Suppr超能文献

G蛋白偶联受体跨膜螺旋结构域中的疏水性图谱。

Hydrophobicity profiles in G protein-coupled receptor transmembrane helical domains.

作者信息

Crasto Chiquito J

机构信息

Division of Research, Department of genetics, University of Alabama at Birmingham, Alabama, UsA.

出版信息

J Receptor Ligand Channel Res. 2010;2010(3):123-133. doi: 10.2147/JRLCR.S14437.

Abstract

The lack of a crystallographically derived structure for all but three G (TP [guanosine triphosphate]-binding) protein-coupled receptor (GPCRs) proteins necessitates the use of computationally derived methods to determine their structures. Computational methodologies allow a mechanistic glimpse into GPCR-ligand interactions at a molecular level to better understand the initial steps leading to a protein's biologic functions, ie, protecting the ligands that activate, deactivate, or inhibit the protein, stabilizing protein structure in the membrane's lipid bilayer, and ensuring that the hydrophilic environment within the GPCR-binding pocket is maintained. Described here is a formalism that quantifies the amphiphilic nature of a helix, by determining the effective hydrophobicity (or hydrophilicity) at specific positions around it. This formalism will enable computational protein modelers to position helices so that the functional aspects of GPCRs are adequately represented in the model. Hydro-Eff®, an online tool, allows users to calculate effective helical hydrophobicities.

摘要

除了三种G(三磷酸鸟苷结合)蛋白偶联受体(GPCR)蛋白外,其他GPCR蛋白缺乏晶体学推导的结构,因此需要使用计算推导的方法来确定其结构。计算方法能够在分子水平上对GPCR-配体相互作用进行机理洞察,从而更好地理解导致蛋白质生物学功能的初始步骤,即保护激活、失活或抑制该蛋白质的配体,稳定膜脂双层中的蛋白质结构,并确保GPCR结合口袋内的亲水环境得以维持。本文描述了一种形式主义,通过确定螺旋周围特定位置的有效疏水性(或亲水性)来量化螺旋的两亲性。这种形式主义将使计算蛋白质建模人员能够定位螺旋,从而在模型中充分体现GPCR的功能方面。在线工具Hydro-Eff®允许用户计算有效的螺旋疏水性。

相似文献

8
X-ray structure breakthroughs in the GPCR transmembrane region.G蛋白偶联受体跨膜区域的X射线结构突破。
Biochem Pharmacol. 2009 Jul 1;78(1):11-20. doi: 10.1016/j.bcp.2009.02.012. Epub 2009 Feb 27.

本文引用的文献

8
Structure of a beta1-adrenergic G-protein-coupled receptor.β1-肾上腺素能G蛋白偶联受体的结构
Nature. 2008 Jul 24;454(7203):486-91. doi: 10.1038/nature07101. Epub 2008 Jun 25.
9
The Jpred 3 secondary structure prediction server.Jpred 3二级结构预测服务器。
Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W197-201. doi: 10.1093/nar/gkn238. Epub 2008 May 7.
10
Comparative protein structure modeling using MODELLER.使用MODELLER进行比较蛋白质结构建模。
Curr Protoc Protein Sci. 2007 Nov;Chapter 2:Unit 2.9. doi: 10.1002/0471140864.ps0209s50.

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