QuartPAC

QuartPAC identifies non-random clustering of somatic mutations within protein quaternary structures to detect potential driver mutations implicated in tumorigenesis.

Key Features:

• 3D Spatial Analysis: Leverages three-dimensional quaternary structure coordinates from the Protein Data Bank (PDB) to analyze spatial clustering of amino acid substitutions.
• Integration with Mutational Databases: Maps somatic mutation data from the Catalogue of Somatic Mutations in Cancer (COSMIC) onto protein structures for combined structural and mutational analysis.
• Novel Algorithmic Approach: Implements a dedicated algorithm to identify non-random clustering of mutations within quaternary structural contexts.

Scientific Applications:

• Driver Mutation Identification: Prioritizes candidate driver mutations by detecting non-random clusters of somatic substitutions within folded protein assemblies.
• Oncology Target Discovery: Localizes recurrent mutational clusters to key protein regions to support identification and prioritization of therapeutic targets.
• Precision Oncology: Informs personalized medicine and targeted therapy strategies by mapping patient-derived somatic mutations onto complete protein quaternary structures.

Methodology:

Uses three-dimensional quaternary structures from the Protein Data Bank (PDB), maps somatic mutations from COSMIC onto those structures, and applies a novel algorithm to detect non-random clustering of amino acid substitutions.