Mesoscopic Structure of Lipid Nanoparticles Studied by Small-Angle X-Ray Scattering: A Spherical Core-Triple Shell Model Analysis
Lipid nanoparticles (LNPs) are widely recognized as effective drug delivery systems for RNA therapeutics because their efficacy is critically dependent on structural organization. The mesoscopic architecture of these multicomponent systems, which is governed by interactions among ionizable lipids, s...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Membranes |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0375/15/5/153 |
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| Summary: | Lipid nanoparticles (LNPs) are widely recognized as effective drug delivery systems for RNA therapeutics because their efficacy is critically dependent on structural organization. The mesoscopic architecture of these multicomponent systems, which is governed by interactions among ionizable lipids, structural lipids, nucleic acids, and stabilizers, dictates encapsulation efficiency, biodistribution, and therapeutic performance. Although small-angle X-Ray scattering (SAXS) enables nanostructure characterization, the absence of suitable analytical models has hindered LNP development. Here, we present a core-triple shell SAXS model that resolves LNP hierarchical organization, including the inner lipid layer, intermediate hydrophilic region, and outer PEG corona. For LNPs encapsulating mRNA, a Gaussian distribution model was implemented to characterize the quasi-periodic structure originating from the self-assembly of mRNA-ionizable lipid complexes. Validation studies employing Comirnaty-based LNPs demonstrated that controlled variation of nitrogen-to-phosphorus (N/P) ratios produced distinguishable structural features that establish quantitative correlations between N/P ratios and LNP mesoscopic assembled structure. The modeling framework provides pharmaceutical researchers with robust analytical tools for systematic stability assessment and precision formulation for the optimization of LNPs. These structural insights are expected to advance the development of next-generation RNA therapeutics by potentially enhancing their delivery efficiency and pharmacokinetic properties. |
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| ISSN: | 2077-0375 |