OR and DXR

OR and DXR characterize structural and dynamic interactions between G-Protein Coupled Receptors (GPCRs) and intracellular partners (G-proteins and arrestins) to define determinants of receptor coupling selectivity.

Key Features:

• Multiple Sequence Alignment and Homology Modeling: Constructs sequence alignments and homology models of GPCRs and their intracellular binding partners to generate structural representations when experimental structures are unavailable.
• Complex Assembling and Refinement: Assembles receptor–partner complexes and refines them using HADDOCK followed by complex equilibration to stabilize interaction interfaces.
• Protein-Protein Interface Characterization: Performs comprehensive structural and dynamic analyses of interfaces between GPCRs and intracellular proteins including arrestins (Arr2, Arr3) and G-proteins (Gi1, Gi2, Gi3, Go, Gq).
• Application to Multiple GPCR Sub-families: Applies the pipeline across GPCR sub-families with specific use on the opioid receptor (OR) family and the dopamine receptor (DXR) family to assess coupling selectivity with intracellular partners.
• Large-Scale Analysis Capability: Supports large-scale modeling, exemplified by generation of 50 models for the DXR family, enabling comparison of structural and dynamic properties among partner groups (Arrs, Gs-, and Gi-proteins) and identification of motifs involved in selective coupling.

Scientific Applications:

• Structural characterization of GPCR complexes: Defines atomic-level interfaces and conformational states of GPCR–G protein and GPCR–arrestin assemblies.
• Coupling selectivity analysis: Investigates how different intracellular partners (Arr2, Arr3, Gi1, Gi2, Gi3, Go, Gq, Gs) determine receptor-specific coupling preferences.
• Comparative sub-family studies: Compares OR and DXR family members to reveal sub-family-specific determinants of signaling and partner recognition.
• Motif and signature identification: Identifies structural and dynamic motifs associated with selective coupling across large ensembles of models.

Methodology:

Computational steps include multiple sequence alignment, homology modeling, complex assembly, refinement with HADDOCK, complex equilibration, and structural and dynamic analysis of protein–protein interfaces, including generation of model ensembles (e.g., 50 DXR models).