A new protein folding algorithm based on hydrophobic compactness: Rigid Unconnected Secondary Structure Iterative Assembly (RUSSIA). II: Applications.

Denis Znamenskiy, Khan Le Tuan, Jean-Paul Mornon, Jacques Chomilier
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引用次数: 3

Abstract

The RUSSIA procedure (Rigid Unconnected Secondary Structure Iterative Assembly) produces structural models of cores of small- and medium-sized proteins. Loops are omitted from this treatment and regular secondary structures are reduced to points, the centers of their hydrophobic faces. This methodology relies on the maximum compactness of the hydrophobic residues, as described in detail in Part I. Starting data are the sequence and the predicted limits and natures of regular secondary structures (alpha or beta). Helices are treated as rigid cylinders, whereas beta-strands are collectively taken into account within beta-sheets modeled by helicoid surfaces. Strands are allowed to shift along their mean axis to allow some flexibility and the alpha-helices can be placed on either side of beta-sheets. Numerous initial conformations are produced by discrete rotations of the helices and sheets around the direction going from the center of their hydrophobic face to the global center of the protein. Selection of proposed models is based upon a criterion lying on the minimization of distances separating hydrophobic residues belonging to different regular secondary structures. The procedure is rapid and appears to be robust relative to the quality of starting data (nature and length of regular secondary structures). This dependence of the quality of the model on secondary structure prediction and in particular the beta-sheet topology, is one of the limits of the present algorithm. We present here some results for a set of 12 proteins (alpha, beta and alpha/beta classes) of lengths 40-166 amino acids. The r.m.s. deviations for core models with respect to the native proteins are in the range 1.4-3.7 A.

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一种基于疏水紧密性的蛋白质折叠新算法:刚性非连接二级结构迭代组装(俄罗斯)。2:应用程序。
俄罗斯程序(刚性无连接二级结构迭代组装)产生了中小型蛋白质核心的结构模型。回路从这种处理中被省略,规则的二级结构被简化为点,即它们疏水面的中心。该方法依赖于疏水残基的最大紧密度,如第一部分中详细描述的那样。起始数据是规则二级结构(α或β)的序列和预测极限和性质。螺旋被视为刚性圆柱体,而β -链在由螺旋面模拟的β -片内被集体考虑。链可以沿着它们的平均轴移动,以获得一定的灵活性,而α螺旋可以放置在β薄片的两侧。螺旋和薄片沿着从疏水面中心到蛋白质整体中心的方向进行离散旋转,产生了许多初始构象。所提出的模型的选择是基于一个准则,即属于不同规则二级结构的疏水残基分离距离的最小化。这个过程是快速的,并且相对于起始数据的质量(规则二级结构的性质和长度)似乎是健壮的。这种依赖于二级结构预测的模型质量,特别是β -薄片拓扑,是本算法的局限性之一。我们在这里给出了长度为40-166个氨基酸的12种蛋白质(α、β和α / β类)的一些结果。核心模型相对于天然蛋白的均方根偏差在1.4-3.7 A之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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