In Silico Study of Ionizable Lipid Nanoparticles Using the SPICA Force Field

Area of Science:

• Nanotechnology
• Computational Chemistry
• Biophysics

Background:

• Lipid nanoparticles (LNPs) are crucial for delivering nucleic acid therapeutics.
• Accurate molecular characterization of LNPs, especially via in silico methods, is limited.
• Existing coarse-grained (CG) models for LNPs require improvement for detailed nanostructure analysis.

Purpose of the Study:

• To develop and validate an explicit coarse-grained (CG) model for lipid nanoparticles (LNPs).
• To investigate the in silico structural behavior of LNPs under varying pH and lipid compositions.
• To provide molecular-level insights into LNP-DNA interactions and transfection enhancement.

Main Methods:

• Expansion of the SPICA force field for a novel CG model of LNPs.
• Molecular dynamics simulations of LNPs with different helper lipids and pH conditions.
• Validation of in silico findings against experimental data (SAXS, cryo-TEM).

Main Results:

• A robust CG model for simulating LNP nanostructures was developed.
• Distinct LNP microstructures were observed at pH 4 (bilayer with sandwiched dsDNA) and pH 7 (amorphous dsDNA domains).
• The model explains how unsaturated phosphatidylcholine lipids enhance DNA transfection activity.

Conclusions:

• The developed CG model accurately predicts LNP structures and behavior.
• This research provides critical molecular insights for optimizing LNP design for enhanced stability and therapeutic efficacy.
• The findings advance the in silico investigation of lipid nanoparticle systems.