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通过模板匹配实现自动侧链模型构建和序列分配。

Automated side-chain model building and sequence assignment by template matching.

作者信息

Terwilliger Thomas C

机构信息

Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

出版信息

Acta Crystallogr D Biol Crystallogr. 2003 Jan;59(Pt 1):45-9. doi: 10.1107/s0907444902018048. Epub 2002 Dec 19.

Abstract

An algorithm is described for automated building of side chains in an electron-density map once a main-chain model is built and for alignment of the protein sequence to the map. The procedure is based on a comparison of electron density at the expected side-chain positions with electron-density templates. The templates are constructed from average amino-acid side-chain densities in 574 refined protein structures. For each contiguous segment of main chain, a matrix with entries corresponding to an estimate of the probability that each of the 20 amino acids is located at each position of the main-chain model is obtained. The probability that this segment corresponds to each possible alignment with the sequence of the protein is estimated using a Bayesian approach and high-confidence matches are kept. Once side-chain identities are determined, the most probable rotamer for each side chain is built into the model. The automated procedure has been implemented in the RESOLVE software. Combined with automated main-chain model building, the procedure produces a preliminary model suitable for refinement and extension by an experienced crystallographer.

摘要

本文描述了一种算法,用于在构建主链模型后自动在电子密度图中构建侧链,并将蛋白质序列与该图进行比对。该程序基于将预期侧链位置的电子密度与电子密度模板进行比较。这些模板由574个精制蛋白质结构中的平均氨基酸侧链密度构建而成。对于主链的每个连续片段,会得到一个矩阵,其元素对应于20种氨基酸中每种氨基酸位于主链模型每个位置的概率估计值。使用贝叶斯方法估计该片段与蛋白质序列的每种可能比对的概率,并保留高置信度匹配。一旦确定了侧链身份,就会将每个侧链最可能的旋转异构体构建到模型中。该自动化程序已在RESOLVE软件中实现。与自动主链模型构建相结合,该程序会生成一个适合由经验丰富的晶体学家进行优化和扩展的初步模型。

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