Dataset Information

MRNA Vaccines Against SARS-CoV-2 Variants Delivered by Lipid Nanoparticles Based on Novel Ionizable Lipids.

ABSTRACT: SARS-CoV-2 variants are now still challenging all the approved vaccines, including mRNA vaccines. There is an urgent need to develop new generation mRNA vaccines with more powerful efficacy and better safety against SARS-CoV-2 variants. In this study, a new set of ionizable lipids named 4N4T are constructed and applied to form novel lipid nanoparticles called 4N4T-LNPs. Leading 4N4T-LNPs exhibit much higher mRNA translation efficiency than the approved SM-102-LNPs. To test the effectiveness of the novel delivery system, the DS mRNA encoding the full-length S protein of the SARS-CoV-2 variant is synthesized and loaded in 4N4T-LNPs. The obtained 4N4T-DS mRNA vaccines successfully trigger robust and durable humoral immune responses against SARS-CoV-2 and its variants including Delta and Omicron. Importantly, the novel vaccines have higher RBD-specific IgG titers and neutralizing antibody titers than SM-102-based DS mRNA vaccine. Besides, for the first time, the types of mRNA vaccine-induced neutralizing antibodies are found to be influenced by the chemical structure of ionizable lipids. 4N4T-DS mRNA vaccines also induce strong Th1-skewed T cell responses and have good safety. This work provides a novel vehicle for mRNA delivery that is more effective than the approved LNPs and shows its application in vaccines against SARS-CoV-2 variants.

SUBMITTER: Chen K

PROVIDER: S-EPMC9349794 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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mRNA Vaccines Against SARS-CoV-2 Variants Delivered by Lipid Nanoparticles Based on Novel Ionizable Lipids.

Chen Kepan K Fan Na N Huang Hai H Jiang Xin X Qin Shugang S Xiao Wen W Zheng Qian Q Zhang Yupei Y Duan Xing X Qin Zeyi Z Liu Yongmei Y Zeng Jun J Wei Yuquan Y Song Xiangrong X

Advanced functional materials 20220719 39

SARS-CoV-2 variants are now still challenging all the approved vaccines, including mRNA vaccines. There is an urgent need to develop new generation mRNA vaccines with more powerful efficacy and better safety against SARS-CoV-2 variants. In this study, a new set of ionizable lipids named 4N4T are constructed and applied to form novel lipid nanoparticles called 4N4T-LNPs. Leading 4N4T-LNPs exhibit much higher mRNA translation efficiency than the approved SM-102-LNPs. To test the effectiveness of t ...[more]

PMID: 35942272

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Project description:A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, messenger RNA, and small interfering RNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies, albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder's capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol % PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus (KA) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and the head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for rational LNP design.

Project description:A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, mRNA, and siRNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes a rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder â€™s capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol% PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus ( KA ) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for a rational LNP design.

Dataset Information

MRNA Vaccines Against SARS-CoV-2 Variants Delivered by Lipid Nanoparticles Based on Novel Ionizable Lipids.

Publications

mRNA Vaccines Against SARS-CoV-2 Variants Delivered by Lipid Nanoparticles Based on Novel Ionizable Lipids.

Similar Datasets

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