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检测局部残基环境相似性以识别近天然结构模型。

Detecting local residue environment similarity for recognizing near-native structure models.

作者信息

Kim Hyungrae, Kihara Daisuke

机构信息

Department of Biological Sciences, Purdue University, West Lafayette, Indiana, 47906.

出版信息

Proteins. 2014 Dec;82(12):3255-72. doi: 10.1002/prot.24658. Epub 2014 Oct 30.

Abstract

We developed a new representation of local amino acid environments in protein structures called the Side-chain Depth Environment (SDE). An SDE defines a local structural environment of a residue considering the coordinates and the depth of amino acids that locate in the vicinity of the side-chain centroid of the residue. SDEs are general enough that similar SDEs are found in protein structures with globally different folds. Using SDEs, we developed a procedure called PRESCO (Protein Residue Environment SCOre) for selecting native or near-native models from a pool of computational models. The procedure searches similar residue environments observed in a query model against a set of representative native protein structures to quantify how native-like SDEs in the model are. When benchmarked on commonly used computational model datasets, our PRESCO compared favorably with the other existing scoring functions in selecting native and near-native models.

摘要

我们开发了一种蛋白质结构中局部氨基酸环境的新表示方法,称为侧链深度环境(SDE)。SDE通过考虑位于残基侧链质心附近的氨基酸的坐标和深度来定义残基的局部结构环境。SDE具有足够的通用性,以至于在具有全局不同折叠的蛋白质结构中也能发现相似的SDE。利用SDE,我们开发了一种名为PRESCO(蛋白质残基环境评分)的程序,用于从一组计算模型中选择天然或接近天然的模型。该程序在一组代表性的天然蛋白质结构中搜索查询模型中观察到的相似残基环境,以量化模型中SDE与天然状态的相似程度。在常用的计算模型数据集上进行基准测试时,我们的PRESCO在选择天然和接近天然的模型方面与其他现有评分函数相比具有优势。

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