suppress the sensation of pain and as the analgesic component in the induction and maintenance of anesthesia. Fentanyl is also used as the main component to induce anesthesia and as a potentiator to the general anesthetic propofol. The mechanism by which fentanyl induces its anesthetic action is still unclear, and we have therefore employed fully atomistic molecular dynamics simulations to probe this process by simulating the interactions of fentanyl with the Gloeobacter violaceus ligand-gated ion channel (GLIC). In this paper, we identify multiple extracellular fentanyl binding sites, which are different from the transmembrane general anesthetic binding sites observed for propofol and other general anesthetics. Our simulations identify a novel fentanyl binding site within the GLIC that results in conformational changes that inhibit conduction through the channel.

Identification of the Initial Steps in Signal Transduction in the α4β2 Nicotinic Receptor: Insights from Equilibrium and Nonequilibrium Simulations

Nicotinic acetylcholine receptors (nAChRs) modulate synaptic transmission in the nervous system. These receptors have emerged as therapeutic targets in drug discovery for treating several conditions, including Alzheimer's disease, pain, and nicotine addiction. In this in silico study, we use a combination of equilibrium and nonequilibrium molecular dynamics simulations to map dynamic and structural changes induced by nicotine in the human α4β2 nAChR. They reveal a striking pattern of communication between the extracellular binding pockets and the transmembrane domains (TMDs) and show the sequence of conformational changes associated with the initial steps in this process. We propose a general mechanism for signal transduction for Cys-loop receptors: the mechanistic steps for communication proceed firstly through loop C in the principal subunit, and are subsequently transmitted, gradually and cumulatively, to loop F of the complementary subunit, and then to the TMDs through the M2-M3 linker.

The neural γ2α1β2α1β2 gamma amino butyric acid ion channel receptor: structural analysis of the effects of the ivermectin molecule and disulfide bridges

While ~30% of the human genome encodes membrane proteins, only a handful of structures of membrane proteins have been resolved to high resolution. Here, we studied the structure of a member of the Cys-loop ligand gated ion channel protein superfamily of receptors, human type A γ₂α₁β₂α₁β₂ gamma amino butyric acid receptor complex in a lipid bilayer environment. Studying the correlation between the structure and function of the gamma amino butyric acid receptor may enhance our understanding of the molecular basis of ion channel dysfunctions linked with epilepsy, ataxia, migraine, schizophrenia and other neurodegenerative diseases. The structure of human γ₂α₁β₂α₁β₂ has been modeled based on the X-ray structure of the Caenorhabditis elegans glutamate-gated chloride channel via homology modeling. The template provided the first inhibitory channel structure for the Cys-loop superfamily of ligand-gated ion channels. The only available template structure before this glutamate-gated chloride channel was a cation selective channel which had very low sequence identity with gamma aminobutyric acid receptor. Here, our aim was to study the effect of structural corrections originating from modeling on a more reliable template structure. The homology model was analyzed for structural properties via a 100 ns molecular dynamics (MD) study. Due to the structural shifts and the removal of an open channel potentiator molecule, ivermectin, from the template structure, helical packing changes were observed in the transmembrane segment. Namely removal of ivermectin molecule caused a closure around the Leu 9 position along the ion channel. In terms of the structural shifts, there are three potential disulfide bridges between the M1 and M3 helices of the γ₂ and 2 α₁ subunits in the model. The effect of these disulfide bridges was investigated via monitoring the differences in root mean square fluctuations (RMSF) of individual amino acids and principal component analysis of the MD trajectory of the two homology models-one with the disulfide bridge and one with protonated Cys residues. In all subunit types, RMSF of the transmembrane domain helices are reduced in the presence of disulfide bridges. Additionally, loop A, loop F and loop C fluctuations were affected in the extracellular domain. In cross-correlation analysis of the trajectory, the two model structures displayed different coupling in between the M2-M3 linker region, protruding from the membrane, and the β1-β2/D loop and cys-loop regions in the extracellular domain. Correlations of the C loop, which collapses directly over the bound ligand molecule, were also affected by differences in the packing of transmembrane helices. Finally, more localized correlations were observed in the transmembrane helices when disulfide bridges were present in the model. The differences observed in this study suggest that dynamic coupling at the interface of extracellular and ion channel domains differs from the coupling introduced by disulfide bridges in the transmembrane region. We hope that this hypothesis will be tested experimentally in the near future.

An Electrostatic Funnel in the GABA-Binding Pathway

The γ-aminobutyric acid type A receptor (GABA_A-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABA_A-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABA_A-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABA_A-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site.

Neurotransmitters convey signals from one neuron to the next and are indispensable to the functioning of the nervous system. These small molecules bind to receptors to exert their action. One of the most important neurotransmitters is γ-aminobutyric acid (GABA), which binds to its type A receptor to exert an inhibitory influence on the neuron. Many drugs, both medicinal and nefarious, bind to these neuroreceptors and alter the balance of neuronal signals in the brain. There is a fine balance between these drugs eliciting the desired effect, and causing unwanted and sometimes irreversible alterations in neural behavior. To study this critical binding event, we are using computational simulations to observe precisely how the GABA molecule binds to its type A receptor (GABA_A-receptor). One hundred individual simulations were carried out where GABA was placed near the binding site and then allowed to freely bind to the GABA_A-receptor. Binding occurred in 19 of these simulations. Statistical analysis of these binding simulations reveals the consistent pathway taken by GABA molecules to enter the binding site. This improved understanding of the binding event enables development of safer medicinal neuroactive drugs and countermeasures for effects of neuronal chemical trauma.

A predicted binding site for cholesterol on the GABAA receptor

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.

Pentameric Ligand-gated Ion Channels : Insights from Computation

Pentameric ligand-gated ion channels (pLGICs) conduct upon the binding of an agonist and are fundamental to neurotransmission. New insights into the complex mechanisms underlying pLGIC gating, ion selectivity, and modulation have recently been gained via a series of crystal structures in prokaryotes and C .elegans, as well as computational studies relying on these structures. Here we review contributions from a variety of computational approaches, including normal mode analysis, automated docking, and fully atomistic molecular dynamics simulation. Examples from our own research, particularly concerning interactions with general anesthetics and lipids, are used to illustrate predictive results complementary to crystallographic studies.

Probing the orthosteric binding site of GABAA receptors with heterocyclic GABA carboxylic acid bioisosteres

The ionotropic GABAA receptors (GABAARs) are widely distributed in the central nervous system where they play essential roles in numerous physiological and pathological processes. A high degree of structural heterogeneity of the GABAAR has been revealed and extensive effort has been made to develop selective and potent GABAAR agonists. This review investigates the use of heterocyclic carboxylic acid bioisosteres within the GABAAR area. Several heterocycles including 3-hydroxyisoxazole, 3-hydroxyisoxazoline, 3-hydroxyisothiazole, and the 1- and 3-hydroxypyrazole rings have been employed in order to map the orthosteric binding site. The physicochemical properties of the heterocyclic moieties making them suitable for bioisosteric replacement of the carboxylic acid in the molecule of GABA are discussed. A variety of synthetic strategies for synthesis of the heterocyclic scaffolds are available. Likewise, methods for introduction of substituents into specific positions of the heterocyclic scaffolds facilitate the investigation of different regions in the orthosteric binding pocket in close vicinity of the core scaffolds of muscimol/GABA. The development of structural models, from pharmacophore models to receptor homology models, has provided more insight into the molecular basis for binding. Similar binding modes are proposed for the heterocyclic GABA analogues covered in this review by use of ligand-receptor docking into the receptor homology model and the presented structure-activity relationships. A network of interactions between the analogues and the binding pocket is leaving no room for substituents and underline the limited space in the GABAAR orthosteric binding site when in the agonist conformation.

Identification of a possible secondary picrotoxin-binding site on the GABA(A) receptor

The type A GABA receptors (GABARs) are ligand-gated ion channels (LGICs) found in the brain and are the major inhibitory neurotransmitter receptors. Upon binding of an agonist, the GABAR opens and increases the intraneuronal concentration of chloride ions, thus hyperpolarizing the cell and inhibiting the transmission of the nerve action potential. GABARs also contain many other modulatory binding pockets that differ from the agonist-binding site. The composition of the GABAR subunits can alter the properties of these modulatory sites. Picrotoxin is a noncompetitive antagonist for LGICs, and by inhibiting GABAR, picrotoxin can cause overstimulation and induce convulsions. We use addition of picrotoxin to probe the characteristics and possible mechanism of an additional modulatory pocket located at the interface between the ligand-binding domain and the transmembrane domain of the GABAR. Picrotoxin is widely regarded as a pore-blocking agent that acts at the cytoplasmic end of the channel. However, there are also data to suggest that there may be an additional, secondary binding site for picrotoxin. Through homology modeling, molecular docking, and molecular dynamics simulations, we show that binding of picrotoxin to this interface pocket correlates with these data, and negative modulation occurs at the pocket via a kinking of the pore-lining helices into a more closed orientation.

A unified model of the GABA(A) receptor comprising agonist and benzodiazepine binding sites

We present a full-length α(1)β(2)γ(2) GABA receptor model optimized for agonists and benzodiazepine (BZD) allosteric modulators. We propose binding hypotheses for the agonists GABA, muscimol and THIP and for the allosteric modulator diazepam (DZP). The receptor model is primarily based on the glutamate-gated chloride channel (GluCl) from C. elegans and includes additional structural information from the prokaryotic ligand-gated ion channel ELIC in a few regions. Available mutational data of the binding sites are well explained by the model and the proposed ligand binding poses. We suggest a GABA binding mode similar to the binding mode of glutamate in the GluCl X-ray structure. Key interactions are predicted with residues α(1)R66, β(2)T202, α(1)T129, β(2)E155, β(2)Y205 and the backbone of β(2)S156. Muscimol is predicted to bind similarly, however, with minor differences rationalized with quantum mechanical energy calculations. Muscimol key interactions are predicted to be α(1)R66, β(2)T202, α(1)T129, β(2)E155, β(2)Y205 and β(2)F200. Furthermore, we argue that a water molecule could mediate further interactions between muscimol and the backbone of β(2)S156 and β(2)Y157. DZP is predicted to bind with interactions comparable to those of the agonists in the orthosteric site. The carbonyl group of DZP is predicted to interact with two threonines α(1)T206 and γ(2)T142, similar to the acidic moiety of GABA. The chlorine atom of DZP is placed near the important α(1)H101 and the N-methyl group near α(1)Y159, α(1)T206, and α(1)Y209. We present a binding mode of DZP in which the pending phenyl moiety of DZP is buried in the binding pocket and thus shielded from solvent exposure. Our full length GABA(A) receptor is made available as Model S1.

GABA binding to an insect GABA receptor: a molecular dynamics and mutagenesis study

RDL receptors are GABA-activated inhibitory Cys-loop receptors found throughout the insect CNS. They are a key target for insecticides. Here, we characterize the GABA binding site in RDL receptors using computational and electrophysiological techniques. A homology model of the extracellular domain of RDL was generated and GABA docked into the binding site. Molecular dynamics simulations predicted critical GABA binding interactions with aromatic residues F206, Y254, and Y109 and hydrophilic residues E204, S176, R111, R166, S176, and T251. These residues were mutated, expressed in Xenopus oocytes, and their functions assessed using electrophysiology. The data support the binding mechanism provided by the simulations, which predict that GABA forms many interactions with binding site residues, the most significant of which are cation-π interactions with F206 and Y254, H-bonds with E204, S205, R111, S176, T251, and ionic interactions with R111 and E204. These findings clarify the roles of a range of residues in binding GABA in the RDL receptor, and also show that molecular dynamics simulations are a useful tool to identify specific interactions in Cys-loop receptors.

A role for loop F in modulating GABA binding affinity in the GABA(A) receptor

The brain's major inhibitory neuroreceptor is the ligand-gated ion channel γ-aminobutyric acid (GABA) type A receptor (GABAR). GABARs exist in a variety of different subunit combinations that act to modulate the physiological behavior of GABAR by altering its pharmacological profile, as well as its affinity for GABA. While the α(1)β(2)γ(2) subtype is one of the most prevalent GABARs, the less populous α(6)β(3)δ subtype has much higher GABA sensitivity. Previous studies identified residues crucial for GABA binding; however, the specific molecular differences responsible for this diverse sensitivity are not known. Furthermore, the role of loop F is a divisive subject, with conflicting evidence for ligand binding function. Using homology modeling, ligand docking, and molecular dynamics simulations, we investigated the GABA binding sites of the two receptor subtypes. Simulations identified seven residues that consistently interacted with GABA in both subtypes: αF65, αR132, βL99, βE155, βR/K196, βY205, and βR207. Residue substitution at position β196 (arginine in α(6)β(3)δ, lysine in α(1)β(2)γ(2)) resulted in a shift in GABA binding. However, the major difference between the two binding sites was the magnitude of loop F involvement, with a greater contribution in the α(6)β(3)δ receptor. Free energy calculations confirm that the α(6)β(3)δ binding pocket has an increased affinity for GABA. Thus, the possible role for loop F across the GABAR family is to modulate GABA affinity.

The energetic consequences of loop 9 gating motions in acetylcholine receptor-channels

Acetylcholine receptor-channels (AChRs) mediate fast synaptic transmission between nerve and muscle. In order to better-understand the mechanism by which this protein assembles and isomerizes between closed- and open-channel conformations we measured changes in the diliganded gating equilibrium constant (E(2)) consequent to mutations of residues at the C-terminus of loop 9 (L9) in the α and ε subunits of mouse neuromuscular AChRs. These amino acids are close to two interesting interfaces, between the extracellular and transmembrane domain within a subunit (E–T interface) and between primary and complementary subunits (P–C interface). Most α subunit mutations modestly decreased E(2) (mainly by slowing the channel-opening rate constant) and sometimes produced AChRs that had heterogeneous gating kinetic properties. Mutations in the ε subunit had a larger effect and could either increase or decrease E(2), but did not induce kinetic heterogeneity. There are broad-but-weak energetic interactions between αL9 residues and others at the αE–T interface, as well as between the εL9 residue and others at the P–C interface (in particular, the M2–M3 linker). These interactions serve, in part, to maintain the structural integrity of the AChR assembly at the E–T interface. Overall, the energy changes of L9 residues are significant but smaller than in other regions of the protein.

New insights into the GABA(A) receptor structure and orthosteric ligand binding: receptor modeling guided by experimental data

GABA(A) receptors (GABA(A)Rs) are ligand gated chloride ion channels that mediate overall inhibitory signaling in the CNS. A detailed understanding of their structure is important to gain insights in, e.g., ligand binding and functional properties of this pharmaceutically important target. Homology modeling is a necessary tool in this regard because experimentally determined structures are lacking. Here we present an exhaustive approach for creating a high quality model of the α(1)β(2)γ(2) subtype of the GABA(A)R ligand binding domain, and we demonstrate its usefulness in understanding details of orthosteric ligand binding. The model was constructed by using multiple templates and by incorporation of knowledge from biochemical/pharmacological experiments. It was validated on the basis of objective energy functions, its ability to account for available residue specific information, and its stability in molecular dynamics (MD) compared with that of the two homologous crystal structures. We then combined the model with extensive structure-activity relationships available from two homologous series of orthosteric GABA(A)R antagonists to create a detailed hypothesis for their binding modes. Excellent agreement with key experimental data was found, including the ability of the model to accommodate and explain a previously developed pharmacophore model. A coupling to agonist binding was thereby established and discussed in relation to activation mechanisms. Our results highlight the importance of critical evaluation and optimization of each step in the homology modeling process. The approach taken here can greatly aid in increasing the understanding of GABA(A)Rs and related receptors where structural insight is limited and reliable models are difficult to obtain.

Decrypting the sequence of structural events during the gating transition of pentameric ligand-gated ion channels based on an interpolated elastic network model

Despite many experimental and computational studies of the gating transition of pentameric ligand-gated ion channels (pLGICs), the structural basis of how ligand binding couples to channel gating remains unknown. By using a newly developed interpolated elastic network model (iENM), we have attempted to compute a likely transition pathway from the closed- to the open-channel conformation of pLGICs as captured by the crystal structures of two prokaryotic pLGICs. The iENM pathway predicts a sequence of structural events that begins at the ligand-binding loops and is followed by the displacements of two key loops (loop 2 and loop 7) at the interface between the extracellular and transmembrane domain, the tilting/bending of the pore-lining M2 helix, and subsequent movements of M4, M3 and M1 helices in the transmembrane domain. The predicted order of structural events is in broad agreement with the Φ-value analysis of α subunit of nicotinic acetylcholine receptor mutants, which supports a conserved core mechanism for ligand-gated channel opening in pLGICs. Further perturbation analysis has supported the critical role of certain intra-subunit and inter-subunit interactions in dictating the above sequence of events.

A state-dependent salt-bridge interaction exists across the β/α intersubunit interface of the GABAA receptor

The GABA(A) receptor is a multisubunit protein that transduces the binding of a neurotransmitter at an intersubunit interface into the opening of a central ion channel. The structural components that mediate the steps involved in this action are poorly defined. A large amount of work has focused on clarifying the specific functions and interactions of residues believed to surround the GABA binding pocket. Here, we explored two charged residues (β(2)Asp163 and α(1)Arg120), which have been suggested by homology models to participate in a salt-bridge interaction. When mutated to alanine, both single mutants, as well as the double mutant, increase EC(50-GABA), decrease the GABA binding rate, and accelerate deactivation and GABA unbinding rates. Double-mutant cycle analysis demonstrates that the effects of each alanine mutation on the GABA binding rate were additive and independent. In contrast, a significant coupling energy was found during an analysis of deactivation time constants. Using kinetic modeling, we further demonstrated that the GABA unbinding rates, in particular, are strongly coupled. These data suggest that β(2)Asp163 and α(1)Arg120 form a state-dependent salt bridge, interacting when GABA is bound to the receptor but not when the receptor is in the unbound state.

Molecular dynamics simulation studies of GLUT4: substrate-free and substrate-induced dynamics and ATP-mediated glucose transport inhibition

Background

Glucose transporter 4 (GLUT4) is an insulin facilitated glucose transporter that plays an important role in maintaining blood glucose homeostasis. GLUT4 is sequestered into intracellular vesicles in unstimulated cells and translocated to the plasma membrane by various stimuli. Understanding the structural details of GLUT4 will provide insights into the mechanism of glucose transport and its regulation. To date, a crystal structure for GLUT4 is not available. However, earlier work from our laboratory proposed a well validated homology model for GLUT4 based on the experimental data available on GLUT1 and the crystal structure data obtained from the glycerol 3-phosphate transporter.

Methodology/Principal Findings

In the present study, the dynamic behavior of GLUT4 in a membrane environment was analyzed using three forms of GLUT4 (apo, substrate and ATP-substrate bound states). Apo form simulation analysis revealed an extracellular open conformation of GLUT4 in the membrane favoring easy exofacial binding of substrate. Simulation studies with the substrate bound form proposed a stable state of GLUT4 with glucose, which can be a substrate-occluded state of the transporter. Principal component analysis suggested a clockwise movement for the domains in the apo form, whereas ATP substrate-bound form induced an anti-clockwise rotation. Simulation studies suggested distinct conformational changes for the GLUT4 domains in the ATP substrate-bound form and favor a constricted behavior for the transport channel. Various inter-domain hydrogen bonds and switching of a salt-bridge network from E345-R350-E409 to E345-R169-E409 contributed to this ATP-mediated channel constriction favoring substrate occlusion and prevention of its release into cytoplasm. These data are consistent with the biochemical studies, suggesting an inhibitory role for ATP in GLUT-mediated glucose transport.

Conclusions/Significance

In the absence of a crystal structure for any glucose transporter, this study provides mechanistic details of the conformational changes in GLUT4 induced by substrate and its regulator.