PITA

PITA infers the most likely biological oligomeric assemblies from X-ray crystallography data to resolve ambiguities arising from crystal symmetry operators and incomplete Protein Data Bank (PDB) annotations.

Key Features:

• Automatic inference of assembly structures: Determines physiologically relevant oligomeric assemblies from crystallographic data and PDB entries.
• Scoring system based on contact size and chemical complementarity: Scores potential protein-protein interfaces using contact size and chemical complementarity to prioritize biologically plausible interactions.
• Clustering procedure for subunit assembly inference: Employs a clustering method with an adjustable parameter to group scored contacts and infer subunit assemblies.
• Performance evaluation: Validated on a non-redundant dataset of 55 monomeric and 163 oligomeric proteins (dimers to hexamers) with a reported classification error rate of 16%.

Scientific Applications:

• Inference of functional assemblies: Identifying probable physiological oligomeric states for proteins lacking explicit assembly annotations in the PDB.
• Interface and interaction analysis: Prioritizing protein-protein interfaces to support investigations of protein function, interactions, and molecular mechanisms.
• Support for drug design and enzymology: Providing assembly and interface information relevant to drug design, enzymology, and the study of complex biological systems.

Methodology:

Analyzes crystallographic data to identify inter-subunit contacts, scores contacts by contact size and chemical complementarity, and clusters scored contacts with an adjustable parameter to infer the most probable assembly structures.