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自动工具和基于模板的 CASP8 目标蛋白建模中的人类专业知识的使用。

The use of automatic tools and human expertise in template-based modeling of CASP8 target proteins.

机构信息

Institute of Biotechnology, Graiciūno 8, LT-02241 Vilnius, Lithuania.

出版信息

Proteins. 2009;77 Suppl 9:81-8. doi: 10.1002/prot.22515.

DOI:10.1002/prot.22515
PMID:19639635
Abstract

Here, we describe our template-based protein modeling approach and its performance during the eighth community-wide experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP8, http://predictioncenter.org/casp8). In CASP8, our modeling approach was supplemented by the newly developed distant homology detection method based on sequence profile-profile comparison. Detection of structural homologs that could be used as modeling templates was largely achieved by automated profile-based searches. However, the other two major steps in template-based modeling (TBM) (selection of the best template(s) and construction of the optimal sequence-structure alignment) to a large degree relied on the combination of automatic tools and manual input. The analysis of 64 domains categorized by CASP8 assessors as TBM domains revealed that we missed correct structural templates for only four of them. The use of multiple templates or their fragments enabled us to improve over the structure of the single best PDB template in about 1/3 of our models for TBM domains. Our results for sequence-structure alignments are mixed. Although many models have optimal or near optimal sequence mapping, a large fraction contains one or more misaligned regions. Strikingly, in spite of this, our TBM models have the best overall alignment accuracy scores. This clearly suggests that the correct mapping of protein sequence onto three-dimensional structure remains one of the big challenges in protein structure prediction.

摘要

在这里,我们描述了我们基于模板的蛋白质建模方法及其在第八届蛋白质结构预测技术评估国际竞赛(CASP8,http://predictioncenter.org/casp8)中的表现。在 CASP8 中,我们的建模方法得到了新开发的基于序列轮廓-轮廓比较的远距离同源检测方法的补充。结构同源物的检测可以作为建模模板,主要通过自动化的基于轮廓的搜索来实现。然而,基于模板建模(TBM)的另外两个主要步骤(最佳模板的选择和最佳序列-结构比对的构建)在很大程度上依赖于自动工具和人工输入的结合。对 CASP8 评估者分类为 TBM 域的 64 个结构域的分析表明,我们仅错过了其中四个结构域的正确结构模板。使用多个模板或它们的片段使我们能够在大约 1/3 的 TBM 结构域模型中,对单个最佳 PDB 模板的结构进行改进。我们在序列-结构比对方面的结果喜忧参半。虽然许多模型具有最佳或接近最佳的序列映射,但很大一部分模型包含一个或多个未对齐的区域。引人注目的是,尽管如此,我们的 TBM 模型仍具有最佳的整体比对准确性评分。这清楚地表明,将蛋白质序列正确映射到三维结构仍然是蛋白质结构预测中的一大挑战。

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