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β-Barrel transmembrane proteins: Geometric modelling, detection of transmembrane region, and structural properties

机译:β-桶状跨膜蛋白:几何建模,跨膜区域检测和结构特性

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摘要

The location of the membrane lipid bilayer relative to a transmembrane protein structure is important in protein engineering. Since it is not present on the determined structures, it is essential to automatically define the membrane embedded protein region in order to test mutation effects or to design potential drugs. β-Barrel transmembrane proteins, present in nature as outer membrane proteins (OMPs), comprise one of the two transmembrane protein fold classes. Lately, the number of their determined structures has increased and this enables the implementation and evaluation of structure-based annotation methods and their more comprehensive study. In this paper, we propose two new algorithms for (ⅰ) the geometric modelling of β-barrels and (ⅱ) the detection of the transmembrane region of a β-barrel transmembrane protein. The geometric modelling algorithm combines a non-linear least square minimization method and a genetic algorithm in order to find the characteristics (axis, radius) of a shape with axial symmetry which best models a β-barrel. The transmembrane region is detected by profiling the external residues of the β-barrel along its axis in terms of hydrophobicity and existence of aromatic and charged residues. TbB-Tool implements these algorithms and is available in http://www.di.uoa.gr/~ivalavan/TbB_Tool.htm. A non-redundant set of 22 OMPs is used in order to evaluate the algorithms implemented and the results are very satisfying. In addition, we quantify the abundance of all amino acids and the average hydrophobicity for external and internal β-stranded residues along the axis of β-barrel, thus confirming and extending other researchers' results.
机译:膜脂质双层相对于跨膜蛋白质结构的位置在蛋白质工程中很重要。由于它不存在于确定的结构中,因此必须自动定义膜嵌入的蛋白区域,以测试突变效果或设计潜在的药物。自然界中以外膜蛋白(OMP)形式存在的β-桶形跨膜蛋白包含两个跨膜蛋白折叠类别之一。最近,它们确定的结构数量增加了,这使基于结构的注释方法的实施和评估以及更全面的研究成为可能。在本文中,我们提出了两种新算法用于(ⅰ)β桶的几何建模和(ⅱ)检测β桶的跨膜蛋白的跨膜区域。几何建模算法将非线性最小二乘最小化方法和遗传算法相结合,以找到具有轴向对称性的形状的特征(轴,半径),从而最好地建模β形桶。通过沿疏水性以及存在的芳香族和带电残基的存在沿着桶的外部轮廓分析β-桶的外部残基,可以检测跨膜区域。 TbB-Tool实现了这些算法,可从http://www.di.uoa.gr/~ivalavan/TbB_Tool.htm中获得。为了评估实现的算法,使用了22个OMP的非冗余集,结果非常令人满意。此外,我们量化了所有氨基酸的含量以及沿β-桶轴的内部和外部β链残基的平均疏水性,从而证实并扩展了其他研究人员的研究结果。

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