Disruptor: Computational identification of oncogenic mutants disrupting protein-protein and protein-DNA interactions

Area of Science:

• Computational Biology
• Molecular Oncology
• Structural Bioinformatics

Background:

• Identifying oncogenic mutations is crucial for cancer research and targeted therapies.
• Understanding how mutations disrupt molecular interactions (e.g., protein-protein, protein-DNA) is key to elucidating cancer mechanisms.

Purpose of the Study:

• To present Osprey, a novel computational protocol for prospectively identifying oncogenic mutations.
• To demonstrate the protocol's applicability to both protein-protein and protein-DNA interfaces.
• To validate the method and apply it to predict novel mutations in cancer-related genes.

Main Methods:

• Development of the Osprey computational protocol.
• Application of Osprey to analyze protein-protein and protein-DNA interfaces.
• Validation using a dataset of clinically relevant mutations.
• Prediction and experimental confirmation of mutations in CDK6 and p16 genes.

Main Results:

• The Osprey protocol successfully identifies oncogenic mutations by assessing the disruption of molecular interactions.
• The method is versatile, applicable to diverse interface types.
• Predicted mutations in CDK6 and p16 were experimentally validated, confirming impaired complex formation.

Conclusions:

• Osprey provides a robust computational approach for identifying disease-driving mutations.
• This method aids in understanding mutation impact on molecular complex formation.
• The findings offer new insights into the functional consequences of mutations in CDK6 and p16.