纳米技术
分辨率(逻辑)
计算机科学
纳米颗粒
计算生物学
药物输送
化学
材料科学
生物
人工智能
作者
Lisbeth R. Kjølbye,Mariana Valério,Markéta Paloncýová,Luís Borges-Araújo,Roberto Pestana-Nobles,Fabian Grünewald,Bart M. H. Bruininks,Rocío Araya‐Osorio,Martin Šrejber,Raúl Mera‐Adasme,LUCA MONTICELL,Siewert J. Marrink,Michal Otyepka,SANGWOOK WU,Paulo C. T. Souza
标识
DOI:10.26434/chemrxiv-2024-bf4n8
摘要
Lipid nanoparticles (LNPs) represent a promising platform for advanced drug and gene delivery, yet optimizing these particles for specific cargos and cell targets poses a complex, multifaceted challenge. Furthermore, there is a pressing need for a more comprehensive understanding of the underlying technology. Experimental studies are costly and often provide low-resolution information. Molecular dynamics (MD) simulations allow us to study these particles at a higher resolution, enhancing our understanding. However, studying these systems at atomic resolutions is both challenging and computationally expensive, as well as time-consuming. Coarse-grained (CG) models, such as Martini 3, are positioned as promising tools for studying LNPs. To enable CG-MD studies of LNPs, accurate and validated models of their components are needed. Here, we present a substantial extension of the Martini 3 library of lipids, covering the most important LNP components, including over a hundred of ionizable lipid (IL) models, along with natural occurring sterol models and PEGylated lipid models. We furthermore present initial protocols for screening fusion efficacy across different lipid formulations and for constructing whole LNPs at CG resolution, enabling future studies of these nanoparticles.
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