Biology subjects

Nakate, P.

Publications and source records attributed to Nakate, P..

3 recordsLinked to original sources

bioRxiv2026

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

Lipid nanoparticles (LNPs) are one of the leading platforms for delivering nucleic acid therapeutics, yet their efficacy is limited by physicochemical interactions with the extracellular matrix (ECM) that trap the particles before they reach target cells. PEGylated nanoparticles mitigate these interactions by forming a protective steric layer on their surfaces. However, there is a lack of a predictive tool that gives mechanistic insights about how PEG surface density governs the underlying interaction and results in enhanced diffusive transport of LNPs through the ECM. Here, we present a multiscale hierarchical computational framework that couples all-atom constant pH molecular dynamics (CpHMD) with a highly coarse-grained model of the complete LNP within a crosslinked hyaluronic acid (HA) network. These atomistic simulations resolve the free energy of interaction between the LNP surface and HA chains across varying PEG lipid compositions, and integrate these free energy profiles to inform the coarse-grained simulations of LNP transport through the matrix. This work highlights that even a slightly PEGylated surface depletes the near-contact shell between the LNP and HA chains, which disrupts their adhesive interactions. These protective PEG layers produce a sharp, non-linear enhancement in LNP diffusivities, with just 1% PEG increasing the diffusivity nearly eight-fold relative to bare LNPs, which remain trapped in the matrix structures. This work provides a quantitative estimate of how PEG surface density governs LNP transport through the ECM, which offers predictive guidance for engineering LNP surface properties in target-specific drug delivery.

biophysics↗

bioRxiv2026

Anomalous diffusion of nanoparticles in semidilute hyaluronic acid solutions

Efficient drug delivery using nanoparticles (NPs) critically depends on their ability to diffuse through biological tissues to reach target cells at therapeutic concentrations. The extracellular matrix (ECM) poses a key barrier to such transport, which directly influences bio-distribution, cellular uptake, and overall therapeutic efficacy. A key regulator of this transport is hyaluronic acid/hyaluronan (HA), a major ECM polysaccharide that forms a hydrated, viscoelastic network. Increased/reduced hyaluronan concentration can elevate/decrease ECM bulk and effective viscosity. Increase in effective viscosity at the nanometer/micrometer length scales can hinder NP mobility through steric obstruction and hydrodynamic drag. There is a large variability in the HA molecular weights and concentrations, especially across age, tissue/organ, and pathological conditions. This work aims to study the diffusion of different NP types in the mixtures of HA polymers with variable molecular weights using the dynamic light scattering technique (DLS). Furthermore, we perform coarse-grained molecular dynamics (CG-MD) simulations for a model system to complement our findings from the dynamic light scattering experiments. We observe NP undergo anomalous diffusion, which is strongly dependent on the ratio of particle size/HA network mesh size, especially for higher molecular weight mixtures. This is strongly influenced by the effective viscosity, which is defined at the local environment experienced by the NPs. Our work highlights developing a simplified predictive framework coupled with simulations for a target-specific extracellular matrix environment.

biophysics↗

bioRxiv2026

Modeling lipid nanoparticle transport in extracellular matrix: Effects of particle size and rigidity

Lipid nanoparticles (LNPs) traverse through multiple biological barriers, such as crosslinked mesh structures in the extracellular matrix, before reaching their target sites. The physicochemical properties of LNPs determine their ability to penetrate complex biological environments such as the brain extracellular matrix. Their deformation in polymeric matrices affects transport, making it crucial to understand these factors for effective therapeutic delivery. Here, we develop a highly Coarse-Grained (CG) model of the LNP and its surrounding polymeric matrix, simulated as a uniform grid of cross-linked hyaluronic acid (HA) chains. The model for highly coarse-grained LNP was developed from a one-particle-thick membrane model that maintains mechanical features of lipid membranes, such as fluidity, topological changes, and hydrodynamic effects. Here, we investigate the collective influence of lipid nanoparticle size and its bending rigidity on the diffusive transport through the biological matrix. Our work highlights the role of particle to matrix size ratio in understanding deformation-assisted diffusive transport of LNPs in the matrix environment. Our study provides a tool to disentangle the effects of particle size and their bending rigidity on the transport through complex environments. Furthermore, this study systematically complements the rational design of lipid nanoparticle-based drug delivery platforms. SIGNIFICANCELipid nanoparticles (LNPs) are emerging as a powerful platform for delivering nucleic acid-based therapeutics, especially to hard-to-reach tissues like the brain. Their ability to protect and transport charged molecules, such as mRNA or siRNA, offers promising strategies for treating neurological disorders and advancing precision medicine for aging demographics around the world. In the brain parenchyma, LNPs must navigate the dense and heterogeneous extracellular matrix (ECM), composed primarily of crosslinked hyaluronic acid and proteoglycans. Understanding how particle size, deformability, and shape parameter affect the transport through this complex environment is critical for optimizing drug delivery platforms.

biophysics↗