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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
GPCRs Regulate Adenylyl Cylase Activity01:09

GPCRs Regulate Adenylyl Cylase Activity

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 cells.
Two...
Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower Kd...
G Protein-coupled Receptors01:15

G Protein-coupled Receptors

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...
GPCR Desensitization01:12

GPCR Desensitization

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...
Transducer Mechanism: G Protein–Coupled Receptors01:30

Transducer Mechanism: G Protein–Coupled Receptors

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, 7TM, or...

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Related Experiment Video

Updated: May 15, 2026

Monitoring GPCR-β-arrestin1/2 Interactions in Real Time Living Systems to Accelerate Drug Discovery
08:21

Monitoring GPCR-β-arrestin1/2 Interactions in Real Time Living Systems to Accelerate Drug Discovery

Published on: June 28, 2019

Study on human GPCR-inhibitor interactions by proteochemometric modeling.

Jun Gao1, Qi Huang, Dingfeng Wu

  • 1School of Stomatology, Tongji University, Shanghai 200072, PR China. jungao@shmtu.edu.cn

Gene
|December 19, 2012
PubMed
Summary
This summary is machine-generated.

Developing new drugs for G protein-coupled receptors (GPCRs) is challenging due to sequence similarities. This study introduces proteochemometric models to predict GPCR-inhibitor interactions, aiding in designing safer and more effective drugs.

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Construction of Model Lipid Membranes Incorporating G-protein Coupled Receptors (GPCRs)
09:45

Construction of Model Lipid Membranes Incorporating G-protein Coupled Receptors (GPCRs)

Published on: February 5, 2022

Related Experiment Videos

Last Updated: May 15, 2026

Monitoring GPCR-β-arrestin1/2 Interactions in Real Time Living Systems to Accelerate Drug Discovery
08:21

Monitoring GPCR-β-arrestin1/2 Interactions in Real Time Living Systems to Accelerate Drug Discovery

Published on: June 28, 2019

Parallel Interrogation of β-Arrestin2 Recruitment for Ligand Screening on a GPCR-Wide Scale using PRESTO-Tango Assay
09:03

Parallel Interrogation of β-Arrestin2 Recruitment for Ligand Screening on a GPCR-Wide Scale using PRESTO-Tango Assay

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Construction of Model Lipid Membranes Incorporating G-protein Coupled Receptors (GPCRs)
09:45

Construction of Model Lipid Membranes Incorporating G-protein Coupled Receptors (GPCRs)

Published on: February 5, 2022

Area of Science:

  • Computational chemistry
  • Pharmacology
  • Drug discovery

Background:

  • G protein-coupled receptors (GPCRs) are key drug targets, but their high sequence homology complicates drug design for safety and efficacy.
  • Predicting interactions between GPCRs and inhibitors is crucial for developing targeted therapies for various diseases.

Purpose of the Study:

  • To develop robust proteochemometric (PCM) models for predicting human GPCR-inhibitor interactions.
  • To identify optimal descriptors and statistical learning techniques for accurate prediction of GPCR drug interactions.

Main Methods:

  • Construction of PCM models using various combinations of protein and ligand descriptors with statistical learning techniques (Support Vector Regression and Gaussian Processes).
  • Evaluation of descriptor performance, including Transmembrane (TM) identity and z-scale descriptors, and the impact of ligand-receptor cross-terms.
  • Validation of the best performing models using an external test set and ROC curve analysis.

Main Results:

  • Support Vector Regression (SVR) generally outperformed Gaussian Processes (GP) in predictive accuracy.
  • Transmembrane (TM) identity descriptors proved more effective than z-scale descriptors for characterizing GPCRs.
  • The inclusion of ligand-receptor cross-terms did not significantly improve model performance. The best models achieved high predictive accuracy (e.g., SVR-S-DLI: R(2)=1.0000, Q(2)test=0.7423).

Conclusions:

  • The developed PCM models demonstrate strong predictive capabilities for human GPCR-inhibitor interactions.
  • These models can facilitate the discovery of novel multi-target or specific GPCR inhibitors with improved efficacy and reduced side effects.
  • The findings offer a valuable tool for rational drug design targeting GPCRs.