CavityPlus

CavityPlus identifies protein surface cavities from three-dimensional structural information and analyzes their ligandability and druggability to support structure-based drug discovery.

Key Features:

• Cavity Detection: Uses the upgraded CAVITY program to detect potential binding sites on protein structures and ranks them by ligandability and druggability scores, with enhanced calculation speed reported in 2022.
• CavPharmer: Extracts and analyzes receptor-based pharmacophore features within detected cavities using the Pocket pharmacophore modeling tool.
• CorrSite2.0: Identifies potential allosteric ligand-binding sites through motion correlation analyses between cavities.
• CovCys: Detects druggable cysteine residues to pinpoint potential covalent ligand binding sites.
• CavityMatch Module: Searches pre-constructed cavity databases for cavities similar to a query to support drug repurposing and protein function studies.

Scientific Applications:

• Structure-based drug discovery: Identifies and characterizes ligand-binding cavities to inform medicinal chemistry efforts.
• Target identification and selection: Maps functional and druggable sites to assist selection of therapeutic targets.
• Virtual screening: Provides cavity delineation and pharmacophore models to support virtual screening workflows.
• De novo drug design: Supplies pharmacophore features and cavity properties for fragment- and structure-based design.
• Allosteric and covalent inhibitor design: Facilitates design of allosteric modulators and covalent inhibitors via correlated-cavity analysis and druggable cysteine detection.
• Drug repurposing and protein function studies: Enables cavity similarity searches to identify analogous binding sites across proteins for repurposing and functional annotation.

Methodology:

Computational steps include cavity detection and ranking by the CAVITY program using ligandability and druggability scores; pharmacophore extraction with CavPharmer using Pocket; motion correlation analyses in CorrSite2.0 to predict allosteric sites; druggable cysteine identification by CovCys; and cavity similarity searches against pre-constructed databases by CavityMatch.