A multiscale modeling framework for transport of PEGylated lipid nanoparticle through the extracellular matrix

Lipid nanoparticles (LNPs) are pivotal for delivering nucleic acid therapeutics; however, their effectiveness is hindered by interactions with the extracellular matrix (ECM). PEGylated nanoparticles address this issue by forming a steric layer that prevents these interactions. Despite this, there is a need for a predictive tool that elucidates how PEG surface density influences the interaction dynamics and leads to improved transport of LNPs through the ECM.

In this study, researchers introduce a multiscale hierarchical computational framework that integrates all-atom constant pH molecular dynamics (CpHMD) with a coarse-grained representation of the entire LNP embedded in a crosslinked hyaluronic acid (HA) network. The atomistic simulations quantify the free energy of interaction between the LNP surface and HA chains at various PEG lipid concentrations.

By incorporating these free energy profiles into the coarse-grained simulations, the framework predicts how LNPs traverse the matrix. The findings reveal that even a minor PEGylation reduces the near-contact zone between LNPs and HA chains, thereby weakening their adhesive bonds. Consequently, these PEG layers generate a pronounced, non-linear improvement in LNP diffusivity; a mere 1% increase in PEG content can boost diffusivity by approximately eight times compared to non-PEGylated LNPs, which remain ensnared within the matrix.

This research offers a quantitative understanding of how PEG surface density dictates LNP transport through the ECM, providing valuable guidance for tailoring LNP surface characteristics to enhance targeted drug delivery.