Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles

化学 纳米颗粒 钥匙(锁) 纳米技术 材料科学 计算机科学 计算机安全
作者
Giulio Tesei,Ya‐Wen Hsiao,Aleksandra P. Dabkowska,Gunnar Grönberg,Marianna Yanez Arteta,David Ulkoski,David J. Bray,Martin Trulsson,Johan Ulander,Mikael Lund,Lennart Lindfors
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [Proceedings of the National Academy of Sciences]
卷期号:121 (2) 被引量:32
标识
DOI:10.1073/pnas.2311700120
摘要

The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo-the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory. All-atom molecular dynamics simulations, and experimentally measured polar headgroup pKa values, are used to develop a coarse-grained representation of the lipids, which enables the investigation of the pH-dependent behavior of lipid nanoparticles (LNPs) through Monte Carlo simulations, in the absence and presence of RNA molecules. Our results show that the charge state of the lipids is determined by the interplay between lipid shape and headgroup chemistry, providing an explanation for the similar pH-dependent ionization state observed for lipids with headgroup pKa values about one-pH-unit apart. The pH dependence of lipid ionization is significantly influenced by the presence of RNA, whereby charge neutrality is achieved by imparting a finite and constant charge per lipid at intermediate pH values. The simulation results are experimentally supported by measurements of α-carbon 13C-NMR chemical shifts for eGFP mRNA LNPs of both DLin-MC3-DMA and DLin-DMA at various pH conditions. Further, we evaluate the applicability of a mean-field Poisson-Boltzmann theory to capture these phenomena.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
up发布了新的文献求助10
刚刚
墨墨叻完成签到,获得积分10
刚刚
娇娇完成签到,获得积分10
刚刚
叶子发布了新的文献求助10
刚刚
wanci应助豆豆采纳,获得10
1秒前
1秒前
free发布了新的文献求助10
2秒前
guagua完成签到 ,获得积分10
2秒前
虚幻故事完成签到,获得积分10
2秒前
廿二完成签到 ,获得积分10
2秒前
量子星尘发布了新的文献求助10
2秒前
atmosphere发布了新的文献求助10
3秒前
小锤完成签到,获得积分10
3秒前
oohQoo完成签到,获得积分10
3秒前
YQF完成签到,获得积分10
4秒前
九日完成签到,获得积分10
5秒前
科研彭于晏完成签到,获得积分10
5秒前
Earnestlee完成签到,获得积分10
5秒前
英俊的铭应助yan采纳,获得10
6秒前
愿景完成签到,获得积分10
6秒前
sad完成签到,获得积分10
6秒前
luckyhan发布了新的文献求助10
6秒前
Shinewei完成签到,获得积分10
6秒前
Owen应助wsafhgfjb采纳,获得10
7秒前
7秒前
7秒前
alv完成签到,获得积分10
7秒前
cc2941完成签到,获得积分10
7秒前
壳壳完成签到,获得积分10
7秒前
丘比特应助风暴采纳,获得10
8秒前
Lychee完成签到 ,获得积分10
8秒前
8秒前
8秒前
五斤老陈醋完成签到,获得积分10
8秒前
8秒前
8秒前
Jasper应助fr0zen采纳,获得10
8秒前
9秒前
HHHZZZ完成签到,获得积分10
9秒前
panini完成签到,获得积分10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1621
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] | NHBS Field Guides & Natural History 1500
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 1000
Brittle fracture in welded ships 1000
Metagames: Games about Games 700
King Tyrant 680
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5573825
求助须知:如何正确求助?哪些是违规求助? 4660098
关于积分的说明 14727788
捐赠科研通 4599933
什么是DOI,文献DOI怎么找? 2524546
邀请新用户注册赠送积分活动 1494900
关于科研通互助平台的介绍 1464997