Computational modeling in the optimization of lipid nanoparticles for efficient siRNA delivery: Design, molecular dynamics simulations, and experimental validation

Lipid nanoparticles (LNP) are a promising technology for RNA delivery. However, key factors must be considered in its formulation. Traditional methods are costly and time-consuming, while computational modeling efficiently predicts key parameters to optimize the process. Therefore, this study aimed to employ computational modeling to design LNPs for siRNA delivery and validate the results through laboratory experiments. We employed Chimera, SimRNA, OpenBabel, and Packmol to create the LNP model, which was subsequently developed using microfluidizer technology. The LNPs were characterized by zeta potential, PDI, particle size, pH, and storage stability. The results demonstrate that, as predicted by Molecular Dynamics (MD) simulations, LNP A (DOPC-DOTAP-Cholesterol) emerged as the most efficient siRNA delivery system based on computational and laboratory findings. Our results suggest that MD proved effective in predicting the characteristics of LNPs, serving as a powerful tool in the development of LNP-based siRNA delivery systems while optimizing both time and cost.