Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Depicting a protein's two faces: GPCR classification by phylogenetic tree-based HMMs.

Bin Qian¹, Orkun S Soyer, Richard R Neubig

¹Biophysics Research Division, University of Michigan, Ann Arbor, MI 48105, USA.

|November 5, 2003

Summary

This study introduces a phylogenetic tree-based profile hidden Markov model (T-HMM) for analyzing protein sequences. The T-HMM method accurately classifies G protein-coupled receptors (GPCRs) based on their function, ligand, and coupled G protein.

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Ipilimumab and nivolumab for cancer treatment: a pharmacovigilance study based on the FDA adverse event reporting system database.

Frontiers in endocrinology·2026

Same author

Impact of living environmental quality on sarcopenia in middle-aged and older adults: evidence from cross-sectional and cohort analyses.

The journal of nutrition, health & aging·2026

Same author

Postoperative analgesic efficacy of intertransverse process block vs. erector spinae plane block in total laparoscopic hysterectomy: a randomized double-blind trial.

Frontiers in medicine·2026

Same author

Integrating Pharmacovigilance Data Mining and Mendelian Randomization to Identify Risk Profiles and Causal Targets of Opioid-Induced Delirium.

CNS neuroscience & therapeutics·2026

Same author

Rab1a attenuates TNF-α-induced apoptosis and extracellular matrix degradation in nucleus pulposus cells by inhibiting PI3K-Akt signaling pathway overactivation.

International immunopharmacology·2026

Same author

Stable Dual-Functional Coating on Polyurethane Surface by Grafting Antibacterial-Zwitterionic Copolymer.

Langmuir : the ACS journal of surfaces and colloids·2026

Area of Science:

Bioinformatics
Computational Biology
Protein Science

Background:

Proteins with similar functions often share conserved sequence features.
Statistical models can leverage these features for protein classification and function prediction.
Existing methods often overlook evolutionary relationships in sequence analysis.

Purpose of the Study:

To develop a novel method for extracting common sequence features among related proteins.
To apply this method to G protein-coupled receptors (GPCRs).
To assess the accuracy of the generated protein profiles in GPCR classification.

Main Methods:

Utilized a phylogenetic tree-based profile hidden Markov model (T-HMM).
Generated sequence profiles for groups of evolutionarily related proteins.

Related Experiment Videos

Applied the T-HMM to a dataset of G protein-coupled receptors (GPCRs).

Main Results:

The T-HMM method effectively captures common sequence features.
The generated T-HMM profiles demonstrated high accuracy in classifying GPCR functions.
Classification accuracy was high for both ligand binding and coupled G protein type.

Conclusions:

Phylogenetic information significantly enhances the accuracy of protein profile generation.
T-HMM is a powerful tool for analyzing protein sequence-function relationships.
This approach provides a robust framework for GPCR classification and discovery.