Oxidation Resistance 1 Modulates Glycolytic Pathways in the Cerebellum via an Interaction with Glucose-6-Phosphate Isomerase.

Glucose metabolism is essential for the brain: it not only provides the required energy for cellular function and communication but also participates in balancing the levels of oxidative stress in neurons. Defects in glucose metabolism have been described in neurodegenerative disease; however, it remains unclear how this fundamental process contributes to neuronal cell death in these disorders. Here, we investigated the molecular mechanisms driving the selective neurodegeneration in an ataxic mouse model lacking oxidation resistance 1 (Oxr1) and discovered an unexpected function for this protein as a regulator of the glycolytic enzyme, glucose-6-phosphate isomerase (GPI/Gpi1). Initially, we present a dysregulation of metabolites of glucose metabolism at the pre-symptomatic stage in the Oxr1 knockout cerebellum. We then demonstrate that Oxr1 and Gpi1 physically and functionally interact and that the level of Gpi1 oligomerisation is disrupted when Oxr1 is deleted in vivo. Furthermore, we show that Oxr1 modulates the additional and less well-understood roles of Gpi1 as a cytokine and neuroprotective factor. Overall, our data identify a new molecular function for Oxr1, establishing this protein as important player in neuronal survival, regulating both oxidative stress and glucose metabolism in the brain.

Activation of Toll-like receptors nucleates assembly of the MyDDosome signaling hub.

Infection and tissue damage induces assembly of supramolecular organizing centres (SMOCs)), such as the Toll-like receptor (TLR) MyDDosome, to co-ordinate inflammatory signaling. SMOC assembly is thought to drive digital all-or-none responses, yet TLR activation by diverse microbes induces anything from mild to severe inflammation. Using single-molecule imaging of TLR4-MyDDosome signaling in living macrophages, we find that MyDDosomes assemble within minutes of TLR4 stimulation. TLR4/MD2 activation leads only to formation of TLR4/MD2 heterotetramers, but not oligomers, suggesting a stoichiometric mismatch between activated receptors and MyDDosomes. The strength of TLR4 signalling depends not only on the number and size of MyDDosomes formed but also how quickly these structures assemble. Activated TLR4, therefore, acts transiently nucleating assembly of MyDDosomes, a process that is uncoupled from receptor activation. These data explain how the oncogenic mutation of MyD88 (L265P) assembles MyDDosomes in the absence of receptor activation to cause constitutive activation of pro-survival NF-κB signalling.

Insights into channel dysfunction from modelling and molecular dynamics simulations.

Developments in structural biology mean that the number of different ion channel structures has increased significantly in recent years. Structures of ion channels enable us to rationalize how mutations may lead to channelopathies. However, determining the structures of ion channels is still not trivial, especially as they necessarily exist in many distinct functional states. Therefore, the use of computational modelling can provide complementary information that can refine working hypotheses of both wild type and mutant ion channels. The simplest but still powerful tool is homology modelling. Many structures are available now that can provide suitable templates for many different types of ion channels, allowing a full three-dimensional interpretation of mutational effects. These structural models, and indeed the structures themselves obtained by X-ray crystallography, and more recently cryo-electron microscopy, can be subjected to molecular dynamics simulations, either as a tool to help explore the conformational dynamics in detail or simply as a means to refine the models further. Here we review how these approaches have been used to improve our understanding of how diseases might be linked to specific mutations in ion channel proteins. This article is part of the Special Issue entitled 'Channelopathies.'

Functional Validation of Heteromeric Kainate Receptor Models.

Kainate receptors require the presence of external ions for gating. Most work thus far has been performed on homomeric GluK2 but, in vivo, kainate receptors are likely heterotetramers. Agonists bind to the ligand-binding domain (LBD) which is arranged as a dimer of dimers as exemplified in homomeric structures, but no high-resolution structure currently exists of heteromeric kainate receptors. In a full-length heterotetramer, the LBDs could potentially be arranged either as a GluK2 homomer alongside a GluK5 homomer or as two GluK2/K5 heterodimers. We have constructed models of the LBD dimers based on the GluK2 LBD crystal structures and investigated their stability with molecular dynamics simulations. We have then used the models to make predictions about the functional behavior of the full-length GluK2/K5 receptor, which we confirmed via electrophysiological recordings. A key prediction and observation is that lithium ions bind to the dimer interface of GluK2/K5 heteromers and slow their desensitization.

Energetics of Endotoxin Recognition in the Toll-Like Receptor 4 Innate Immune Response.

Bacterial outer membrane lipopolysaccharide (LPS) potently stimulates the mammalian innate immune system, and can lead to sepsis, the primary cause of death from infections. LPS is sensed by Toll-like receptor 4 (TLR4) in complex with its lipid-binding coreceptor MD-2, but subtle structural variations in LPS can profoundly modulate the response. To better understand the mechanism of LPS-induced stimulation and bacterial evasion, we have calculated the binding affinity to MD-2 of agonistic and antagonistic LPS variants including lipid A, lipid IVa, and synthetic antagonist Eritoran, and provide evidence that the coreceptor is a molecular switch that undergoes ligand-induced conformational changes to appropriately activate or inhibit the receptor complex. The plasticity of the coreceptor binding cavity is shown to be essential for distinguishing between ligands, whilst similar calculations for a model bacterial LPS bilayer reveal the "membrane-like" nature of the protein cavity. The ability to predict the activity of LPS variants should facilitate the rational design of TLR4 therapeutics.

Efficient Characterization of Protein Cavities within Molecular Simulation Trajectories: trj_cavity.

Protein cavities and tunnels are critical in determining phenomena such as ligand binding, molecular transport, and enzyme catalysis. Molecular dynamics (MD) simulations enable the exploration of the flexibility and conformational plasticity of protein cavities, extending the information available from static experimental structures relevant to, for example, drug design. Here, we present a new tool (trj_cavity) implemented within the GROMACS ( www.gromacs.org ) framework for the rapid identification and characterization of cavities detected within MD trajectories. trj_cavity is optimized for usability and computational efficiency and is applicable to the time-dependent analysis of any cavity topology, and optional specialized descriptors can be used to characterize, for example, protein channels. Its novel grid-based algorithm performs an efficient neighbor search whose calculation time is linear with system size, and a comparison of performance with other widely used cavity analysis programs reveals an orders-of-magnitude improvement in the computational cost. To demonstrate its potential for revealing novel mechanistic insights, trj_cavity has been used to analyze long-time scale simulation trajectories for three diverse protein cavity systems. This has helped to reveal, respectively, the lipid binding mechanism in the deep hydrophobic cavity of a soluble mite-allergen protein, Der p 2; a means for shuttling carbohydrates between the surface-exposed substrate-binding and catalytic pockets of a multidomain, membrane-proximal pullulanase, PulA; and the structural basis for selectivity in the transmembrane pore of a voltage-gated sodium channel (NavMs), embedded within a lipid bilayer environment. trj_cavity is available for download under an open-source license ( http://sourceforge.net/projects/trjcavity ). A simplified, GROMACS-independent version may also be compiled.

The structural basis for endotoxin-induced allosteric regulation of the Toll-like receptor 4 (TLR4) innate immune receptor.

As part of the innate immune system, Toll-like receptor 4 (TLR4) recognizes bacterial cell surface lipopolysaccharide (LPS) by forming a complex with a lipid-binding co-receptor, MD-2. In the presence of agonist, TLR4·MD-2 dimerizes to form an active receptor complex, leading to initiation of intracellular inflammatory signals. TLR4 is of great biomedical interest, but its pharmacological manipulation is complicated because even subtle variations in the structure of LPS can profoundly impact the resultant immunological response. Here, we use atomically detailed molecular simulations to gain insights into the nature of the molecular signaling mechanism. We first demonstrate that MD-2 is extraordinarily flexible. The "clamshell-like" motions of its ß-cup fold enable it to sensitively match the volume of its hydrophobic cavity to the size and shape of the bound lipid moiety. We show that MD-2 allosterically transmits this conformational plasticity, in a ligand-dependent manner, to a phenylalanine residue (Phe-126) at the cavity mouth previously implicated in TLR4 activation. Remarkably, within the receptor complex, we observe spontaneous transitions between active and inactive signaling states of Phe-126, and we confirm that Phe-126 is indeed the "molecular switch" in endotoxic signaling.

The simulation approach to lipid-protein interactions.

The interactions between lipids and proteins are crucial for a range of biological processes, from the folding and stability of membrane proteins to signaling and metabolism facilitated by lipid-binding proteins. However, high-resolution structural details concerning functional lipid/protein interactions are scarce due to barriers in both experimental isolation of native lipid-bound complexes and subsequent biophysical characterization. The molecular dynamics (MD) simulation approach provides a means to complement available structural data, yielding dynamic, structural, and thermodynamic data for a protein embedded within a physiologically realistic, modelled lipid environment. In this chapter, we provide a guide to current methods for setting up and running simulations of membrane proteins and soluble, lipid-binding proteins, using standard atomistically detailed representations, as well as simplified, coarse-grained models. In addition, we outline recent studies that illustrate the power of the simulation approach in the context of biologically relevant lipid/protein interactions.