Experimentally-Solved and Predicted GPCR Structures (GPCR-EXP)

Experimentally-Solved and Predicted GPCR Structures (GPCR-EXP) curates and integrates experimental Protein Data Bank (PDB) entries and GPCR-I-TASSER–predicted structures of human G protein-coupled receptors to support structural analysis and hierarchical virtual screening in GPCR structural biology and drug discovery.

Key Features:

• Experimental PDB curation: Integrates Protein Data Bank (PDB) entries for GPCRs with resolution details, publication information, and associated biological ligands.
• Genome-wide predicted structures: Provides predicted structures for all human genome-encoded GPCRs modeled with GPCR-I-TASSER.
• MAGELLAN integration: Integrates MAGELLAN, a hierarchical virtual-screening pipeline that performs low-resolution structure prediction and binding-site identification, detects homologous GPCRs via structural and orthosteric binding-site comparisons, constructs ligand profiles from homologous ligand–GPCR complexes, and threads those profiles through compound databases for virtual screening.
• Ligand profiling: Constructs ligand profiles from homologous ligand–GPCR complexes to enhance coverage and sensitivity of virtual-screening models.
• Retrospective screening performance: Reports a median enrichment factor (EF) of 14.38 on large-scale retrospective screens against human Class A GPCRs, outperforming AutoDock Vina, DOCK 6, PoLi, and FINDSITECcomb2.0.
• Deorphanization and visualization: Supports GPCR deorphanization and visualizes receptor relationships by constructing minimum spanning trees based on predicted ligand-binding ensemble similarities, with case studies on opioid and motilin receptors.
• Database statistics: Provides statistics summarizing the GPCR structural landscape derived from experimental and predicted entries.

Scientific Applications:

• Comparative structural analysis: Use experimental and GPCR-I-TASSER–predicted models for comparative analysis of GPCR architecture and binding sites.
• Hierarchical virtual screening: Apply MAGELLAN’s hierarchical pipeline and ligand profiling for prioritizing compounds in GPCR-targeted drug discovery.
• GPCR deorphanization: Facilitate identification of candidate ligands for orphan receptors, demonstrated for opioid and motilin receptors.
• Homolog detection and ligand transfer: Detect homologous GPCRs through structural and orthosteric binding-site comparisons to inform ligand hypothesis transfer.
• Method benchmarking: Enable retrospective benchmarking of virtual-screening approaches with reported comparisons to AutoDock Vina, DOCK 6, PoLi, and FINDSITECcomb2.0.

Methodology:

Curates experimental PDB entries; generates predicted GPCR structures with GPCR-I-TASSER; employs MAGELLAN steps: low-resolution protein structure prediction and binding-site identification, homologous GPCR detection via structural and orthosteric binding-site comparisons, ligand-profile construction from homologous ligand–GPCR complexes, threading ligand profiles through compound databases for virtual screening, and constructs minimum spanning trees from predicted ligand-binding ensemble similarities for visualization.