Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

13.9K
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...
13.9K
G Protein-coupled Receptors01:15

G Protein-coupled Receptors

13.8K
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...
13.8K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

3.9K
3.9K
GPCRs Regulate Adenylyl Cylase Activity01:09

GPCRs Regulate Adenylyl Cylase Activity

6.0K
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...
6.0K
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

1.9K
1.9K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.7K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Genomic landscape of drug binding and pharmacogenetic variation across diverse populations using SNPdrug3D.

Nature communications·2026
Same author

Differences in reactive metabolite formation and cytochrome P450 binding between acetaminophen and its bicyclo[1.1.1]pentane bioisostere.

Drug metabolism and pharmacokinetics·2026
Same author

Simulation-guided chemical direct reprogramming informed by temporal cellular conversion processes at the single-cell level.

Communications chemistry·2026
Same author

Methylmercury causes pain disorders by disrupting the neuronal function of spinal dorsal horn neurons in mice.

Toxicological research·2026
Same author

Improved Method for Predicting GPCR-GPCR Interaction Pairs.

Proteins·2026
Same author

Mechanism-based prediction of drug synergy via network controllability analysis of therapeutic pathways in intractable diseases.

iScience·2026
Same journal

Beyond weight loss: predictors of treatment satisfaction and patient-reported outcomes in incretin-based therapies. A cross-sectional study.

Frontiers in endocrinology·2026
Same journal

Development and validation of a cross-sectional risk screening nomogram for carotid plaque based on routine health examination data and the triglyceride-glucose-waist-to-hip ratio.

Frontiers in endocrinology·2026
Same journal

An interpretable nomogram for predicting early acute postoperative hypocalcemia in differentiated thyroid cancer: development and internal validation.

Frontiers in endocrinology·2026
Same journal

Polymorphism analysis of estrogen receptor β Gene RsaI and AluI in girls with idiopathic central precocious puberty: investigating the relationship and implications for early risk prediction.

Frontiers in endocrinology·2026
Same journal

Prospective association between biological aging and risk of hospital-diagnosed MASLD: evidence from the UK Biobank.

Frontiers in endocrinology·2026
Same journal

Editorial: New advances in embryo development and embryo-endometrial interface.

Frontiers in endocrinology·2026
See all related articles

Related Experiment Video

Updated: Sep 27, 2025

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

407

A Web Server for GPCR-GPCR Interaction Pair Prediction.

Wataru Nemoto1,2, Yoshihiro Yamanishi3, Vachiranee Limviphuvadh4

  • 1Division of Life Science, Department of Science and Engineering, School of Science and Engineering, Tokyo Denki University (TDU), Hatoyama-machi, Japan.

Frontiers in Endocrinology
|April 11, 2022
PubMed
Summary
This summary is machine-generated.

The GGIP web server predicts G protein-coupled receptor (GPCR) interactions using a support vector machine. This tool aids in understanding GPCR-GPCR interactions and analyzing disease-associated mutations.

Keywords:
GPCRbioinformaticsdisease-associated mutationmachine learningmembrane proteinpredictionprotein-protein interactionweb service

More Related Videos

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.0K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.6K

Related Experiment Videos

Last Updated: Sep 27, 2025

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

407
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.0K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.6K

Area of Science:

  • Biochemistry
  • Bioinformatics
  • Computational Biology

Background:

  • G protein-coupled receptors (GPCRs) form a large family of cell surface receptors involved in numerous physiological processes.
  • Understanding GPCR-GPCR interactions is crucial for deciphering complex cellular signaling pathways.
  • Existing methods for predicting GPCR-GPCR interactions are limited.

Purpose of the Study:

  • To introduce the GGIP web server, a novel tool for predicting GPCR-GPCR interaction pairs.
  • To provide a user-friendly platform for GPCR interaction prediction.
  • To demonstrate the utility of GGIP in analyzing disease-associated mutations.

Main Methods:

  • The GGIP web server utilizes a support vector machine (SVM) algorithm.
  • It accepts two amino acid sequences in FASTA format as input.
  • Predictions are generated based on sequence information and optionally a template PDB ID.

Main Results:

  • The GGIP server accurately predicts whether input GPCR sequence pairs interact.
  • For human GPCRs, it identifies interacting monomers within the predicted pair.
  • The server provides rapid predictions and is freely accessible.

Conclusions:

  • The GGIP web server is a valuable and unique resource for predicting GPCR-GPCR interactions.
  • Its ease of use and accessibility make it suitable for researchers in various fields.
  • GGIP has potential applications in disease mutation analysis and drug discovery.