Scaling behaviour and rate-determining steps in filamentous self-assembly

Area of Science:

• Biophysics
• Molecular Biology
• Systems Biology

Background:

• Protein filament formation is crucial for biological functions (e.g., cytoskeleton) and diseases (e.g., Alzheimer's).
• Observed aggregation behaviors vary widely, from simple growth to complex cooperative processes.
• Current models often use distinct mechanisms for different protein self-assembly processes.

Purpose of the Study:

• To develop a single, unifying framework to quantitatively describe diverse filamentous protein self-assembly behaviors.
• To demonstrate that a broad range of macroscopic aggregation phenomena can be explained by a single model.
• To establish a method for identifying rate-determining steps in aggregation reactions.

Main Methods:

• Development of a unifying Petri net model for filamentous growth.
• Modeling based on aggregate number and aggregate mass concentrations.
• Analysis of system scaling behavior to determine rate-limiting steps.

Main Results:

• A single Petri net model quantitatively captures diverse protein aggregation behaviors.
• The model successfully explains phenomena ranging from simple growth to cooperative assembly.
• The framework allows direct identification of rate-determining steps from scaling behavior.

Conclusions:

• A unified Petri net approach provides a powerful quantitative description of protein self-assembly.
• This framework simplifies the understanding of diverse filamentous growth mechanisms.
• The approach is general and adaptable to future extensions of aggregation reaction networks.