MONSTER

MONSTER predicts non-bonding interactions in macromolecular structures to identify and characterize stabilizing interactions using atomic coordinate data from Protein Data Bank (PDB) files.

Key Features:

• Input handling: Accepts PDB structure files and validates atomic coordinate data via a PERL-based wrapper that integrates in-house scripts and established public domain software.
• Interaction prediction: Identifies interacting residues within macromolecular structures and assigns specific non-bonding interaction types relevant to molecular stability.
• Output formats: Produces results in XML and text formats and provides representations as 3D structures and 2D diagrams.

Scientific Applications:

• Structure mining and validation: Highlights stabilizing non-bonding interactions to aid examination and validation of experimentally determined macromolecular structures.
• Functional analysis guidance: Identifies key non-bonding interactions that inform hypotheses about biomolecular function and guide experimental design.

Methodology:

Processes PDB atomic coordinates using a PERL-based wrapper that integrates in-house scripts and public domain software to validate coordinates, identify interacting residues, assign interaction types, and generate XML/text and 2D/3D outputs.