Finite lattice model for molecular aggregation equilibria. Boolean statistics, analytical approximations, and the...

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Biophysics

Background:

• Molecular processes like aggregation and self-assembly rely on non-covalent interactions.
• Understanding solute-ligand and ligand-ligand interactions is crucial for modeling these processes.

Purpose of the Study:

• To compare the accuracy of weighted random mixing (WRM) and Bethe-Guggenheim (BG) approximations in modeling molecular aggregation.
• To develop a computationally efficient method for obtaining accurate finite lattice (FL) predictions approaching the thermodynamic limit.
• To assess the applicability of lattice models by comparing them with molecular dynamics simulations.

Main Methods:

• Comparison of WRM and BG approximations against exact finite lattice (FL) predictions.
• Development of an efficient nearest-neighbor counting method for FL configurations.
• Application to methane aggregation around neopentane, comparing lattice models with molecular dynamics simulations.

Main Results:

• WRM and BG approximations are complementary, excelling in different aggregation regimes.
• An efficient method enables FL predictions for larger systems (up to n=48 binding sites), approaching the thermodynamic limit.
• Lattice model predictions align with molecular dynamics simulations for methane-neopentane aggregation.

Conclusions:

• The refined lattice models provide accurate predictions for molecular aggregation and self-assembly.
• The complementary nature of WRM and BG approximations offers flexibility in modeling diverse systems.
• The developed computational methods enhance the feasibility of studying complex molecular interactions.