GGIP

GGIP predicts interaction pairs between G protein-coupled receptors (GPCRs) from sequence data using a support vector machine to identify GPCR–GPCR interactions.

Key Features:

• Sequence input format: Accepts two GPCR amino acid sequences in FASTA format for pairwise analysis.
• Prediction output: Produces a binary prediction indicating whether the input GPCR sequence pair is likely to interact.
• Template structure selection: Allows specification of a PDB ID to select a template structure used to refine predictions.
• Human GPCR interaction expansion: Reports additional monomers predicted to interact with the query sequences for human GPCRs.
• Algorithm: Implements a support vector machine (SVM) classifier trained to predict GPCR–GPCR interaction pairs.

Scientific Applications:

• Disease-associated mutation analysis: Predicts how sequence variants may alter GPCR–GPCR interaction propensity relevant to disease mechanisms.
• Drug discovery and development: Informs assessment of compounds and strategies targeting GPCR interaction interfaces.

Methodology:

The method employs a support vector machine to analyze input GPCR sequences and incorporates a selected PDB template structure to refine predictions.