GPCR-SSFE

GPCR-SSFE generates three-dimensional homology models of Class A G-protein coupled receptors to support structural analysis and structure-based drug design.

Key Features:

• Template library: A curated library of 27 inactive template structures for Class A GPCRs is employed to inform model building.
• Fingerprint correlation scoring: A fingerprint correlation scoring strategy identifies optimal templates by capturing structural nuances beyond sequence similarity.
• Helix-specific template selection: Helix-specific template selection enables per-helix choice of templates for model construction.
• Single-template and fragment-based modeling: Models can be constructed using single-template or helix-fragment–based approaches.
• SL2 loop modeling: Integration of the SL2 tool provides interactive loop modeling to refine loop conformations and template selection.
• Pre-calculated model repository: Includes a repository of pre-calculated homology models for Class A GPCRs.
• NGL visualization: Integration of the NGL viewer enables visualization of modeled structures.
• Benchmarking and validation: Validated by blind-testing against recently published GPCR structures, with performance reported as comparable or superior to other leading GPCR modeling web servers.

Scientific Applications:

• Homology modeling: Generation of three-dimensional homology models for Class A GPCR structural analysis.
• Structure-based drug design: Support for ligand-binding analysis and structure-guided drug discovery workflows.
• Template selection optimization: Improved template selection through fingerprint scoring and helix-specific choices for more accurate models.
• Fragment-based model construction: Assembly of models from helix-specific fragments to represent structural diversity.
• Loop refinement: Loop conformation refinement using SL2 to improve local structural accuracy.
• Benchmarking: Comparative evaluation against experimental GPCR structures and other GPCR modeling web servers.

Methodology:

Computational methods explicitly include use of a 27-template library, fingerprint correlation scoring for template identification, helix-specific template selection enabling single-template or fragment-based homology model construction, integration of SL2 for loop modeling, and visualization via the NGL viewer.