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一种膜蛋白中氨基酸相互作用的综合计算研究。

A comprehensive computational study of amino acid interactions in membrane proteins.

机构信息

Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium.

Department of Mathematics and Informatics, Cheikh Anta Diop University, Dakar-Fann, Senegal.

出版信息

Sci Rep. 2019 Aug 19;9(1):12043. doi: 10.1038/s41598-019-48541-2.

DOI:10.1038/s41598-019-48541-2
PMID:31427701
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6700154/
Abstract

Transmembrane proteins play a fundamental role in a wide series of biological processes but, despite their importance, they are less studied than globular proteins, essentially because their embedding in lipid membranes hampers their experimental characterization. In this paper, we improved our understanding of their structural stability through the development of new knowledge-based energy functions describing amino acid pair interactions that prevail in the transmembrane and extramembrane regions of membrane proteins. The comparison of these potentials and those derived from globular proteins yields an objective view of the relative strength of amino acid interactions in the different protein environments, and their role in protein stabilization. Separate potentials were also derived from α-helical and β-barrel transmembrane regions to investigate possible dissimilarities. We found that, in extramembrane regions, hydrophobic residues are less frequent but interactions between aromatic and aliphatic amino acids as well as aromatic-sulfur interactions contribute more to stability. In transmembrane regions, polar residues are less abundant but interactions between residues of equal or opposite charges or non-charged polar residues as well as anion-π interactions appear stronger. This shows indirectly the preference of the water and lipid molecules to interact with polar and hydrophobic residues, respectively. We applied these new energy functions to predict whether a residue is located in the trans- or extramembrane region, and obtained an AUC score of 83% in cross validation, which demonstrates their accuracy. As their application is, moreover, extremely fast, they are optimal instruments for membrane protein design and large-scale investigations of membrane protein stability.

摘要

跨膜蛋白在广泛的生物过程中起着至关重要的作用,但与球状蛋白相比,它们的研究较少,这主要是因为它们嵌入脂质膜中,阻碍了对其进行实验表征。在本文中,我们通过开发新的基于知识的能量函数来改进对它们结构稳定性的理解,这些能量函数描述了在膜蛋白的跨膜和膜外区域中起主导作用的氨基酸对相互作用。这些势与来自球状蛋白的势进行比较,可以客观地了解不同蛋白质环境中氨基酸相互作用的相对强度,以及它们在蛋白质稳定化中的作用。还分别从α-螺旋和β桶跨膜区域中得出了单独的势,以研究可能存在的差异。我们发现,在膜外区域,疏水性残基较少,但芳香族和脂族氨基酸之间以及芳香族-硫之间的相互作用对稳定性的贡献更大。在跨膜区域中,极性残基较少,但相同或相反电荷或非极性极性残基之间以及阴离子-π相互作用的相互作用似乎更强。这间接表明水分子和脂质分子分别与极性和疏水性残基相互作用的偏好。我们将这些新的能量函数应用于预测残基是否位于跨膜或膜外区域,在交叉验证中获得了 83%的 AUC 分数,这证明了它们的准确性。此外,由于它们的应用速度极快,因此它们是膜蛋白设计和大规模膜蛋白稳定性研究的理想工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/5944abcb10a0/41598_2019_48541_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/3aab6025e452/41598_2019_48541_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/f2b6afa3b378/41598_2019_48541_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/8b89c2295ce5/41598_2019_48541_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/7bb1803cc4a4/41598_2019_48541_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/ccaf081f7971/41598_2019_48541_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/9f231f385f55/41598_2019_48541_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/1f4e00ac19ff/41598_2019_48541_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/216b401f6d8e/41598_2019_48541_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/5944abcb10a0/41598_2019_48541_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/3aab6025e452/41598_2019_48541_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/f2b6afa3b378/41598_2019_48541_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/8b89c2295ce5/41598_2019_48541_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/7bb1803cc4a4/41598_2019_48541_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/ccaf081f7971/41598_2019_48541_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/9f231f385f55/41598_2019_48541_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/1f4e00ac19ff/41598_2019_48541_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/216b401f6d8e/41598_2019_48541_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bc6/6700154/5944abcb10a0/41598_2019_48541_Fig9_HTML.jpg

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