CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation.

Area of Science:

• Biomedical Engineering
• Computational Chemistry
• Materials Science

Background:

• Lipid nanobubbles offer biocompatibility and therapeutic potential for applications like drug delivery and imaging.
• Understanding molecular interactions is crucial for precise nanobubble applications.
• Current molecular dynamics simulations use vacuum cores, limiting biological relevance.

Purpose of the Study:

• To develop and optimize all-atom gas parameters for molecular dynamics (MD) simulations of lipid nanobubbles.
• To enable accurate simulation of gas behavior within nanobubbles and their interactions with biological systems.
• To provide a computational tool for studying the molecular mechanisms of lipid nanobubbles.

Main Methods:

• Developed and optimized CHARMM36 all-atom gas parameters for N2, O2, H2, CO, CO2, and SO2.
• Validated gas parameters by reproducing gas density and spontaneous nanobubble formation.
• Created a Python script for generating all-atom lipid nanobubble simulation systems.

Main Results:

• Optimized gas parameters accurately reproduced gas density and nanobubble formation.
• Simulations successfully captured lipid nanobubble self-assembly.
• The developed models efficiently simulated nanobubble dynamics at interfaces.

Conclusions:

• The proposed all-atom gas models are suitable for simulating free and lipid nanobubbles.
• These models overcome limitations of previous vacuum-core simulations.
• They are key to understanding molecular-level interactions between nanobubbles and biological systems.