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首页> 外文期刊>Proteins: Structure, Function, and Genetics >Fast de novo discovery of low-energy protein loop conformations
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Fast de novo discovery of low-energy protein loop conformations

机译:快速De Novo发现低能量蛋白质环形构象

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In the prediction of protein structure from amino acid sequence, loops are challenging regions for computational methods. Since loops are often located on the protein surface, they can have significant roles in determining protein functions and binding properties. Loop prediction without the aid of a structural template requires extensive conformational sampling and energy minimization, which are computationally difficult. In this article we present a new de novo loop sampling method, the Parallely filtered Energy Targeted All-atom Loop Sampler (PETALS) to rapidly locate low energy conformations. PETALS explores both backbone and side-chain positions of the loop region simultaneously according to the energy function selected by the user, and constructs a nonredundant ensemble of low energy loop conformations using filtering criteria. The method is illustrated with the DFIRE potential and DiSGro energy function for loops, and shown to be highly effective at discovering conformations with near-native (or better) energy. Using the same energy function as the DiSGro algorithm, PETALS samples conformations with both lower RMSDs and lower energies. PETALS is also useful for assessing the accuracy of different energy functions. PETALS runs rapidly, requiring an average time cost of 10 minutes for a length 12 loop on a single 3.2 GHz processor core, comparable to the fastest existing de novo methods for generating an ensemble of conformations. Proteins 2017; 85:1402-1412. (c) 2017 Wiley Periodicals, Inc.
机译:在从氨基酸序列预测蛋白质结构中,回路是用于计算方法的具有挑战性的区域。由于环路通常位于蛋白质表面上,因此它们可以在确定蛋白质功能和结合特性方面具有显着的作用。循环预测而不借助结构模板需要广泛的构象采样和能量最小化,这是计算困难的。在本文中,我们介绍了一种新的Novo循环采样方法,常用的滤波能量瞄准的全原子环路采样器(花瓣)快速定位低能量构象。花瓣根据用户选择的能量函数同时探讨环形区域的两个骨干和侧链位置,并且使用过滤标准构造低能量环构象的非冗余集合。该方法用循环的DFIRE电位和DISGRO能量函数说明,并且在发现具有近天然(或更好)的能量的构象时高效。使用与DISGRO算法相同的能量函数,花瓣样本与较低的RMSD和较低的能量兼容。花瓣对于评估不同能量功能的准确性也是有用的。花瓣迅速运行,在单个3.2 GHz处理器核心上的长度12环的平均时间成本为10分钟,可与用于生成构象的集合的最快现有的DE Novo方法相媲美。蛋白质2017; 85:1402-1412。 (c)2017 Wiley期刊,Inc。

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