Valavanis Ioannis K, Bagos Pantelis G, Emiris Ioannis Z
Faculty of Informatics and Telecommunications, University of Athens, Panepistimiopolis, Athens 15784, Greece.
Comput Biol Chem. 2006 Dec;30(6):416-24. doi: 10.1016/j.compbiolchem.2006.09.001. Epub 2006 Nov 9.
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. beta-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 beta-barrels and (ii) the detection of the transmembrane region of a beta-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 beta-barrel. The transmembrane region is detected by profiling the external residues of the beta-barrel along its axis in terms of hydrophobicity and existence of aromatic and charged residues. TbB-Tool implements these algorithms and is available in . 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 beta-stranded residues along the axis of beta-barrel, thus confirming and extending other researchers' results.
在蛋白质工程中，膜脂双层相对于跨膜蛋白结构的位置很重要。由于在已确定的结构中不存在膜脂双层，因此自动定义膜嵌入蛋白区域对于测试突变效应或设计潜在药物至关重要。β-桶状跨膜蛋白作为外膜蛋白（OMPs）存在于自然界中，是两种跨膜蛋白折叠类型之一。最近，已确定结构的数量有所增加，这使得基于结构的注释方法得以实施和评估，并能对其进行更全面的研究。在本文中，我们提出了两种新算法，一种用于（i）β-桶状结构的几何建模，另一种用于（ii）检测β-桶状跨膜蛋白的跨膜区域。几何建模算法结合了非线性最小二乘最小化方法和遗传算法，以找到具有轴对称性的形状的特征（轴、半径），从而最佳地模拟β-桶状结构。通过沿β-桶状结构的轴分析其外部残基的疏水性以及芳香族和带电残基的存在情况来检测跨膜区域。TbB-Tool实现了这些算法，可通过[具体方式]获取。使用一组22个非冗余的OMP来评估所实现的算法，结果非常令人满意。此外，我们量化了沿β-桶状结构轴的外部和内部β-链残基中所有氨基酸的丰度和平均疏水性，从而证实并扩展了其他研究人员的结果。
