Bond formation kinetics affects self-assembly directed by ligand-receptor interactions.

Area of Science:

• Physical Chemistry
• Materials Science
• Computational Chemistry

Background:

• Coarse-grained models often use equilibrium statistical mechanics for self-assembly.
• These models neglect the kinetics of inter-particle linker formation.
• This simplification can overlook crucial dynamic aspects of self-assembly.

Purpose of the Study:

• To investigate the impact of aggregation kinetics on self-assembly pathways.
• To develop a simulation method incorporating linker formation and breakage dynamics.
• To analyze how linker kinetics influence aggregate structure and relaxation.

Main Methods:

• Developed a hybrid simulation approach combining Brownian dynamics and Gillespie algorithm.
• Explicitly modeled the evolution of inter-particle linkages over time.
• Simulated self-assembly processes under varying conditions (temperature, diffusion).

Main Results:

• Explicitly modeling linker kinetics leads to aggregates with lower initial valency compared to effective potential models.
• The rate of supramolecular linkage formation significantly alters the self-assembly pathway.
• Relaxation to equilibrium is hindered by the time needed to break and reform linkages, especially at low temperatures and high diffusion.

Conclusions:

• Kinetic rates of inter-particle linkage formation are critical for accurate coarse-grained descriptions of self-assembly.
• Neglecting these kinetics can lead to inaccurate predictions of aggregate structure and dynamics.
• Incorporating dynamic linker evolution is essential for studying ligand-receptor systems and supramolecular assembly.