GPCR and Structural Pharmacology Research

GPCR pharmacology: agonist vs antagonist vs inverse agonist vs biased agonist — each has different clinical implications. Biased agonism (preferential G-protein vs β-arrestin signaling) can separate efficacy from side effects; for example, G-protein-biased opioid agonists aim to retain analgesia while reducing β-arrestin-mediated respiratory depression. Always classify retrieved ligands by their pharmacological type, not just their chemical structure. Receptor state (active vs inactive crystal structure) determines which ligands and mutations are interpretable — an inactive-state structure is appropriate for antagonist binding analysis, active-state for agonist-bound complexes. Generic GPCR numbering (Ballesteros-Weinstein) enables cross-receptor mutation comparison; always report positions in this system alongside sequence positions.

LOOK UP DON'T GUESS: never assume GPCRdb entry names (e.g., adrb2_human) or PDB IDs — always use GPCRdb_list_proteins to find the correct entry name and GPCRdb_get_structures to confirm available structures.

Research skill integrating GPCRdb (GPCR receptor biology), SAbDab (antibody structures), and PDBePISA (protein interface analysis) to support structural pharmacology, antibody engineering, and GPCR-targeted drug discovery.

KEY PRINCIPLES:

1. Receptor-first — Identify GPCR entry name before any GPCRdb queries
2. Ligand classification — Distinguish agonists, antagonists, partial agonists, biased agonists
3. Structure-guided — Pair GPCRdb mutation data with PDB structures via PDBePISA
4. Antibody context — Use SAbDab for therapeutic antibody structure retrieval and CDR analysis
5. English-first queries — Use standard receptor names (e.g., "beta-2 adrenergic receptor") in searches; convert to GPCRdb entry names for API calls

When to Use