PACKMAN

PACKMAN predicts protein hinge regions from single static protein structures to characterize residue packing that underlies large-scale conformational dynamics such as domain opening and closing.

Key Features:

• Graph-theory analysis: Employs graph theory to analyze the packing and geometries of residues within protein structures.
• Single-structure prediction: Predicts hinge regions reliably from a single static structure in either open or closed conformations.
• Graph-based residue characterization: Characterizes residue interactions and configurations using graph-based representations to identify hinge regions.
• Validation with B-factors: Validates predicted hinges through permutation tests on B-factors to assess flexibility and movement.
• Comparison to curated lists: Compares predictions against manually curated lists of known hinge residues.
• Case studies and dataset: Applied to a set of 167 protein pairs with known open and closed structures, including Zika virus examples where hinges were identified in NS5, NS2B (bound in the NS3 protease complex), and NS3-helicase.

Scientific Applications:

• Conformational change analysis: Identifies hinge regions that mediate domain motions to analyze conformational changes.
• Conformational ensemble generation: Supports generation of conformational ensembles of protein targets for structure-based drug design.
• Mechanistic insight: Provides insights into mechanistic aspects of protein function linked to dynamic hinge behavior.

Methodology:

Uses graph theory to analyze residue packing and geometries, constructs graph-based representations of residue interactions and configurations, and validates predictions via permutation tests on B-factors and comparison to manually curated hinge lists.