Evidence map›Paper›PMID 42818376›Full record

ArticlebioRxiv : the preprint server for biology2026

A multiscale modeling framework for transport of PEGy-lated lipid nanoparticle through the extracellular matrix.

Prasheel Nakate, Kyle J Colston, Severin T Schneebeli, Arezoo M Ardekani

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Prasheel NakateSchool of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907, United States.ORCID 0000-0002-7962-3328
Kyle J ColstonDepartment of Industrial and Molecular Pharmaceutics, Purdue University, West Lafayette, Indiana 47907, United States.
Severin T SchneebeliDepartment of Industrial and Molecular Pharmaceutics, Purdue University, West Lafayette, Indiana 47907, United States.ORCID 0000-0002-9511-9922
Arezoo M ArdekaniSchool of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907, United States.ORCID 0000-0003-3301-3193

Funding

Robust Sequence-defined Nanocages with Protein-mimetic CavitiesR35GM147579 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Severin Thomas Schneebeli · 2022 to 2026
$1.9M
NIGMS NIH HHS R35 GM147579
6 · The paper itself

Abstract

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.

Identifiers

PMID42818376
PMCPMC13622685

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.