PatternQuery

PatternQuery detects, extracts, and analyzes well-defined biomacromolecular patterns, including binding sites, catalytic sites, and specific protein or nucleic acid sequences, from structural datasets such as the Protein Data Bank (PDB) to support studies of molecular function and interactions.

Key Features:

• Pattern Definition and Extraction: A unique query language with Python-like syntax allows users to define and extract precise biomolecular patterns.
• Data Source Flexibility: Supports input of user datasets and searches across the entire PDB, with filters such as PDB ID, resolution, and organism of origin.
• Efficient Processing: Performs rapid extractions—typically seconds for hundreds of entries—with an entire PDB search taking up to approximately one hour.
• Data Accessibility and Presentation: Extracted patterns are provided for download and presented in tabular and graphical formats.
• Novel Analytical Opportunities: The Python-like query language and database-wide search capability enable PDB-wide analyses that were previously difficult or unfeasible.

Scientific Applications:

• Drug Discovery: Enables identification and extraction of binding site patterns relevant to ligand design and target characterization.
• Enzyme Function Studies: Facilitates detection of catalytic site motifs and sequence patterns underlying enzymatic mechanisms.
• Protein–Protein Interaction Analysis: Supports extraction of interface and sequence patterns to study structural determinants of interactions.

Methodology:

PatternQuery uses a Python-like query language to define biomolecular patterns and the backend processes those queries against datasets including the entire PDB, returning extracted patterns as downloadable tabular and graphical results.