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Related Concept Videos

G-protein Coupled Receptors01:21

G-protein Coupled Receptors

118.4K
G-protein coupled receptors are ligand binding receptors that indirectly affect changes in the cell. The actual receptor is a single polypeptide that transverses the cell membrane seven times creating intracellular and extracellular loops. The extracellular loops create a ligand specific pocket which binds to neurotransmitters or hormones. The intracellular loops holds onto the G-protein.
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Transducer Mechanism: G Protein–Coupled Receptors01:30

Transducer Mechanism: G Protein–Coupled Receptors

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G Protein–Coupled Receptors (GPCRs) are membrane-bound receptors that transiently associate with heterotrimeric G proteins and induce an appropriate response to various stimuli. GPCRs regulate critical physiological pathways and are excellent drug targets for treating diseases such as diabetes, cancer, obesity, depression, or Alzheimer's. Nearly 35% of approved drugs implement their therapeutic effects by selectively interacting with specific GPCRs.
GPCRs are also called heptahelical,...
1.9K
Activation and Inactivation of G Proteins01:22

Activation and Inactivation of G Proteins

7.1K
Heterotrimeric G proteins are guanine nucleotide-binding proteins. As the name suggests, heterotrimeric G proteins are composed of three subunits: alpha, beta, and gamma. They remain GDP-bound or GTP-bound inside the cells and switch between inactive/active states. The Gα subunit possesses the nucleotide-binding pocket that binds guanine nucleotides and switches between GDP or GTP-bound states. In contrast, the Gꞵ and Gγ subunits are always bound together with high...
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G Protein-coupled Receptors01:15

G Protein-coupled Receptors

11.8K
G Protein-Coupled Receptors or GPCRs are membrane-bound receptors that transiently associate with heterotrimeric G proteins and induce an appropriate response to sensory stimuli such as light, odors, hormones, cytokines, or neurotransmitters.
GPCRs are also called heptahelical, 7TM, or serpentine receptors, and consist of seven (H1-H7) transmembrane alpha-helices that span the bilayer to form a cylindrical core. The transmembrane helices are connected by three extracellular loops and three...
11.8K
GPCRs Regulate Adenylyl Cylase Activity01:09

GPCRs Regulate Adenylyl Cylase Activity

5.5K
Some GPCRs transmit signals through adenylyl cyclase (AC), a transmembrane enzyme. AC helps synthesize second messenger cyclic adenosine monophosphate (cAMP). AC catalyzes cyclization reaction and converts ATP to cAMP by releasing a pyrophosphate. The pyrophosphate is further hydrolyzed to phosphate by the enzyme pyrophosphatase, which drives cAMP synthesis to completion. However, cAMP is rapidly degraded to 5′ AMP by the enzymes phosphodiesterase (PDE), preventing overstimulation of...
5.5K
GPCR Desensitization01:12

GPCR Desensitization

6.0K
G protein-coupled receptor (GPCR) signaling plays a crucial role in cell functioning. GPCR desensitization is an equally essential process. It allows cells to respond to changing environments and regain sensitivity to new stimuli while preventing unnecessary stimulation when no longer needed. Prolonged exposure to stimuli leads to GPCR desensitization. It involves blocking the receptors from binding and activating additional G proteins. This inhibits activation of downstream effectors, thereby...
6.0K

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Related Experiment Video

Updated: Jun 26, 2025

Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding
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Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding

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Engineering G protein-coupled receptors for stabilization.

João Paulo L Velloso1,2,3, Alex G C de Sá1,2,3, Douglas E V Pires4

  • 1School of Chemistry and Molecular Biosciences, The Australian Centre for Ecogenomics, The University of Queensland, Brisbane, Queensland, Australia.

Protein Science : a Publication of the Protein Society
|May 15, 2024
PubMed
Summary
This summary is machine-generated.

GPCR-tm is a new machine learning tool that predicts how mutations affect G protein-coupled receptor (GPCR) stability. This computational approach aids in stabilizing GPCRs for drug discovery and structural studies.

Keywords:
G protein‐coupled receptorsmachine learning (ML)protein engineeringstability predictionstructural characterization

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A Kinetic Fluorescence-based Ca2+ Mobilization Assay to Identify G Protein-coupled Receptor Agonists, Antagonists, and Allosteric Modulators
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A Kinetic Fluorescence-based Ca2+ Mobilization Assay to Identify G Protein-coupled Receptor Agonists, Antagonists, and Allosteric Modulators

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G Protein-selective GPCR Conformations Measured Using FRET Sensors in a Live Cell Suspension Fluorometer Assay
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G Protein-selective GPCR Conformations Measured Using FRET Sensors in a Live Cell Suspension Fluorometer Assay

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Related Experiment Videos

Last Updated: Jun 26, 2025

Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding
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Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding

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A Kinetic Fluorescence-based Ca2+ Mobilization Assay to Identify G Protein-coupled Receptor Agonists, Antagonists, and Allosteric Modulators
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A Kinetic Fluorescence-based Ca2+ Mobilization Assay to Identify G Protein-coupled Receptor Agonists, Antagonists, and Allosteric Modulators

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G Protein-selective GPCR Conformations Measured Using FRET Sensors in a Live Cell Suspension Fluorometer Assay
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G Protein-selective GPCR Conformations Measured Using FRET Sensors in a Live Cell Suspension Fluorometer Assay

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Area of Science:

  • Biochemistry and structural biology
  • Computational biology and bioinformatics
  • Drug discovery and pharmacology

Background:

  • G protein-coupled receptors (GPCRs) are critical drug targets, but their inherent instability hinders research.
  • Traditional protein engineering for GPCR stabilization is time-consuming and computationally challenging.
  • Existing computational methods for soluble proteins are not well-suited for GPCRs.

Purpose of the Study:

  • To develop a novel, personalized, structure-driven computational tool for predicting mutation impacts on GPCR stability.
  • To provide a machine learning-based solution to overcome the limitations in GPCR engineering for structural characterization and drug screening.

Main Methods:

  • Development of GPCR-tm, a web-based machine learning tool utilizing structurally driven features.
  • Application of graph-based signatures to represent mutation environments.
  • Validation using 10-fold cross-validation and blind test sets.

Main Results:

  • GPCR-tm demonstrates comparable or superior performance to existing methods.
  • Achieved Pearson's correlation coefficients of 0.74 (cross-validation) and 0.46 (blind test).
  • Identified structural graph-based signatures as key predictors of mutation effects on stability.

Conclusions:

  • GPCR-tm accurately ranks mutations by their impact on protein stability, facilitating rational stabilization strategies.
  • The tool aids in overcoming challenges in GPCR structural studies and drug discovery.
  • GPCR-tm is accessible via a user-friendly web server for broader scientific use.