Coarse-Grained Simulation of mRNA-Loaded Lipid Nanoparticle Self-Assembly

26 February 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Ionizable lipid-containing lipid nanoparticles (LNPs) have enabled the delivery of RNA for a range of therapeutic applications. In order to optimize safe, targeted and effective LNP-based RNA delivery platforms, an understanding of the role of composition and pH in their structural properties and self-assembly is crucial, yet there have been few computational studies of such phenomena. Here we present a coarse-grained model of ionizable lipid and mRNA-containing LNPs. Our model allows access to the large length- and time-scales necessary for LNP self-assembly, and is mapped and parameterized with reference to all-atom structures and simulations of the corresponding components at compositions typical of LNPs used for mRNA delivery. Our simulations reveal insights into the dynamics of self-assembly of such mRNA-encapsulating LNPs, as well as the subsequent pH change-driven LNP morphology and release of mRNA.

Keywords

molecular modeling
coarse-grained simulation
lipid nanoparticles
mRNA vaccines
self-assembly

Supplementary materials

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Description
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Supporting Information
Description
RNA sequences used in simulations, description of simulation protocols, description of coarse-grained mapping and force-field training procedure, comparison of AA and CG pair distribution functions, bond and angle distributions
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CG Force-Field Nonbonds
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Nonbond parameters for CG force field
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CG Force-Field Bonds
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Bond parameters for CG force field
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CG Force-Field Angles
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Angle parameters for CG force field
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Comment number 1, John Shelley: Sep 18, 2024, 20:29

This article has been published in Molecular Physics, 2024, 21, 4747 after review and revision. Link to ACS article website: https://pubs.acs.org/doi/10.1021/acs.molpharmaceut.4c00216