G—蛋白异三聚体（G—protein heterotrimer）的晶体结构

继１９９４年Ｓｉｇｌｅｒ－Ｈａｍｍ和Ｓｐｒａｎｇ－Ｇｉｌｍａｎ实验室报道Ｇｉα１的晶体结构之后,１９９５年１２月和１９９６年１月这两个实验室又相继报道了Ｇ－蛋白异三聚体（ＧαＧＤＰ）βγ和Ｇβγ二聚体的晶体结构,这些研究结果表明Ｇ－蛋白复合物象一台由操纵杆（受体）,开关（Ｇα）和螺旋浆（Ｇβγ）组成的信号转导纳米机器,并揭示了α和β亚基间可能存两种不同的功能界面,β和γ亚基间,α和γ的相互作用,以     

Dissecting Arabidopsis Gβ signal transduction on the protein surface

The heterotrimeric G-protein complex provides signal amplification and target specificity. The Arabidopsis (Arabidopsis thaliana) Gβ-subunit of this complex (AGB1) interacts with and modulates the activity of target cytoplasmic proteins. This specificity resides in the structure of the interface between AGB1 and its targets. Important surface residues of AGB1, which were deduced from a comparative evolutionary approach, were mutated to dissect AGB1-dependent physiological functions. Analysis of the capacity of these mutants to complement well-established phenotypes of Gβ-null mutants revealed AGB1 residues critical for specific AGB1-mediated biological processes, including growth architecture, pathogen resistance, stomata-mediated leaf-air gas exchange, and possibly photosynthesis. These findings provide promising new avenues to direct the finely tuned engineering of crop yield and traits.     

GPCR: G protein complexes—the fundamental signaling assembly

G protein coupled receptors (GPCR) constitute the largest group of cell surface receptors that transmit various signals across biological membranes through the binding and activation of heterotrimeric G proteins, which amplify the signal and activate downstream effectors leading to the biological responses. Thus, the first critical step in this signaling cascade is the interaction between receptor and its cognate G protein. Understanding this critical event at the molecular level is of high importance because abnormal function of GPCRs is associated with many diseases. Thus, these receptors are targets for drug development.     

Phylogeny and evolutionary rates of G protein α subunit genes

Summary Rooted phylogenetic trees for a total of 34 genes encoding the stimulatory (s), inhibitory (i), transducin (t), G_x (x), G_z (z), G₁₁ (11), G₁₂ (12), G₁₃ (13), G₁₆ (16), G_q (q), and other (o) G protein a subunits have been constructed. The analysis shows that the G₁₂ (12 and 13), G_q (11, 16, and q), and G_s (s genes) groups form one cluster, and the G_x (x and z genes), G_i (i genes), G_t (t1 and t2), and G_o (o genes) groups form another cluster. During mammalian evolution, the rates of synonymous substitutions for these genes were estimated to be between 1.77 × 10^–9/site/year and 5.63 × 10^–9/site/year, whereas those of nonsynonymous substitutions were between 0.008 × 10^–9/site/year and 0.067 × 10^–9/site/year. These evolutionary rates are similar to those for histone genes, suggesting equally important biological functions of the G protein a subunits. Offprint requests to: S. Yokoyama     

Direct-reversible binding of small molecules to G protein βγ subunits

Heterotrimeric guanine nucleotide-binding proteins (G proteins) composed of three subunits α, β, γ mediate activation of multiple intracellular signaling cascades initiated by G protein-coupled receptors (GPCRs). Previously our laboratory identified small molecules that bind to Gβγ and interfere with or enhance binding of select effectors with Gβγ. To understand the molecular mechanisms of selectivity and assess binding of compounds to Gβγ, we used biophysical and biochemical approaches to directly monitor small molecule binding to Gβγ. Surface plasmon resonance (SPR) analysis indicated that multiple compounds bound directly to Gβγ with affinities in the high nanomolar to low micromolar range but with surprisingly slow on and off rate kinetics. While the k(off) was slow for most of the compounds in physiological buffers, they could be removed from Gβγ with mild chaotropic salts or mildly dissociating collision energy in a mass-spectrometer indicating that compound-Gβγ interactions were non-covalent. Finally, at concentrations used to observe maximal biological effects the stoichiometry of binding was 1:1. The results from this study show that small molecule modulation of Gβγ-effector interactions is by specific direct non-covalent and reversible binding of small molecules to Gβγ. This is highly relevant to development of Gβγ targeting as a therapeutic approach since reversible, direct binding is a prerequisite for drug development and important for specificity.     

A constitutively active Gα subunit provides insights into the mechanism of G protein activation

The activation of Gα subunits of heterotrimeric G proteins by G protein-coupled receptors (GPCRs) is a critical event underlying a variety of biological responses. Understanding how G proteins are activated will require structural and biochemical analyses of GPCRs complexed to their G protein partners, together with structure-function studies of Gα mutants that shed light on the different steps in the activation pathway. Previously, we reported that the substitution of a glycine for a proline at position 56 within the linker region connecting the helical and GTP-binding domains of a Gα chimera, designated αT*, yields a more readily exchangeable state for guanine nucleotides. Here we show that GDP-GTP exchange on αT*(G56P), in the presence of the light-activated GPCR, rhodopsin (R*), is less sensitive to the β1γ1 subunit complex than to wild-type αT*. We determined the X-ray crystal structure for the αT*(G56P) mutant and found that the G56P substitution leads to concerted changes that are transmitted to the conformationally sensitive switch regions, the α4-β6 loop, and the β6 strand. The α4-β6 loop has been proposed to be a GPCR contact site that signals to the TCAT motif and weakens the binding of the guanine ring of GDP, whereas the switch regions are the contact sites for the β1γ1 complex. Collectively, these biochemical and structural data lead us to suggest that αT*(G56P) may be adopting a conformation that is normally induced within Gα subunits by the combined actions of a GPCR and a Gβγ subunit complex during the G protein activation event.     

Signaling by a non-dissociated complex of G protein βγ and α subunits stimulated by a receptor-independent activator of G protein signaling, AGS8

Accumulating evidence suggests that heterotrimeric G protein activation may not require G protein subunit dissociation. Results presented here provide evidence for a subunit dissociation-independent mechanism for G protein activation by a receptor-independent activator of G protein signaling, AGS8. AGS8 is a member of the AGS group III family of AGS proteins thought to activate G protein signaling primarily through interactions with Gbetagamma subunits. Results are presented demonstrating that AGS8 binds to the effector and alpha subunit binding "hot spot" on Gbetagamma yet does not interfere with Galpha subunit binding to Gbetagamma or phospholipase C beta2 activation. AGS8 stimulates activation of phospholipase C beta2 by heterotrimeric Galphabetagamma and forms a quaternary complex with Galpha(i1), Gbeta(1)gamma(2), and phospholipase C beta2. AGS8 rescued phospholipase C beta binding and regulation by an inactive beta subunit with a mutation in the hot spot (beta(1)(W99A)gamma(2)) that normally prevents binding and activation of phospholipase C beta2. This demonstrates that, in the presence of AGS8, the hot spot is not used for Gbetagamma interactions with phospholipase C beta2. Mutation of an alternate binding site for phospholipase C beta2 in the amino-terminal coiled-coil region of Gbetagamma prevented AGS8-dependent phospholipase C binding and activation. These data implicate a mechanism for AGS8, and potentially other Gbetagamma binding proteins, for directing Gbetagamma signaling through alternative effector activation sites on Gbetagamma in the absence of subunit dissociation.     

The G protein Gαs acts as a tumor suppressor in sonic hedgehog signaling-driven tumorigenesis

G protein-coupled receptors (GPCRs) are critical players in tumor growth and progression. The redundant roles of GPCRs in tumor development confound effective treatment; therefore, targeting a single common signaling component downstream of these receptors may be efficacious. GPCRs transmit signals through heterotrimeric G proteins composed of Gα and Gβγ subunits. Hyperactive Gα_s signaling can mediate tumor progression in some tissues; however, recent work in medulloblastoma and basal cell carcinoma revealed that Gα_s can also function as a tumor suppressor in neoplasms derived from ectoderm cells including neural and epidermal stem/progenitor cells. In these stem-cell compartments, signaling through Gα_s suppresses self-renewal by inhibiting the Sonic Hedgehog (SHH) and Hippo pathways. The loss of GNAS, which encodes Gα_s, leads to activation of these pathways, over-proliferation of progenitor cells, and tumor formation. Gα_s activates the cAMP-dependent protein kinase A (PKA) signaling pathway and inhibits activation of SHH effectors Smoothened-Gli. In addition, Gα_s-cAMP-PKA activation negatively regulates the Hippo pathway by blocking the NF2-LATS1/2-Yap signaling. In this review, we will address the novel function of the signaling network regulated by Gα_s in suppression of SHH-driven tumorigenesis and the therapeutic approaches that can be envisioned to harness this pathway to inhibit tumor growth and progression.     

The heterotrimeric G protein subunits Gα(q) and Gβ(1) have lysophospholipase D activity

In a previous study we purified a novel lysoPLD (lysophospholipase D) which converts LPC (lysophosphatidylcholine) into a bioactive phospholipid, LPA (lysophosphatidic acid), from the rat brain. In the present study, we identified the purified 42 and 35 kDa proteins as the heterotrimeric G protein subunits Gα(q) and Gβ(1) respectively. When FLAG-tagged Gα(q) or Gβ(1) was expressed in cells and purified, significant lysoPLD activity was observed in the microsomal fractions. Levels of the hydrolysed product choline increased over time, and the Mg(2+) dependency and substrate specificity of Gα(q) were similar to those of lysoPLD purified from the rat brain. Mutation of Gα(q) at amino acids Lys(52), Thr(186) or Asp(205), residues that are predicted to interact with nucleotide phosphates or catalytic Mg(2+), dramatically reduced lysoPLD activity. GTP does not compete with LPC for the lysoPLD activity, indicating that these substrate-binding sites are not identical. Whereas the enzyme activity of highly purified FLAG-tagged Gα(q) overexpressed in COS-7 cells was ~4 nmol/min per mg, the activity from Neuro2A cells was 137.4 nmol/min per mg. The calculated K(m) and V(max) values for lysoPAF (1-O-hexadecyl-sn-glycero-3-phosphocholine) obtained from Neuro2A cells were 21 μM and 0.16 μmol/min per mg respectively, similar to the enzyme purified from the rat brain. These results reveal a new function for Gα(q) and Gβ(1) as an enzyme with lysoPLD activity. Tag-purified Gα(11) also exhibited a high lysoPLD activity, but Gα(i) and Gα(s) did not. The lysoPLD activity of the Gα subunit is strictly dependent on its subfamily and might be important for cellular responses. However, treatment of Hepa-1 cells with Gα(q) and Gα(11) siRNAs (small interfering RNAs) did not change lysoPLD activity in the microsomal fraction. Clarification of the physiological relevance of lysoPLD activity of these proteins will need further studies.     

Conformational flexibility and binding interactions of the G protein βγ heterodimer

Previous NMR experiments on unbound G protein βγ heterodimer suggested that particular residues in the binding interface are mobile on the nanosecond timescale. In this work we performed nanosecond‐timescale molecular dynamics simulations to investigate conformational changes and dynamics of Gβγ in the presence of several binding partners: a high‐affinity peptide (SIGK), phosducin, and the GDP‐bound α subunit. In these simulations, the high mobility of GβW99 was reduced by SIGK, and it appeared that a tyrosine might stabilize GβW99 by hydrophobic or aromatic stacking interactions in addition to hydrogen bonds. Simulations of the phosducin‐Gβγ complex showed that the mobility of GβW99 was restricted, consistent with inferences from NMR. However, large‐scale conformational changes of Gβγ due to binding, which were hypothesized in the NMR study, were not observed in the simulations, most likely due to their short (nanosecond) duration. A pocket consisting of hydrophobic amino acids on Gα appears to restrict GβW99 mobility in the crystal structure of the Gαβγ? heterotrimer. The simulation trajectories are consistent with this idea. However, local conformational changes of residues GβW63, GβW211, GβW297, GβW332, and GβW339 were detected during the MD simulations. As expected, the magnitude of atomic fluctuations observed in simulations was greater for α than for the βγ subunits, suggesting that α has greater flexibility. These observations support the notion that to maintain the high mobility of GβW99 observed by solution NMR requires that the Gβ–α interface must open up on time scale longer than can be observed in nanosecond scale simulations. Proteins 2011. © 2010 Wiley‐Liss, Inc.     

Identification of heterotrimeric G protein α and β subunits in rice

Like those in mammals, heterotrimeric G protein complexes have been implicated in signal transduction pathways in plants; however, the subunits themselves have not been isolated. In this study, the rice heterotrimeric G protein subunits α (Gα) and β (Gβ) were purified by affinity chromatography using anti-Gα and -Gβ antibodies and SDS-PAGE. Six and seven peptides, respectively, were identified by mass spectrometry and identified as the translation products of the Gα gene RGA1 and Gβ gene RGB1. During purification, the subunits dissociated easily from the G protein complex.     

Two distinct aspects of coupling between Gα(i) protein and G protein-activated K+ channel (GIRK) revealed by fluorescently labeled Gα(i3) protein subunits

G protein-activated K(+) channels (Kir3 or GIRK) are activated by direct interaction with Gβγ. Gα is essential for specific signaling and regulates basal activity of GIRK (I(basal)) and kinetics of the response elicited by activation by G protein-coupled receptors (I(evoked)). These regulations are believed to occur within a GIRK-Gα-Gβγ signaling complex. Fluorescent energy resonance transfer (FRET) studies showed strong GIRK-Gβγ interactions but yielded controversial results regarding the GIRK-Gα(i/o) interaction. We investigated the mechanisms of regulation of GIRK by Gα(i/o) using wild-type Gα(i3) (Gα(i3)WT) and Gα(i3) labeled at three different positions with fluorescent proteins, CFP or YFP (xFP). Gα(i3)xFP proteins bound the cytosolic domain of GIRK1 and interacted with Gβγ in a guanine nucleotide-dependent manner. However, only an N-terminally labeled, myristoylated Gα(i3)xFP (Gα(i3)NT) closely mimicked all aspects of Gα(i3)WT regulation except for a weaker regulation of I(basal). Gα(i3) labeled with YFP within the Gα helical domain preserved regulation of I(basal) but failed to restore fast I(evoked). Titrated expression of Gα(i3)NT and Gα(i3)WT confirmed that regulation of I(basal) and of the kinetics of I(evoked) of GIRK1/2 are independent functions of Gα(i). FRET and direct biochemical measurements indicated much stronger interaction between GIRK1 and Gβγ than between GIRK1 and Gα(i3). Thus, Gα(i/o)βγ heterotrimer may be attached to GIRK primarily via Gβγ within the signaling complex. Our findings support the notion that Gα(i/o) actively regulates GIRK. Although regulation of I(basal) is a function of Gα(i)(GDP), our new findings indicate that regulation of kinetics of I(evoked) is mediated by Gα(i)(GTP).     

All G protein βγ complexes are capable of translocation on receptor activation

Heterotrimeric G proteins transduce signals sensed by transmembrane G protein coupled receptors (GPCRs). A subfamily of G protein βγ subunit types has been shown to selectively translocate from the plasma membrane to internal membranes on receptor activation. Using 4D imaging we show here that Gβγ translocation is not restricted to some subunit types but rather all 12 members of the family of mammalian γ subunits are capable of supporting βγ translocation. Translocation kinetics varies widely depending on the specific γ subunit type, with t(1/2) ranging from 10s to many minutes. Using fluorescence complementation, we show that the β and γ subunits translocate as βγ dimers with kinetics determined by the γ subunit type. The expression patterns of endogenous γ subunit types in HeLa cells, hippocampal neurons and cardiomyocytes are distinctly different. Consistent with these differences, the βγ translocation rates vary widely. βγ translocation rates exhibit the same γ subunit dependent trends regardless of the specific receptor type or cell type showing that the translocation rates are intrinsic to the γ subunit types. βγ complexes with widely different rates of translocation had differential effects on muscarinic stimulation of GIRK channel activity. These results show that G protein βγ translocation is a general response to activation of GPCRs and may play a role in regulating signaling activity.     

A Chlamydomonas gene encodes a G protein β subunit-like polypeptide

Summary A Chlamydomonas gene encodes a protein that shows sequence similarity with the subunit of guanine nucleotide binding proteins from mammals, fruit fly and yeast. In addition to amino acid sequences similarity, each of these proteins contains a segmented repeat structure in which certain amino acids form a consensus sequence. Thus this gene product has been designated a Chlamydomonas subunit-like polypeptide (Cblp). The mRNA is constitutively expressed during the cell cycle and during flagellar regeneration.     

A luciferase complementation assay system using transferable mouse artificial chromosomes to monitor protein–protein interactions mediated by G protein-coupled receptors

G protein-coupled receptors (GPCRs) are seven-transmembrane domain receptors that interact with the β-arrestin family, particularly β-arrestin 1 (ARRB1). GPCRs interact with 33% of small molecule drugs. Ligand screening is promising for drug discovery concerning GPCR-related diseases. Luciferase complementation assay (LCA) enables detection of protein–protein complementation via bioluminescence following complementation of N- and C-terminal luciferase fragments (NEluc and CEluc) fused to target proteins, but it is necessary to co-express the two genes. Here, we developed LCAs with mouse artificial chromosomes (MACs) that have unique characteristics such as stable maintenance and a substantial insert-carrying capacity. First, an NEluc-ARRB1 was inserted into MAC4 by Cre-loxP recombination in CHO cells, named ARRB1-MAC4. Second, a parathyroid hormone receptor 2 (PTHR2)-CEluc or prostaglandin EP4 receptor (hEP4)-CEluc were inserted into ARRB1-MAC4, named ARRB1-PTHR2-MAC4 and ARRB1-hEP4-MAC4, respectively, via the sequential integration of multiple vectors (SIM) system. Each MAC was transferred into HEK293 cells by microcell-mediated chromosome transfer (MMCT). LCAs using the established HEK293 cell lines resulted in 35,000 photon counts upon somatostatin stimulation for ARRB1-MAC4 with transient transfection of the somatostatin receptor 2 (SSTR2) expression vector, 1800 photon counts upon parathyroid hormone stimulation for ARRB1-PTHR2-MAC4, and 35,000 photon counts upon prostaglandin E2 stimulation for ARRB1-hEP4-MAC4. These MACs were maintained independently from host chromosomes in CHO and HEK293 cells. HEK293 cells containing ARRB1-PTHR2-MAC4 showed a stable reaction for long-term. Thus, the combination of gene loading by the SIM system into a MAC and an LCA targeting GPCRs provides a novel and useful platform to discover drugs for GPCR-related diseases.     

Predicting protein–protein interactions from protein sequences using meta predictor

A novel method is proposed for predicting protein–protein interactions (PPIs) based on the meta approach, which predicts PPIs using support vector machine that combines results by six independent state-of-the-art predictors. Significant improvement in prediction performance is observed, when performed on Saccharomyces cerevisiae and Helicobacter pylori datasets. In addition, we used the final prediction model trained on the PPIs dataset of S. cerevisiae to predict interactions in other species. The results reveal that our meta model is also capable of performing cross-species predictions. The source code and the datasets are available at