Activation mechanism of the class D fungal GPCR dimer Ste2.

The fungal class D1 G-protein-coupled receptor (GPCR) Ste2 has a different arrangement of transmembrane helices compared with mammalian GPCRs and a distinct mode of coupling to the heterotrimeric G protein Gpa1-Ste2-Ste181. In addition, Ste2 lacks conserved sequence motifs such as DRY, PIF and NPXXY, which are associated with the activation of class A GPCRs2. This suggested that the activation mechanism of Ste2 may also differ. Here we determined structures of Saccharomyces cerevisiae Ste2 in the absence of G protein in two different conformations bound to the native agonist α-factor, bound to an antagonist and without ligand. These structures revealed that Ste2 is indeed activated differently from other GPCRs. In the inactive state, the cytoplasmic end of transmembrane helix H7 is unstructured and packs between helices H1-H6, blocking the G protein coupling site. Agonist binding results in the outward movement of the extracellular ends of H6 and H7 by 6 Å. On the intracellular surface, the G protein coupling site is formed by a 20 Å outward movement of the unstructured region in H7 that unblocks the site, and a 12 Å inward movement of H6. This is a distinct mechanism in GPCRs, in which the movement of H6 and H7 upon agonist binding facilitates G protein coupling.

Data-driven regularization lowers the size barrier of cryo-EM structure determination.

Macromolecular structure determination by electron cryo-microscopy (cryo-EM) is limited by the alignment of noisy images of individual particles. Because smaller particles have weaker signals, alignment errors impose size limitations on its applicability. Here, we explore how image alignment is improved by the application of deep learning to exploit prior knowledge about biological macromolecular structures that would otherwise be difficult to express mathematically. We train a denoising convolutional neural network on pairs of half-set reconstructions from the electron microscopy data bank (EMDB) and use this denoiser as an alternative to a commonly used smoothness prior. We demonstrate that this approach, which we call Blush regularization, yields better reconstructions than do existing algorithms, in particular for data with low signal-to-noise ratios. The reconstruction of a protein-nucleic acid complex with a molecular weight of 40 kDa, which was previously intractable, illustrates that denoising neural networks will expand the applicability of cryo-EM structure determination for a wide range of biological macromolecules.

Structure of the class D GPCR Ste2 dimer coupled to two G proteins.

G-protein-coupled receptors (GPCRs) are divided phylogenetically into six classes1,2, denoted A to F. More than 370 structures of vertebrate GPCRs (belonging to classes A, B, C and F) have been determined, leading to a substantial understanding of their function3. By contrast, there are no structures of class D GPCRs, which are found exclusively in fungi where they regulate survival and reproduction. Here we determine the structure of a class D GPCR, the Saccharomyces cerevisiae pheromone receptor Ste2, in an active state coupled to the heterotrimeric G protein Gpa1-Ste4-Ste18. Ste2 was purified as a homodimer coupled to two G proteins. The dimer interface of Ste2 is formed by the N terminus, the transmembrane helices H1, H2 and H7, and the first extracellular loop ECL1. We establish a class D1 generic residue numbering system (CD1) to enable comparisons with orthologues and with other GPCR classes. The structure of Ste2 bears similarities in overall topology to class A GPCRs, but the transmembrane helix H4 is shifted by more than 20 Å and the G-protein-binding site is a shallow groove rather than a cleft. The structure provides a template for the design of novel drugs to target fungal GPCRs, which could be used to treat numerous intractable fungal diseases4.

Developing novel antifungals: lessons from G protein-coupled receptors.

Up to 1.5 million people die yearly from fungal disease, but the repertoire of antifungal drug classes is minimal and the incidence of drug resistance is rising rapidly. This dilemma was recently declared by the World Health Organization as a global health emergency, but the discovery of new antifungal drug classes remains excruciatingly slow. This process could be accelerated by focusing on novel targets, such as G protein-coupled receptor (GPCR)-like proteins, that have a high likelihood of being druggable and have well-defined biology and roles in disease. We discuss recent successes in understanding the biology of virulence and in structure determination of yeast GPCRs, and highlight new approaches that might pay significant dividends in the urgent search for novel antifungal drugs.

Dietary flavonoid fisetin binds human SUMO1 and blocks sumoylation of p53.

Flavonoids are plant-derived compounds that occur abundantly in fruits and vegetables and have been shown to possess potent anti-cancer, antioxidant, and anti-inflammatory properties. However, their direct targets and molecular mechanism of action are not well characterized, hampering exploitation of the beneficial properties of flavonoids for drug development. Small ubiquitin-related modifier 1 (SUMO1) is attached to target proteins as part of a post-translational modification system implicated in a myriad of cellular processes from nuclear trafficking to transcriptional regulation. Using a combination of surface plasmon resonance, differential scanning fluorimetry and fluorescence quenching studies, we provide evidence for direct binding of the dietary flavonoid fisetin to human SUMO1. Our NMR chemical shift perturbation analyses reveal that binding to fisetin involves four conserved amino acid residues (L65, F66, E67, M82) previously shown to be important for conjugation of SUMO1 to target proteins. In vitro sumoylation experiments indicate that fisetin blocks sumoylation of tumor suppressor p53, consistent with fisetin negatively affecting post-translational modification and thus the biological activity of p53. A series of differential scanning fluorimetry experiments suggest that high concentrations of fisetin result in destabilization and unfolding of SUMO1, presenting a molecular mechanism by which flavonoid binding affects its activity. Overall, our data establish a novel direct interaction between fisetin and SUMO1, providing a mechanistic explanation for the ability of fisetin to modulate multiple key signaling pathways inside cells.