GIANT

GIANT identifies statistically overrepresented atomic contact patterns in 3D protein–small ligand complexes to objectively characterize ligand recognition and binding modes.

Key Features:

• Statistical analysis of interaction patterns: Leverages extensive statistical analyses of atomic contacts from 3D structures of protein–ligand complexes to identify interaction patterns that are statistically overrepresented.
• Annotation of interacting residues and ligand atoms: Annotates interacting amino acid residues, ligand atoms, and interacting pairs derived from protein–small ligand complexes.
• Contact-to-pattern assignment and statistical preferences: Assigns each atomic contact to an interaction pattern and quantifies statistical preferences of those patterns.
• Pattern representation and example complexes: Represents interaction patterns using probability density functions and provides lists of protein–ligand complexes that exhibit similar interactions.
• Binding-mode analysis guided by empirical patterns: Enables investigation of protein–small ligand binding modes using statistically determined interaction patterns rather than relying solely on prior knowledge or subjective inspection.

Scientific Applications:

• Selective ligand recognition: Characterizes molecular determinants of selective ligand recognition by proteins using empirically derived interaction patterns.
• Drug discovery and design: Informs structure-based drug discovery by mapping precise interaction patterns that can guide design of more effective and selective therapeutic agents.

Methodology:

Robust statistical analysis of existing 3D structure data to identify common/overrepresented atomic contact patterns, representation of patterns as probability density functions, and assignment of contacts to interaction patterns with derivation of statistical preferences.