Suppr超能文献

脂滴单层整合蛋白的蛋白质组学分析鉴定出两亲性界面 α-螺旋膜锚。

Proteomic analysis of monolayer-integrated proteins on lipid droplets identifies amphipathic interfacial α-helical membrane anchors.

机构信息

Department of Biochemistry, Stanford University, Stanford, CA 94305.

Department of Structural Biology, Stanford University, Stanford, CA 94305.

出版信息

Proc Natl Acad Sci U S A. 2018 Aug 28;115(35):E8172-E8180. doi: 10.1073/pnas.1807981115. Epub 2018 Aug 13.

Abstract

Despite not spanning phospholipid bilayers, monotopic integral proteins (MIPs) play critical roles in organizing biochemical reactions on membrane surfaces. Defining the structural basis by which these proteins are anchored to membranes has been hampered by the paucity of unambiguously identified MIPs and a lack of computational tools that accurately distinguish monolayer-integrating motifs from bilayer-spanning transmembrane domains (TMDs). We used quantitative proteomics and statistical modeling to identify 87 high-confidence candidate MIPs in lipid droplets, including 21 proteins with predicted TMDs that cannot be accommodated in these monolayer-enveloped organelles. Systematic cysteine-scanning mutagenesis showed the predicted TMD of one candidate MIP, DHRS3, to be a partially buried amphipathic α-helix in both lipid droplet monolayers and the cytoplasmic leaflet of endoplasmic reticulum membrane bilayers. Coarse-grained molecular dynamics simulations support these observations, suggesting that this helix is most stable at the solvent-membrane interface. The simulations also predicted similar interfacial amphipathic helices when applied to seven additional MIPs from our dataset. Our findings suggest that interfacial helices may be a common motif by which MIPs are integrated into membranes, and provide high-throughput methods to identify and study MIPs.

摘要

尽管非跨膜磷脂双层的单次跨膜蛋白(MIP)在膜表面上组织生化反应中起着关键作用,但确定这些蛋白质锚定在膜上的结构基础一直受到以下两个因素的阻碍:明确鉴定的 MIP 数量稀少,以及缺乏能够准确区分单层整合基序与跨双层跨膜结构域(TMD)的计算工具。我们使用定量蛋白质组学和统计建模在脂滴中鉴定了 87 种高可信度的候选 MIP,其中包括 21 种具有预测 TMD 的蛋白质,这些 TMD 不能容纳在这些单层包裹的细胞器中。系统的半胱氨酸扫描突变显示,一种候选 MIP(DHRS3)的预测 TMD 在脂滴单层和内质网膜双层的细胞质叶中是部分埋藏的两亲性α-螺旋。粗粒度分子动力学模拟支持这些观察结果,表明该螺旋在溶剂-膜界面处最稳定。当应用于我们数据集的另外七个 MIP 时,模拟还预测了类似的界面两亲性螺旋。我们的研究结果表明,界面螺旋可能是 MIP 整合到膜中的常见基序,并提供了识别和研究 MIP 的高通量方法。

相似文献

2
Interaction of a model apolipoprotein, apoLp-III, with an oil-phospholipid interface.模型载脂蛋白 apoLp-III 与油-磷脂界面的相互作用。
Biochim Biophys Acta Biomembr. 2018 Feb;1860(2):396-406. doi: 10.1016/j.bbamem.2017.10.008. Epub 2017 Oct 10.
7
Lipid structure in triolein lipid droplets.三油精脂质滴中的脂质结构。
J Phys Chem B. 2014 Sep 4;118(35):10335-40. doi: 10.1021/jp503223z. Epub 2014 Aug 20.

引用本文的文献

1
Selenoprotein K at the intersection of cellular pathways.位于细胞通路交叉点的硒蛋白K
Arch Biochem Biophys. 2025 Feb;764:110221. doi: 10.1016/j.abb.2024.110221. Epub 2024 Nov 20.
2
The Lipid Droplet Protein DHRS3 Is a Regulator of Melanoma Cell State.脂滴蛋白DHRS3是黑色素瘤细胞状态的调节因子。
Pigment Cell Melanoma Res. 2025 Jan;38(1):e13208. doi: 10.1111/pcmr.13208. Epub 2024 Oct 31.
7
Intracellular lipase and regulation of the lipid droplet.细胞内脂肪酶和脂滴的调节。
Curr Opin Lipidol. 2024 Apr 1;35(2):85-92. doi: 10.1097/MOL.0000000000000918. Epub 2024 Feb 15.

本文引用的文献

2
Establishing the lipid droplet proteome: Mechanisms of lipid droplet protein targeting and degradation.建立脂滴蛋白质组学:脂滴蛋白靶向和降解的机制。
Biochim Biophys Acta Mol Cell Biol Lipids. 2017 Oct;1862(10 Pt B):1166-1177. doi: 10.1016/j.bbalip.2017.06.006. Epub 2017 Jun 13.
4
Lipidated proteins: Spotlight on protein-membrane binding interfaces.脂化蛋白:聚焦蛋白质-膜结合界面
Prog Biophys Mol Biol. 2017 Sep;128:74-84. doi: 10.1016/j.pbiomolbio.2017.01.002. Epub 2017 Feb 3.
7
Targeting Fat: Mechanisms of Protein Localization to Lipid Droplets.靶向脂肪:蛋白质定位于脂滴的机制
Trends Cell Biol. 2016 Jul;26(7):535-546. doi: 10.1016/j.tcb.2016.02.007. Epub 2016 Mar 16.
8
Membrane lipid compositional sensing by the inducible amphipathic helix of CCT.通过CCT的诱导性两亲螺旋进行膜脂成分传感。
Biochim Biophys Acta. 2016 Aug;1861(8 Pt B):847-861. doi: 10.1016/j.bbalip.2015.12.022. Epub 2015 Dec 31.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验