Graph theory and stability analysis of protein complex interaction networks

Area of Science:

• Systems Biology
• Network Science
• Bioinformatics

Background:

• Protein complexes are crucial for biological processes.
• Protein complex interaction networks (PCINs) are fundamental to cellular functions.
• Limited research exists on PCIN topology and stability under perturbations.

Purpose of the Study:

• To investigate the global and local topological properties of PCINs.
• To assess the stability and robustness of PCINs under various perturbations.
• To identify critical protein complexes within the network structure.

Main Methods:

• Employed a graph theoretical approach to analyze four species' PCINs.
• Evaluated network stability against 12 types of perturbations.
• Utilized the Kolmogorov-Smirnov test to validate topological indicators.
• Performed scalability and data normalization tests.

Main Results:

• Identified critical protein complexes through topological parameter classification.
• Demonstrated that local topological parameters effectively characterize PCIN structure.
• Found that degree-based, betweenness-based, and brokering-coefficient-based perturbations significantly impact network stability.
• Validated the biological interpretability of the topological analysis approach.

Conclusions:

• Graph theoretical analysis provides meaningful insights into protein complex systems.
• Local topological parameters are reliable indicators for characterizing PCIN structure.
• Network robustness is significantly affected by specific targeted perturbations, offering insights into network resilience.