MUSTANG-MR Structural Sieving Server: Applications in Protein Structural Analysis and Crystallography
MUSTANG-MR Structural Sieving Server: Applications in Protein Structural Analysis and Crystallography
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DOI：
10.1371/journal.pone.0010048
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发表时间：
2010-04-06
期刊：
影响因子：
3.7
通讯作者：
Buckle, Ashley M.
中科院分区：
文献类型：
--
作者：
Konagurthu, Arun S.;Reboul, Cyril F.;Buckle, Ashley M.
背景：结构生物学的一个中心原则是具有共同功能的相关蛋白质具有结构相似性。这对蛋白质结构的推导和分析具有关键的实际影响，并且通过“分子筛”过程被利用，其中共同的核心逐渐从两个或更多个蛋白质结构的比较中提取出来。本文报道了一种新的网络服务器的“筛选”的蛋白质结构，基于多结构比对程序MUSTANG。方法/主要发现：“筛选”的模型是从MUSTANG产生的多个比对和叠加通过迭代过滤出噪音的残基残基对应，直到在模型中得到的对应是最佳的“叠加”下的RMSD阈值。这种残差水平筛选还伴随着从输入集合中迭代消除拟合差的结构。因此，通过改变RMSD的阈值和集合的基数，针对来自MUSTANG的给定多重比对和叠加生成多个筛选模型。为了帮助识别在蛋白质结构的集合中具有功能重要性的结构保守区域，生成Lesk-Hubbard图，绘制叠加中残基对应的数量作为其相应RMSD的函数。保守的“核心”结论：该方法解决了结构生物学中的两个基本问题：第一，确定结构相关蛋白质的共同亚结构，这是表征和预测功能的重要问题;第二，筛选模型的产生与使用分子置换技术在蛋白质晶体结构测定中的应用。
Background: A central tenet of structural biology is that related proteins of common function share structural similarity. This has key practical consequences for the derivation and analysis of protein structures, and is exploited by the process of "molecular sieving" whereby a common core is progressively distilled from a comparison of two or more protein structures. This paper reports a novel web server for "sieving" of protein structures, based on the multiple structural alignment program MUSTANG.Methodology/Principal Findings: "Sieved" models are generated from MUSTANG-generated multiple alignment and superpositions by iteratively filtering out noisy residue-residue correspondences, until the resultant correspondences in the models are optimally "superposable" under a threshold of RMSD. This residue-level sieving is also accompanied by iterative elimination of the poorly fitting structures from the input ensemble. Therefore, by varying the thresholds of RMSD and the cardinality of the ensemble, multiple sieved models are generated for a given multiple alignment and superposition from MUSTANG. To aid the identification of structurally conserved regions of functional importance in an ensemble of protein structures, Lesk-Hubbard graphs are generated, plotting the number of residue correspondences in a superposition as a function of its corresponding RMSD. The conserved "core" (or typically active site) shows a linear trend, which becomes exponential as divergent parts of the structure are included into the superposition.Conclusions: The application addresses two fundamental problems in structural biology: First, the identification of common substructures among structurally related proteins-an important problem in characterization and prediction of function; second, generation of sieved models with demonstrated uses in protein crystallographic structure determination using the technique of Molecular Replacement.