PRED-GPCR

PRED-GPCR predicts and classifies G-protein coupled receptor (GPCR) sequences at the family level by querying them against a curated library of profile Hidden Markov Models (HMMs).

Key Features:

• Database Utilization: Leverages a library of 265 signature profile Hidden Markov Models (HMMs) representing 67 well-characterized GPCR families.
• Automated Screening: Automates querying of input sequences against the HMM library for rapid identification of matches.
• Family-level Classification: Assigns sequences to specific GPCR families based on HMM match patterns.
• Result Reporting: Reports individual motif (single-motif) matches and combined family-level match results.

Scientific Applications:

• GPCR annotation in genomics and proteomics: Classifies sequences to catalog GPCR diversity in genome and proteome projects.
• High-throughput sequence screening: Enables automated screening of large sequence datasets for potential GPCRs.
• Support for research and drug discovery: Provides family-level classification to support fundamental biological studies and drug discovery initiatives.

Methodology:

Querying input sequences against a curated database of 265 profile HMMs representing 67 GPCR families and assigning family membership based on sequence similarity to the HMM models.