Building an automated classification of DNA-binding protein domains.
Building an automated classification of DNA-binding protein domains.
复制标题
构建 DNA 结合蛋白结构域的自动分类。
DOI：
10.1093/bioinformatics/18.suppl_2.s192
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Shindyalov,IlyaN
中科院分区：
文献类型：
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作者：
Ponomarenko,JuliaV;Bourne,PhilipE;Shindyalov,IlyaN
密集增长的DNA-蛋白质复合物的3D结构数据反映在蛋白质数据库（PDB）需要新的方法来注释和表征这些数据，并将导致涉及这些数据的关键生物过程的新的理解。这些数据和来自其他蛋白质结构分类的数据对于完整蛋白质组的建模将变得越来越重要。我们提出了一个完全自动化的分类DNA结合蛋白质结构域的基础上现有的3D结构的PDB。按结构域的分类依赖于蛋白质结构域解析器（PDP）和组合扩展（CE）算法进行结构比对。该方法涉及DNA-蛋白质界面的3D相互作用模式的分析，与DNA相互作用的结构域的分配，基于结构相似性和DNA相互作用模式的结构域的聚类。与现有的资源描述的DNA结合蛋白的结构和功能分类的比较，用于验证和改进这里提出的方法。在我们的研究过程中，我们定义了一组标准和分类学，使我们能够自动建立一个有生物学意义的分类，并定义功能相关的蛋白质结构域的类别。结果表明，考虑到蛋白质结构域和DNA之间的相互作用，大大提高了分类精度。我们的方法提供了DNA结合蛋白家族的高通量和最新注释，可在http：//spdc上找到。sdsc。edu.联系人：shindyal@ sdsc. edu
Intensive growth in 3D structure data on DNA-protein complexes as reflected in the Protein Data Bank (PDB) demands new approaches to the annotation and characterization of these data and will lead to a new understanding of critical biological processes involving these data. These data and those from other protein structure classifications will become increasingly important for the modeling of complete proteomes. We propose a fully automated classification of DNA-binding protein domains based on existing 3D-structures from the PDB. The classification, by domain, relies on the Protein Domain Parser (PDP) and the Combinatorial Extension (CE) algorithm for structural alignment. The approach involves the analysis of 3D-interaction patterns in DNA-protein interfaces, assignment of structural domains interacting with DNA, clustering of domains based on structural similarity and DNA-interacting patterns. Comparison with existing resources on describing structural and functional classifications of DNA-binding proteins was used to validate and improve the approach proposed here. In the course of our study we defined a set of criteria and heuristics allowing us to automatically build a biologically meaningful classification and define classes of functionally related protein domains. It was shown that taking into consideration interactions between protein domains and DNA considerably improves the classification accuracy. Our approach provides a high-throughput and up-to-date annotation of DNA-binding protein families which can be found at http://spdc. sdsc. edu. Contact: shindyal@ sdsc. edu