Protein structure database search and evolutionary classification.

Protein structure database search and evolutionary classification.
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DOI:
10.1093/nar/gkl395
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发表时间:
2006
影响因子:
14.9
通讯作者:
Tung CH
Tung CH
中科院分区:
生物学2区
文献类型:
--
作者:
Yang JM;Tung CH

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随着越来越多的蛋白质结构变得可用,结构基因组学的努力在全基因组策略中提供了结构模型,越来越需要快速准确的方法来发现同源蛋白质和新确定结构的进化分类。我们开发了3D-BLAST,部分是为了解决这些问题。3D-BLAST与BLAST一样快,并且计算比对的统计显著性(E值)以指示预测的可靠性。使用这种方法,我们首先确定了23个国家的结构字母表,代表模式配置文件的骨干片段,然后用它们来表示蛋白质结构数据库作为结构字母序列数据库(SADB)。我们的方法增强了BLAST作为一种搜索方法,使用一个新的结构字母表替换矩阵(SASM),找到最长的共同子结构与高得分的结构化片段对从SADB数据库。使用Intel Pentium 4(2.8 GHz)处理器的个人计算机,我们的方法在1.3 s内搜索了超过10000个蛋白质结构,并与详细结构比对方法的搜索结果取得了很好的一致性。[3D-BLAST可在]
As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at ]
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