Model-based quantification of protein-protein interaction aberrations for exploring dysregulated signalling pathways...

Area of Science:

• Bioinformatics
• Systems Biology
• Computational Biology

Background:

• Protein-protein interactions (PPIs) are crucial for signal transduction and understanding disease mechanisms.
• Traditional pathway analysis methods struggle with complex pathways due to predefined sub-pathway requirements.
• Identifying dysregulated pathways is essential for disease mechanism research.

Purpose of the Study:

• To develop a novel method for quantitatively evaluating individual protein-protein interactions (PPIs).
• To explore dysregulated sub-pathways without requiring predefinition.
• To provide a flexible framework for pathway analysis in complex biological systems.

Main Methods:

• Constructed a mathematical model based on association and dissociation reactions to quantify PPI aberration.
• Assessed aberration using a model parameter reflecting signal intensity differences between healthy and diseased groups, considering protein levels.
• Applied the method to mTOR signaling pathway data and gene expression datasets from clear cell renal cell carcinoma and lung squamous cell carcinoma.

Main Results:

• The proposed method identified aberrant PPIs consistent with a leading conventional method (HiPathia).
• Discovered potentially overlooked sub-pathways, demonstrating advantages over predefined approaches.
• Simulation studies confirmed the method's sufficient performance for real-world applications.

Conclusions:

• The developed method offers a novel framework for pathway analysis, particularly for complex pathways.
• It provides a quantitative approach to evaluate PPIs and explore dysregulated sub-pathways.
• The method is applicable when its underlying assumptions are met, offering a valuable tool for disease mechanism research.