GPCRautomodel

GPCRautomodel performs automated homology modeling and ligand docking for mammalian olfactory receptors (ORs) and other G protein-coupled receptors (GPCRs) to predict 3D receptor structures and evaluate ligand–receptor interactions.

Key Features:

• Automated homology modeling: Builds 3D models for mammalian ORs and other GPCRs using available GPCR structures as templates, including a set of six known GPCR structures.
• Fold recognition alignment: Employs fold recognition techniques to produce robust sequence-to-structure alignments that address low sequence similarity between ORs and template GPCRs.
• Ligand docking: Positions odorants and other ligands onto modeled receptor structures to generate ligand–receptor complexes in 3D.
• Scoring with colony energy: Evaluates and ranks docked complexes using colony energy as the scoring metric.
• 3D model outputs: Produces both free receptor structures and ligand–receptor complex models in three-dimensional coordinates.

Scientific Applications:

• GPCR–ligand interaction analysis: Identifies putative binding sites and interaction modes between odorants/ligands and GPCRs.
• Agonist versus antagonist characterization: Distinguishes docking behaviors of agonists and antagonists, reporting antagonists at the upper binding pocket and agonists in a narrower lower region, with agonist potency correlating to interactions with the pocket floor.
• Experimental validation support: Enables hypotheses for receptor mutagenesis and functional assays, and has been applied to a human OR previously characterized functionally.
• Structural biology and pharmacology: Supports studies of GPCR structure–function relationships relevant to pharmacological profiling.

Methodology:

The workflow uses fold recognition for sequence alignment, homology modeling based on available GPCR 3D structures (including six template structures), and a docking procedure scored by colony energy to generate and evaluate 3D receptor and ligand–receptor complexes.