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52 results for “lipid nanoparticles”

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zenodo48/100

Adsorption free energies and potentials of mean-force for interactions between amino acids, lipid fragments, and nanoparticles

<p>This dataset contains tabulated potentials of mean force (PMFs) and associated adsorption (binding) free energies for interactions of amino acids side chain analogues and lipid fragments (LF) with a range of materials: titanium dioxide, iron oxide, amorphous silica, quartz, and a range of carbon-based materials including amorphous carbon, graphene and carbon nanotubes both in a pristine form and functionalized by certain chemical groups. All data were computed from atomistic molecular dynamics simulations as a part of the SmartNanoTox project 2016-2020. Version 2 of the dataset includes additional materials: zink oxide, zink sulfate in pristine and PMMA-coated forms computed within NanoSolveIt project (2019-2023). The data are intended to be used in coarse-grained models describing interactions of nanomaterials with nanoparticles, for the prediction of the binding affinity of proteins and lipids to nanoparticles, and as biological &quot;fingerprints&quot; of nanomaterials characterizing behavior of the nanomaterials in biological environments.&nbsp;</p>

opencc-by-4.0Aug 2023View details →
dryad40/100

Safer and efficient base editing and prime editing via ribonucleoproteins delivered through optimized lipid-nanoparticle formulations

Open the record for dataset details and reuse information.

publicDec 2025View details →
zenodo36/100

A bottom-up coarse-grained model for interactions of lipids with TiO2 nanoparticles

<p>Supplemetary information data to the paper:</p> <p>M.Ivanov and A.P.Lyubartsev, "Development of a bottom-up coarse-grained model for interactions of lipids with TiO<br>&nbsp;nanoparticles", J. Comput. Chem.m 2024. Doi: <a href="https://doi.org/10.1002/jcc.27310">10.1002/jcc.27310</a></p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Research Data Supporting "Coupling Lipid Nanoparticle Structure and Automated Single Particle Composition Analysis to Design Phospholipase Responsive Nanocarriers"

<p>Raw research data supporting Barriga, Pence, et al. 2022, Advanced Materials. <a href="https://doi.org/10.1002/adma.202200839">https://doi.org/10.1002/adma.202200839</a></p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

mRNA lipid nanoparticle phase transition

<p>The repository contains input files and data from the manuscript:</p> <p>Trollmann, Marius F.W. and B&ouml;ckmann, Rainer A. &quot;mRNA lipid nanoparticle phase transition&quot;, Biophysical Journal (2022)&nbsp;<a href="https://doi.org/10.1016/j.bpj.2022.08.037">https://doi.org/10.1016/j.bpj.2022.08.037</a></p> <p>&nbsp;</p> <p><strong>&gt;&nbsp;Periodic membrane patches</strong></p> <p>Equilibrated structures, .mdp and .top files for the simulations of the periodic Comirnaty membrane patches. (microsecond = us)</p> <p>&gt;&gt; periodic_patches/low_ph/single_patch:&nbsp;</p> <p>~ System A: Three replicas (4.1 us, 3.0 us and 3.0 us) of the self-assembled Comirnaty lipid mixture with the protonated aminolipid</p> <p>&gt;&gt; periodic_patches/low_ph/quad_patch:&nbsp;</p> <p>System B: A quadruplicated system A patch simulated for 1.0 us</p> <p>&gt;&gt; periodic_patches/dspc_chol:</p> <p>System C: Binary membrane including DSPC and 43mol% cholesterol</p> <p>&gt;&gt; periodic_patches/neutral_ph:</p> <p>System D: A deprotonated system B patch simulated for 0.633 us</p> <p>&gt;&gt; periodic_patches/mrna_selfassembly:</p> <p>System E: Structures of the self-assembled Comirnaty lipid mixture with the modified mRNA strand</p> <p>+ periodic_patches/mrna_selfassembly/selfassembly: Structures of the mRNA-lipid mixture after self-assembly with protonated aminolipids</p> <p>+ periodic_patches/mrna_selfassembly/set1: Quadruplicated simulation systems after deprotonation of distant aminolipids (set 1, see paper)</p> <p>&nbsp;+ periodic_patches/mrna_selfassembly/set2: Quadruplicated simulation systems after deprotonation of random aminolipids (set 2, see paper)</p> <p>+ periodic_patches/mrna_selfassembly/set3: Simulation systems after deprotonated of all aminolipids (systems were not quadruplicated) (set 3, see paper)</p> <p>&nbsp;</p> <p><strong>&gt; Lipid nanoparticles</strong></p> <p>Equilibrated structures, .mdp and .top files for the simulations of the lipid nanoparticles. (microsecond = us)</p> <p>&gt;&gt; nanoparticles/lnp_nopegs:</p> <p>System F: Structures of the lipid nanoparticles with capped PEGylated lipids</p> <p>&gt;&gt; nanoparticles/lnp_pegs:</p> <p>System G: Structure of the lipid nanoparticle with complete PEGylated lipids</p> <p>&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</p> <p><strong>&gt; Topologies</strong></p> <p>- topology/DSPC.top - Parameters for the standard phospholipid from the CHARMM36 forcefield</p> <p>- topology/CHOL.top - Parameters for cholesterol from the CHARMM36 forcefield</p> <p>- topology/alc.itp, topology/alc.prm - Parametrization files of the PEG-ylated lipid ALC-0159 obtained from the CGenFF-Webserver</p> <p>- topology/alc_neutral.itp - Parameters for the neutral aminolipid ALC-0315 obtained from the CGenFF-Webserver</p> <p>- topology/alc_protonated.itp - Parameters for the protonated aminolipid ALC-0315 obtained from the CGenFF-Webserver</p> <p>- topology/modRNA.top - Parameters for the short modified mRNA strand. Uridine was replaced with N1-Methylpseudouridine. The parameters were not included in the standard CHARMM36 forcefield (version July 2020) and were manually added to the forcefield.</p> <p>- topology/ALC_SHORT_CORRECT_IDX.itp - Parameters for the capped PEG-ylated lipid ALC-0159 -&gt; Parameters were manually adapted to fit the shortened structure.</p> <p>- topology/charmm36-jul2020.ff - CHARMM36 forcefield parameters (version July 2020) with included parameters for N1-Methylpseudouridine.</p> <p>- topology/cgenff_output - Output from the CGenFF-Webserver to parametrize the aminolipid (ALC-0315) and the PEGylated-lipid (ALC-0159)</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Lipid-polymer nanoparticles to probe the native-like environment of intra-membrane rhomboid protease GlpG and its activity

<p><span>Polymers can facilitate detergent-free extraction of membrane proteins into nanodiscs (e.g., SMALPs, DIBMALPs), incorporating both integral membrane proteins as well as co-extracted native membrane lipids. Lipid-only SMALPs and DIBMALPs have been shown to possess a unique property; the ability to exchange lipids through &lsquo;collisional lipid mixing&rsquo;<em>.</em> Here we expand upon this mixing to include protein-containing DIBMALPs, using the rhomboid protease GlpG. Through lipidomic analysis before and after incubation with DMPC or POPC DIBMALPs, we show that lipids are rapidly exchanged between protein and lipid-only DIBMALPs, and can be used to identify bound or associated lipids through &lsquo;washing-in&rsquo; exogenous lipids. Additionally, through the requirement of rhomboid proteases to cleave intra-membrane substrates, we show that this mixing can be performed for two protein-containing DIBMALP populations, assessing the native function of intramembrane proteolysis and demonstrating that this mixing has no deleterious effects on protein stability or structure</span></p>

opencc-by-4.0Aug 2024View details →
dryad36/100

Data from: Lung and liver editing using lipid nanoparticle delivery of a stable CRISPR-Cas9 RNP

Open the record for dataset details and reuse information.

publicSep 2024View details →
zenodo32/100

Gold nanoparticles interacting with synthetic lipid rafts: an AFM investigation

<p>In this work, Atomic Force Microscopy (AFM) is employed for obtaining the first direct proof that citrated gold nanoparticles (AuNPs) adsorb preferentially along the boundaries of lipid rafts. Multicomponent Supported Lipid Bilayers (SLBs) were used as synthetic model membranes to mimic the nanometric rafts that are known to characterize the plasma membrane.&nbsp;</p>

opencc-by-4.0May 2020View details →
zenodo32/100

Long chain lipids facilitate insertion of large nanoparticles into membranes of small unilamellar vesicles

<p>DLS data and Cryo Images of SUVs-QDs</p>

opencc-by-4.0Jul 2021View details →
zenodo28/100

Fusion-dependent formation of lipid nanoparticles containing macromolecular payloads

<p>The success of Onpattro&trade; (patisiran) clearly demonstrates the utility of lipid nanoparticle (LNP) systems</p> <p>for enabling gene therapies. These systems are composed of ionizable cationic lipids, phospholipid,</p> <p>cholesterol, and polyethylene glycol (PEG)-lipids, and are produced through rapid-mixing of an ethanolic-</p> <p>lipid solution with an acidic aqueous solution followed by dialysis into neutralizing buffer. A detailed</p> <p>understanding of the mechanism of LNP formation is crucial to improving LNP design. Here we use cryogenic</p> <p>transmission electron microscopy and fluorescence techniques to further demonstrate that LNP are</p> <p>formed through the fusion of precursor, pH-sensitive liposomes into large electron-dense core structures</p> <p>as the pH is neutralized. Next, we show that the fusion process is limited by the accumulation of PEGlipid</p> <p>on the emerging particle. Finally, we show that the fusion-dependent mechanism of formation</p> <p>also applies to LNP containing macromolecular payloads including mRNA, DNA vectors, and gold</p> <p>nanoparticles.</p>

opencc-by-4.0Apr 2019View details →
zenodo28/100

Long-chain lipids facilitate insertion of large nanoparticles into membranes of small unilamellar vesicles

<div> <p>DLS data and Cryo Images of SUVs-QDs</p> <p>&nbsp;</p> </div>

opencc-by-4.0Jul 2021View details →
zenodo28/100

Supplementary data for "Comparison of ionizable lipids for lipid nanoparticle mediated DNA delivery"

Open the record for dataset details and reuse information.

opencc-by-4.0Sep 2024View details →
zenodo28/100

Lipid nanoparticle structure and delivery route during pregnancy dictates mRNA potency, immunogenicity, and maternal and fetal outcomes

<p>Raw data used for analysis</p>

opencc-by-4.0Sep 2023View details →
ClinicalTrials.gov28/100

Study of a Respiratory Syncytial Virus Candidate Encapsulated in a Lipid Nanoparticle Based Formulation in Adults Aged 18 to 50 Years and 60 Years and Older

ClinicalTrials.gov study NCT05639894. IPD Sharing: YES. Countries: 3. Publications: 0.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov28/100

Study of a Human Metapneumovirus/Respiratory Syncytial Virus mRNA Vaccine Candidate Encapsulated in a Lipid Nanoparticle-based Formulation in Adults Aged 60 Years and Older

ClinicalTrials.gov study NCT06686654. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →
geo24/100

Lipid nanoparticles deliver DNA-encoded biologics and induce potent protective immunity

GEO Series GSE272803. Mus musculus. 20 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2025View details →
geo24/100

Intratumoral administration of lipid nanoparticles carrying mRNA encoding for IL-21, IL-7, and 4-1BBL induces anti-tumor immunity in preclinical tumor models.

GEO Series GSE249674. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2024View details →
geo24/100

Lipid Nanoparticles Allow Efficient and Harmless Ex Vivo Gene Editing of Human Hematopoietic Cells [RNAseq_lnps]

GEO Series GSE216249. Homo sapiens. 36 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2023View details →
geo24/100

Lipid Nanoparticles Allow Efficient and Harmless Ex Vivo Gene Editing of Human Hematopoietic Cells [RNAseq_electro]

GEO Series GSE216248. Homo sapiens. 33 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2023View details →
geo24/100

Epigenetic metabolite lipid nanoparticles alleviate venous thrombosis via bone marrow reprogramming

GEO Series GSE283897. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJul 2025View details →

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International Brain Laboratory public data

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OpenNeuro

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Last verified 2026-04-29Open record