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蛋白质-脂质相互作用:脂质结合位点预测算法与三维结构数据的相关性

Protein-lipid interactions: correlation of a predictive algorithm for lipid-binding sites with three-dimensional structural data.

作者信息

Scott David L, Diez Gerold, Goldmann Wolfgang H

机构信息

Renal Unit, Leukocyte Biology & Inflammation Program, Structural Biology Program and the Massachusetts General Hospital/Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA.

出版信息

Theor Biol Med Model. 2006 Mar 28;3:17. doi: 10.1186/1742-4682-3-17.

Abstract

BACKGROUND

Over the past decade our laboratory has focused on understanding how soluble cytoskeleton-associated proteins interact with membranes and other lipid aggregates. Many protein domains mediating specific cell membrane interactions appear by fluorescence microscopy and other precision techniques to be partially inserted into the lipid bilayer. It is unclear whether these protein-lipid-interactions are dependent on shared protein motifs or unique regional physiochemistry, or are due to more global characteristics of the protein.

RESULTS

We have developed a novel computational program that predicts a protein's lipid-binding site(s) from primary sequence data. Hydrophobic labeling, Fourier transform infrared spectroscopy (FTIR), film balance, T-jump, CD spectroscopy and calorimetry experiments confirm that the interfaces predicted for several key cytoskeletal proteins (alpha-actinin, Arp2, CapZ, talin and vinculin) partially insert into lipid aggregates. The validity of these predictions is supported by an analysis of the available three-dimensional structural data. The lipid interfaces predicted by our algorithm generally contain energetically favorable secondary structures (e.g., an amphipathic alpha-helix flanked by a flexible hinge or loop region), are solvent-exposed in the intact protein, and possess favorable local or global electrostatic properties.

CONCLUSION

At present, there are few reliable methods to determine the region of a protein that mediates biologically important interactions with lipids or lipid aggregates. Our matrix-based algorithm predicts lipid interaction sites that are consistent with the available biochemical and structural data. To determine whether these sites are indeed correctly identified, and whether use of the algorithm can be safely extended to other classes of proteins, will require further mapping of these sites, including genetic manipulation and/or targeted crystallography.

摘要

背景

在过去十年中,我们实验室专注于了解可溶性细胞骨架相关蛋白如何与膜及其他脂质聚集体相互作用。通过荧光显微镜和其他精密技术观察发现,许多介导特定细胞膜相互作用的蛋白结构域似乎部分插入了脂质双层中。目前尚不清楚这些蛋白质 - 脂质相互作用是依赖于共享的蛋白质基序、独特的区域物理化学性质,还是由蛋白质的更整体特征所导致。

结果

我们开发了一种新颖的计算程序,可从一级序列数据预测蛋白质的脂质结合位点。疏水标记、傅里叶变换红外光谱(FTIR)、膜平衡、T 跳跃、圆二色光谱和量热实验证实,针对几种关键细胞骨架蛋白(α - 辅肌动蛋白、Arp2、CapZ、踝蛋白和纽蛋白)预测的界面部分插入脂质聚集体中。对现有三维结构数据的分析支持了这些预测的有效性。我们算法预测的脂质界面通常包含能量有利的二级结构(例如,两侧有柔性铰链或环区域的两亲性α - 螺旋),在完整蛋白质中暴露于溶剂中,并且具有有利的局部或整体静电性质。

结论

目前,几乎没有可靠的方法来确定蛋白质中介导与脂质或脂质聚集体发生生物学重要相互作用的区域。我们基于矩阵的算法预测的脂质相互作用位点与现有的生化和结构数据一致。要确定这些位点是否确实被正确识别,以及该算法的使用是否可以安全地扩展到其他类别的蛋白质,将需要对这些位点进行进一步的定位,包括基因操作和/或靶向晶体学研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7d7/1523333/2d4b976fc59a/1742-4682-3-17-1.jpg

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