Ramon Guixà-González

Membrane omega-3 fatty acids modulate the oligomerisation kinetics of adenosine A2A and dopamine D2 receptors

Membrane levels of docosahexaenoic acid (DHA), an essential omega-3 polyunsaturated fatty acid (ω-3 PUFA), are decreased in common neuropsychiatric disorders. DHA modulates key cell membrane properties like fluidity, thereby affecting the behaviour of transmembrane proteins like G protein-coupled receptors (GPCRs). These receptors, which have special relevance for major neuropsychiatric disorders have recently been shown to form dimers or higher order oligomers, and evidence suggests that DHA levels affect GPCR function by modulating oligomerisation. In this study, we assessed the effect of membrane DHA content on the formation of a class of protein complexes with particular relevance for brain disease: adenosine A2A and dopamine D2 receptor oligomers. Using extensive multiscale computer modelling, we find a marked propensity of DHA for interaction with both A2A and D2 receptors, which leads to an increased rate of receptor oligomerisation. Bioluminescence resonance energy transfer (BRET) experiments performed on living cells suggest that this DHA effect on the oligomerisation of A2A and D2 receptors is purely kinetic. This work reveals for the first time that membrane ω-3 PUFAs play a key role in GPCR oligomerisation kinetics, which may have important implications for neuropsychiatric conditions like schizophrenia or Parkinson’s disease.

Novel Insights into Biased Agonism at G Protein-Coupled Receptors and their Potential for Drug Design

G-protein coupled receptors (GPCRs) are the most important class of current pharmacological targets. However, it is now widely acknowledged that their regulation is more complex than previously thought: the evidence that GPCRs can couple to several effector pathways, and the existence of biased agonists able to activate them differentially, has introduced a new level of complexity in GPCR drug research. Considering bias represents a challenge for the research of new GPCR modulators, because it demands a detailed characterization of compound properties for several effector pathways. Still, biased ligands could provide an opportunity to modulate GPCR function in a finer way and to separate therapeutic from side effects. Nowadays, a variety of agonists for GPCRs have been described, which differ in their ability to promote receptor coupling to different Gprotein families or even subunits, recruit signal transducers such as arrestins, activate a variety of downstream molecular pathways and induce certain phosphorylation signatures or gene expression patterns. In this review, we will cover some of the experimental techniques currently used to understand and characterize biased agonism and discuss their strengths and limitations. Additionally, we will comment on the computational efforts that are being devoted to study ligand-induced bias and on the potential they hold for rationalizing its structural determinants. Finally, we will discuss which of these strategies could be used for the rational design of biased ligands and give some examples of the potential therapeutic value of this class of compounds.

Membrane cholesterol access into a G-protein-coupled receptor

Cholesterol is a key component of cell membranes with a proven modulatory role on the function and ligand-binding properties of G-protein-coupled receptors (GPCRs). Crystal structures of prototypical GPCRs such as the adenosine A2A receptor (A2AR) have confirmed that cholesterol finds stable binding sites at the receptor surface suggesting an allosteric role of this lipid. Here we combine experimental and computational approaches to show that cholesterol can spontaneously enter the A2AR-binding pocket from the membrane milieu using the same portal gate previously suggested for opsin ligands. We confirm the presence of cholesterol inside the receptor by chemical modification of the A2AR interior in a biotinylation assay. Overall, we show that cholesterols impact on A2AR-binding affinity goes beyond pure allosteric modulation and unveils a new interaction mode between cholesterol and the A2AR that could potentially apply to other GPCRs.

Crosstalk within GPCR Heteromers in Schizophrenia and Parkinsons Disease: Physical or Just Functional?

Crosstalk between G protein-coupled receptors (GPCRs) is one of the key mechanisms used by the cell for integrating multiple signaling pathways. Functional crosstalk at the level of signaling pathways was initially thought to regulate receptor function. Importantly, the existence of GPCR heteromers demonstrates that direct physical interactions between GPCRs could also be behind the crosstalk phenomenon. Neurological disorders such as Parkinsons disease (PD) and schizophrenia have been linked to a dysfunctional communication between certain GPCRs. In this review, we discuss functional and physical crosstalk of the main GPCR families involved in the aforementioned disorders. In addition, we analyze the available structural information on physical crosstalk and highlight some strategies in drug discovery based on these crosstalk mechanisms.

Fractal dimension as a measure of surface roughness of G protein-coupled receptors: implications for structure and function

AbstractProtein surface roughness is a structural property associated with ligand-protein and protein-protein binding interfaces. In this work we apply for the first time the concept of surface roughness, expressed as the fractal dimension, to address structure and function of G protein-coupled receptors (GPCRs) which are an important group of drug targets. We calculate the exposure ratio and the fractal dimension for helix-forming residues of the β2 adrenergic receptor (β2AR), a model system in GPCR studies, in different conformational states: in complex with agonist, antagonist and partial inverse agonists. We show that both exposure ratio and roughness exhibit periodicity which results from the helical structure of GPCRs. The pattern of roughness and exposure ratio of a protein patch depends on its environment: the residues most exposed to membrane are in general most rough whereas parts of receptors mediating interhelical contacts in a monomer or protein complex are much smoother. We also find that intracellular ends (TM3, TM5, TM6 and TM7) which are relevant for G protein binding and thus receptor signaling, are exposed but smooth. Mapping the values of residual fractal dimension onto receptor 3D structures makes it possible to conclude that the binding sites of orthosteric ligands as well as of cholesterol are characterized with significantly higher roughness than the average for the whole protein. In summary, our study suggests that identification of specific patterns of roughness could be a novel approach to spot possible binding sites which could serve as original drug targets for GPCRs modulation. FigureThe significance of surface roughness for protein structure and function.

Multi-Component Protein - Protein Docking Based Protocol with External Scoring for Modeling Dimers of G Protein-Coupled Receptors.

In order to apply structure‐based drug design techniques to GPCR complexes, it is essential to model their 3D structure. For this purpose, a multi‐component protocol was derived based on protein‐protein docking which generates populations of dimers compatible with membrane integration, considering all reasonable interfaces. At the next stage, we applied a scoring procedure based on up to eleven different parameters including shape or electrostatics complementarity. Two methods of consensus scoring were performed: (i) average scores of 100 best scored dimers with respect to each interface, and (ii) frequencies of interfaces among 100 best scored dimers. In general, our multi‐component protocol gives correct indications for dimer interfaces that have been observed in X‐ray crystal structures of GPCR dimers (opsin dimer, chemokine CXCR4 and CCR5 dimers, κ opioid receptor dimer, β1 adrenergic receptor dimer and smoothened receptor dimer) but also suggests alternative dimerization interfaces. Interestingly, at times these alternative interfaces are scored higher than the experimentally observed ones suggesting them to be also relevant in the life cycle of studied GPCR dimers. Further results indicate that GPCR dimer and higher‐order oligomer formation may involve transmembrane helices (TMs) TM1‐TM2‐TM7, TM3‐TM4‐TM5 or TM4‐TM5‐TM6 but not TM1‐TM2‐TM3 or TM2‐TM3‐TM4 which is in general agreement with available experimental and computational data.

Rational design of the survivin/CDK4 complex by combining protein–protein docking and molecular dynamics simulations

AbstractSurvivin, the smallest inhibitor of apoptosis protein (IAP), is a valid target for cancer research. It mediates both the apoptosis pathway and the cell cycle and has been proposed to form a complex with the cyclin-dependent kinase protein CDK4. The resulting complex transports CDK4 from the cytosol to the nucleus, where CDK4 participates in cell division. Survivin has been recognized as a node protein that interacts with several partners; disruption of the formed complexes can lead to new anticancer compounds. We propose a rational model of the survivin/CDK4 complex that fulfills the experimental evidence and that can be used for structure-based design of inhibitors modifying its interface recognition. In particular, the suggested complex involves the alpha helical domain of survivin and resembles the mode of binding of survivin in the survivin/borealin X-ray structure. The proposed model has been obtained by combining protein–protein docking, fractal-based shape complementarity, electrostatics studies and extensive molecular dynamics simulations. FigureProposed model of the survivin/CDK4 complex with a close view of the best model refined through molecular dynamics simulations

Membrane cholesterol effect on the 5‐HT2A receptor: Insights into the lipid‐induced modulation of an antipsychotic drug target

The serotonin 5‐hydroxytryptamine 2A (5‐HT2A) receptor is a G‐protein‐coupled receptor (GPCR) relevant for the treatment of CNS disorders. In this regard, neuronal membrane composition in the brain plays a crucial role in the modulation of the receptor functioning. Since cholesterol is an essential component of neuronal membranes, we have studied its effect on the 5‐HT2A receptor dynamics through all‐atom MD simulations. We find that the presence of cholesterol in the membrane increases receptor conformational variability in most receptor segments. Importantly, detailed structural analysis indicates that conformational variability goes along with the destabilization of hydrogen bonding networks not only within the receptor but also between receptor and lipids. In addition to increased conformational variability, we also find receptor segments with reduced variability. Our analysis suggests that this increased stabilization is the result of stabilizing effects of tightly bound cholesterol molecules to the receptor surface. Our finding contributes to a better understanding of membrane‐induced alterations of receptor dynamics and points to cholesterol‐induced stabilizing and destabilizing effects on the conformational variability of GPCRs.

MDsrv: viewing and sharing molecular dynamics simulations on the web

To the Editor: Molecular dynamics (MD) simulations are a wellestablished technique to investigate time-resolved motions of biological macromolecules at atomic resolution1. Methodological advances, continued software optimization and hardware acceleration have broadened the applicability of MD simulations with respect to feasible system size, runtime and quality2. Coupled to these advances, availability of vast cloud storage is enabling the creation of MD trajectory databases3. However, accessing, viewing and sharing MD trajectories is restricted by large file sizes and the need for specialized software (e.g., VMD, Chimera, Schrodinger Suite Products), which greatly limits the audience to which the MD data are available. In light of increasingly interdisciplinary research and remote collaborations, it is desirable to make the atom trajectories of MD simulations widely available to facilitate interactive exploration and collaborative visual analysis as well as to promote discussions. While some tools exist for analysis or visualization of trajectories, none of these offers a straightforward and easy solution for sharing and viewing MD trajectories online (for a comparison, see Supplementary Note 1). Here, we present MDsrv, a tool to stream MD trajectories and show them interactively within web browsers without requiring advanced knowledge in specialized MD software (Fig. 1). MDsrv is available as a software package (via PyPi and conda, Supplementary Software) that can be run locally or deployed to a dedicated web server to make data from MD simulations accessible to a wide audience of researchers, which helps to facilitate collaboration between computational and experimental researchers (see Supplementary Note 1). For interactive and remote exploration of trajectories, we used client-server architecture to create a web-based platform. MDsrv can be used for viewing or serving MD simulations. The latter usage offers two modes of operation—one is an easy-to-use command-line tool for local service (Supplementary Fig. 1a); the other deploys the tool on a server to provide a dedicated streaming service (see Supplementary Notes 2–4). MDsrv supports structures, topologies and trajectories from common MD packages including Amber, Gromacs, NAMD, Tinker or Desmond. To aid visualization and analysis of MD trajectories, a number of processing steps can be performed on the structure and trajectory data (Supplementary Table 1). When analyzing MD simulations, the focus is generally on the internal motions of the macromolecule rather than on the diffusion movement in aqueous solution or lipid bilayers. To display unprocessed data from nascent simulations, on-the-fly superposition to a reference structure, handling of simulations with periodic boundary conditions and secondary structure assignment can be performed. By applying these calculations only to displayed frames, no scalability issues arise when viewing large structures and very long trajectories. Finally, to reduce the amount of transferred data, coordinate frames can be retrieved individually, and atoms from solvent or other, nonrelevant molecules can be filtered out before transferring a frame. Scalable molecular graphics for the MDsrv web application are provided by the NGL Viewer4. Accelerated 3D graphics are enabled by WebGL, a standard built directly into web browsers without requiring installation of plugins. NGL supports a wide Autodesk for supplying cardboard VR devices at international conferences. We thank the Canadian Institute for Advanced Research and the Canada Excellence Research Chairs program (both to O.P.E.) for financial support to attend and present at international conferences. O.P.E. holds the Anne and Max Tanenbaum Chair in Neuroscience.

Computational Strategies to Incorporate GPCR Complexity in Drug Design

Abstract: G protein-coupled receptors (GPCRs) represent the most important family of drug targets to date. However, state-of-the-art experimental procedures, able to characterize in deep both GPCR modulation in health and disease and the molecular mechanisms of drug action at these receptors, have provided a more nuanced picture than previously expected. Several aspects of GPCR function, which are currently being characterized, clarify some regulatory processes regarding these receptors and, at the same time, introduce novel levels of complexity which should be taken into consideration for rational drug design. In this scenario, computational approaches can help in several ways rationalize the increasing amount of data on GPCRs and their ligands. On the one hand, a set of databases devoted to these receptors provide excellent starting points for data mining. On the other, exploitation of the ever-increasing ligand and structure-based information by novel computational techniques can help addressing emerging questions in the GPCR field. Some of these questions comprise the refined modulation of GPCR signaling states by biased agonists, the exploitation of GPCR oligomers as drug targets, the analysis of polypharmacology in GPCR ligands, the development of strategies for receptor deorphanization or the prediction of off-target interactions of known drugs targeting these receptors. In this chapter, we will cover some of these strategies for knowledge-based rational design for GPCRs and will discuss the main hurdles which they may need to overcome to yield novel, safer and more efficacious drugs possessing polished mechanisms of action.