Gi- and Gs-coupled GPCRs show different modes of G-protein binding.

More than two decades ago, the activation mechanism for the membrane-bound photoreceptor and prototypical G protein-coupled receptor (GPCR) rhodopsin was uncovered. Upon light-induced changes in ligand-receptor interaction, movement of specific transmembrane helices within the receptor opens a crevice at the cytoplasmic surface, allowing for coupling of heterotrimeric guanine nucleotide-binding proteins (G proteins). The general features of this activation mechanism are conserved across the GPCR superfamily. Nevertheless, GPCRs have selectivity for distinct G-protein family members, but the mechanism of selectivity remains elusive. Structures of GPCRs in complex with the stimulatory G protein, Gs, and an accessory nanobody to stabilize the complex have been reported, providing information on the intermolecular interactions. However, to reveal the structural selectivity filters, it will be necessary to determine GPCR-G protein structures involving other G-protein subtypes. In addition, it is important to obtain structures in the absence of a nanobody that may influence the structure. Here, we present a model for a rhodopsin-G protein complex derived from intermolecular distance constraints between the activated receptor and the inhibitory G protein, Gi, using electron paramagnetic resonance spectroscopy and spin-labeling methodologies. Molecular dynamics simulations demonstrated the overall stability of the modeled complex. In the rhodopsin-Gi complex, Gi engages rhodopsin in a manner distinct from previous GPCR-Gs structures, providing insight into specificity determinants

A review of High Performance Computing foundations for scientists

The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [1, 2]. Simulation enables the evaluation of quantities which otherwise would not be accessible, helps to improve experiments and provides new insights on systems which are analysed [3-6]. Knowing the fundamentals of computation can be very useful for scientists, for it can help them to improve the performance of their theoretical models and simulations. This review includes some technical essentials that can be useful to this end, and it is devised as a complement for researchers whose education is focused on scientific issues and not on technological respects. In this document we attempt to discuss the fundamentals of High Performance Computing (HPC) [7] in a way which is easy to understand without much previous background. We sketch the way standard computers and supercomputers work, as well as discuss distributed computing and discuss essential aspects to take into account when running scientific calculations in computers.Comment: 33 page

Frateuria defendens reduces yellows disease symptoms in grapevine under field conditions

Yellows diseases in grapevine, associated with the presence of different phytoplasmas, are a major problem for growers, with no environmentally friendly means of control. Frateuria defendens (Frd), a bacterium with endophytic traits, has been shown to reduce yellows symptoms in grapevine plantlets under laboratory conditions. The objective of this study was to test whether similar effects could be achieved under field conditions. A trial was conducted in a heavily infected vineyard in northern Israel for two consecutive years. A suspension of Frd cells (108·mL-1) was applied bi-weekly by foliar spray on grapevines from bud burst to leaf senescence. Frd penetrated the leaves during the growing period but not during leaf senescence and could be detected in the leaves by PCR analysis up to 14 days post-spraying. The rate of yellows infection was lower in the treated grapevines compared to its increase in untreated grapevines and the yield of symptomatic plants was improved by 10 to 20 %. Taken together, the results suggest Frd acted as a biological control agent in vineyards under the experimental conditions tested

Structural basis for chemokine recognition and activation of a viral G protein-coupled receptor

Chemokines are small proteins that function as immune modulators through activation of chemokine G protein–coupled receptors (GPCRs). Several viruses also encode chemokines and chemokine receptors to subvert the host immune response. How protein ligands activate GPCRs remains unknown. We report the crystal structure at 2.9 angstrom resolution of the human cytomegalovirus GPCR US28 in complex with the chemokine domain of human CX3CL1 (fractalkine). The globular body of CX3CL1 is perched on top of the US28 extracellular vestibule, whereas its amino terminus projects into the central core of US28. The transmembrane helices of US28 adopt an active-state–like conformation. Atomic-level simulations suggest that the agonist-independent activity of US28 may be due to an amino acid network evolved in the viral GPCR to destabilize the receptor’s inactive state.Swiss National Science FoundationNational Institutes of Health (U.S.) (Pioneer Award)Virginia and D.K. Ludwig Fund for Cancer Researc

Spot the difference: Comparing results of analyses from real patient data and synthetic derivatives

BACKGROUND: Synthetic data may provide a solution to researchers who wish to generate and share data in support of precision healthcare. Recent advances in data synthesis enable the creation and analysis of synthetic derivatives as if they were the original data; this process has significant advantages over data deidentification. OBJECTIVES: To assess a big-data platform with data-synthesizing capabilities (MDClone Ltd., Beer Sheva, Israel) for its ability to produce data that can be used for research purposes while obviating privacy and confidentiality concerns. METHODS: We explored three use cases and tested the robustness of synthetic data by comparing the results of analyses using synthetic derivatives to analyses using the original data using traditional statistics, machine learning approaches, and spatial representations of the data. We designed these use cases with the purpose of conducting analyses at the observation level (Use Case 1), patient cohorts (Use Case 2), and population-level data (Use Case 3). RESULTS: For each use case, the results of the analyses were sufficiently statistically similar ( DISCUSSION AND CONCLUSION: This article presents the results of each use case and outlines key considerations for the use of synthetic data, examining their role in clinical research for faster insights and improved data sharing in support of precision healthcare

On the Current Carried by `Neutral' Quasiparticles

The current should be proportional to the momentum in a Galilean-invariant system of particles of fixed charge-to-mass ratio, such as an electron liquid in jellium. However, strongly-interacting electron systems can have phases characterized by broken symmetry or fractionalization. Such phases can have neutral excitations which can presumably carry momentum but not current. In this paper, we show that there is no contradiction: `neutral' excitations {\em do} carry current in a Galilean-invariant system of particles of fixed charge-to-mass ratio. This is explicitly demonstrated in the context of spin waves, the Bogoliubov-de Gennes quasiparticles of a superconductor, the one-dimensional electron gas, and spin-charge separated systems in 2+1 dimensions. We discuss the implications for more realistic systems, which are not Galilean-invariant

Identifying Ligand Binding Conformations of the β2-Adrenergic Receptor by Using Its Agonists as Computational Probes

Recently available G-protein coupled receptor (GPCR) structures and biophysical studies suggest that the difference between the effects of various agonists and antagonists cannot be explained by single structures alone, but rather that the conformational ensembles of the proteins need to be considered. Here we use an elastic network model-guided molecular dynamics simulation protocol to generate an ensemble of conformers of a prototypical GPCR, β2-adrenergic receptor (β2AR). The resulting conformers are clustered into groups based on the conformations of the ligand binding site, and distinct conformers from each group are assessed for their binding to known agonists of β2AR. We show that the select ligands bind preferentially to different predicted conformers of β2AR, and identify a role of β2AR extracellular region as an allosteric binding site for larger drugs such as salmeterol. Thus, drugs and ligands can be used as "computational probes" to systematically identify protein conformers with likely biological significance. © 2012 Isin et al