Molecular Dynamics Simulation of Lipid Nanoparticles Encapsulating mRNA.

design efficacy encapsulation mechanisms lipid nanoparticles (LNPs) mRNA vaccines

Journal

Molecules (Basel, Switzerland)
ISSN: 1420-3049
Titre abrégé: Molecules
Pays: Switzerland
ID NLM: 100964009

Informations de publication

Date de publication:
17 Sep 2024
Historique:
received: 25 08 2024
revised: 14 09 2024
accepted: 15 09 2024
medline: 29 9 2024
pubmed: 28 9 2024
entrez: 28 9 2024
Statut: epublish

Résumé

mRNA vaccines have shown great potential in responding to emerging infectious diseases, with their efficacy and stability largely dependent on the delivery vehicles-lipid nanoparticles (LNPs). This study aims to explore the mechanisms by which LNPs encapsulate mRNA, as well as the effects of different N/P ratios and acid types in nucleic acid solutions on the structure and properties of LNPs, using the ethanol solvent injection method as the encapsulation technique. Six systems were designed, based on the composition and proportions of the existing mRNA vaccine mRNA-1273, and molecular dynamics (MD) simulations were employed to investigate the self-assembly process of LNPs. Ethanol was used as a solvent instead of pure water to better mimic experimental conditions. The results indicate that lipid components self-assemble into nanoparticles under neutral conditions, with the ionizable lipid SM-102 predominantly concentrating in the core of the particles. Upon mixing with nucleic acids in acidic conditions, LNPs undergo disassembly, during which protonated SM-102 encapsulates mRNA through electrostatic interactions, forming stable hydrogen bonds. Cluster structure analysis revealed that the four lipid components of LNPs are distributed sequentially from the outside inwards as DMG-PEG 2000, DSPC, cholesterol, and protonated SM-102. Moreover, LNPs constructed under low pH or low N/P ratios using citric acid exhibited larger volumes and more uniform distribution. These findings provide a scientific basis for further designing and optimizing LNP components to enhance the efficacy of mRNA vaccine encapsulation.

Identifiants

pubmed: 39339404
pii: molecules29184409
doi: 10.3390/molecules29184409
pii:
doi:

Substances chimiques

RNA, Messenger 0
Lipids 0
Lipid Nanoparticles 0
Liposomes 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Zhigang Zhang (Z)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Dazhi Cheng (D)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Wenqin Luo (W)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Donling Hu (D)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Tiantian Yang (T)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Kaixuan Hu (K)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Li Liang (L)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Wei Liu (W)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.

Jianping Hu (J)

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu 610106, China.
School of Life Science, Leshan Normal University, Leshan 614004, China.

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Classifications MeSH