CCCPP

CCCPP identifies and computes cavities, channels, and pockets in protein structures to predict ligand-accessible voids for protein–ligand complex prediction and preparation of docking experiments.

Key Features:

• Void detection: Identifies and computes cavities, channels, and pockets within protein structures that are accessible to ligands.
• Ligand-shaped representations: Considers ligand size and shape by using cylindrical shapes rather than spherical approximations.
• Channel network analysis: Analyzes protein voids through a network of channels tailored to specific ligands to map potential pathways.
• Docking preparation: Predicts potential protein-ligand complexes to assist in preparing protein-ligand docking experiments.
• Validation on CYP enzymes: Validated on cytochrome P450 (CYP) 1A2 and 3A4, identifying pathways to buried heminic active sites, including routes accommodating two ketoconazoles simultaneously.

Scientific Applications:

• Protein–ligand docking preparation: Provides predicted ligand-accessible voids and pathways for preparing docking experiments.
• Structure-based drug design: Maps ligand pathways and pockets relevant for designing compounds and assessing access to buried active sites.
• Enzymatic mechanism and metabolism studies: Enables analysis of access routes to heminic active sites in cytochrome P450 enzymes (CYP 1A2 and 3A4) relevant to xenobiotic metabolism.
• High molecular weight substrate assessment: Assesses pathways accommodating large substrates, exemplified by simultaneous accommodation of two ketoconazoles.

Methodology:

Applies an advanced variant of the alpha shapes method that considers ligand size and shape using cylindrical representations and computes ligand-specific channel networks within protein structures.