Diverse Aggregation Kinetics Predicted by a Coarse-Grained Peptide Model.

Area of Science:

• Biophysics
• Computational Chemistry
• Materials Science

Background:

• Protein and peptide aggregation are critical in medicine and industry.
• Understanding aggregate nucleation and growth mechanisms is essential.
• Experimental studies show diverse aggregation kinetics, including sigmoidal and downhill patterns.

Purpose of the Study:

• To investigate the molecular mechanisms governing peptide aggregation kinetics.
• To explore how interchain attraction and intrachain bending stiffness control aggregation.
• To model and reproduce experimentally observed aggregation modes.

Main Methods:

• Utilized a coarse-grained implicit solvent model for peptide aggregation simulations.
• Systematically varied parameters like interaction strength, stiffness, monomer concentration, and chain length.
• Analyzed simulation data to identify aggregation modes and transient morphologies.

Main Results:

• Interchain attraction strength is the primary determinant of aggregation mode (no aggregation, nucleated, or downhill).
• Chain stiffness modulates aggregation rates and the order of transient aggregates.
• Decreasing monomer concentration shifts aggregation from downhill to nucleated and no-aggregation.
• Longer peptide chains exhibit increased aggregation propensity.

Conclusions:

• The interplay of attraction and stiffness governs peptide aggregation pathways.
• Simulation results align with experimental observations on concentration-dependent and chain-length-dependent aggregation.
• The model provides insights into controlling peptide aggregation for various applications.